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Kringelbach ML, Sanz Perl Y, Deco G. The Thermodynamics of Mind. Trends Cogn Sci 2024:S1364-6613(24)00075-5. [PMID: 38677884 DOI: 10.1016/j.tics.2024.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 03/16/2024] [Accepted: 03/18/2024] [Indexed: 04/29/2024]
Abstract
To not only survive, but also thrive, the brain must efficiently orchestrate distributed computation across space and time. This requires hierarchical organisation facilitating fast information transfer and processing at the lowest possible metabolic cost. Quantifying brain hierarchy is difficult but can be estimated from the asymmetry of information flow. Thermodynamics has successfully characterised hierarchy in many other complex systems. Here, we propose the 'Thermodynamics of Mind' framework as a natural way to quantify hierarchical brain orchestration and its underlying mechanisms. This has already provided novel insights into the orchestration of hierarchy in brain states including movie watching, where the hierarchy of the brain is flatter than during rest. Overall, this framework holds great promise for revealing the orchestration of cognition.
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Affiliation(s)
- Morten L Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK; Department of Psychiatry, University of Oxford, Oxford, UK; Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; International Centre for Flourishing, Universities of Oxford, Aarhus, and Pompeu Fabra, Oxford, UK.
| | - Yonatan Sanz Perl
- International Centre for Flourishing, Universities of Oxford, Aarhus, and Pompeu Fabra, Oxford, UK; Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, Spain; Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
| | - Gustavo Deco
- International Centre for Flourishing, Universities of Oxford, Aarhus, and Pompeu Fabra, Oxford, UK; Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, Spain.
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2
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Moguilner S, Herzog R, Perl YS, Medel V, Cruzat J, Coronel C, Kringelbach M, Deco G, Ibáñez A, Tagliazucchi E. Biophysical models applied to dementia patients reveal links between geographical origin, gender, disease duration, and loss of neural inhibition. Alzheimers Res Ther 2024; 16:79. [PMID: 38605416 PMCID: PMC11008050 DOI: 10.1186/s13195-024-01449-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 04/02/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND The hypothesis of decreased neural inhibition in dementia has been sparsely studied in functional magnetic resonance imaging (fMRI) data across patients with different dementia subtypes, and the role of social and demographic heterogeneities on this hypothesis remains to be addressed. METHODS We inferred regional inhibition by fitting a biophysical whole-brain model (dynamic mean field model with realistic inter-areal connectivity) to fMRI data from 414 participants, including patients with Alzheimer's disease, behavioral variant frontotemporal dementia, and controls. We then investigated the effect of disease condition, and demographic and clinical variables on the local inhibitory feedback, a variable related to the maintenance of balanced neural excitation/inhibition. RESULTS Decreased local inhibitory feedback was inferred from the biophysical modeling results in dementia patients, specific to brain areas presenting neurodegeneration. This loss of local inhibition correlated positively with years with disease, and showed differences regarding the gender and geographical origin of the patients. The model correctly reproduced known disease-related changes in functional connectivity. CONCLUSIONS Results suggest a critical link between abnormal neural and circuit-level excitability levels, the loss of grey matter observed in dementia, and the reorganization of functional connectivity, while highlighting the sensitivity of the underlying biophysical mechanism to demographic and clinical heterogeneities in the patient population.
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Affiliation(s)
- Sebastian Moguilner
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), 1207 1651 4th St, 3rd Floor, San Francisco, CA, 94143, USA
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Vito Dumas 284, B1644BID, Buenos Aires, VIC, Argentina
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
- Trinity College Dublin, Lloyd Building Trinity College Dublin, Dublin, D02 PN40, Ireland
| | - Rubén Herzog
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile
| | - Yonatan Sanz Perl
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Vito Dumas 284, B1644BID, Buenos Aires, VIC, Argentina
- National Scientific and Technical Research Council (CONICET), Godoy Cruz 2290, CABA, 1425, Argentina
- Institute of Applied and Interdisciplinary Physics and Department of Physics, University of Buenos Aires, Pabellón 1, Ciudad Universitaria, CABA, 1428, Argentina
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Plaça de La Mercè, 10-12, Barcelona, 08002, Spain
| | - Vicente Medel
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile
- Centro Interdisciplinario de Neurociencia de Valparaíso (CINV), Universidad de Valparaíso, Harrington 287, Valparaíso, 2381850, Chile
| | - Josefina Cruzat
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile
| | - Carlos Coronel
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile
| | - Morten Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, St.Cross Rd, Oxford, OX1 3JA, UK
- Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Ln, Headington, Oxford, OX3 7JX, UK
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Blvd. 82, Aarhus, 8200, Denmark
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Plaça de La Mercè, 10-12, Barcelona, 08002, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, Leipzig, 04103, Germany
- Institució Catalana de Recerca I Estudis Avancats (ICREA), Passeig de Lluís Companys, 23, Barcelona, 08010, Spain
- Turner Institute for Brain and Mental Health, Monash University, 770 Blackburn Rd,, Clayton, VIC, 3168, Australia
| | - Agustín Ibáñez
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile.
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), 1207 1651 4th St, 3rd Floor, San Francisco, CA, 94143, USA.
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Vito Dumas 284, B1644BID, Buenos Aires, VIC, Argentina.
- Trinity College Institute of Neuroscience, Trinity College Dublin, 152 - 160 Pearse St, Dublin, D02 R590, Ireland.
- Trinity College Dublin, Lloyd Building Trinity College Dublin, Dublin, D02 PN40, Ireland.
| | - Enzo Tagliazucchi
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Santiago Región Metropolitana, Peñalolén, 7941169, Chile.
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Vito Dumas 284, B1644BID, Buenos Aires, VIC, Argentina.
- National Scientific and Technical Research Council (CONICET), Godoy Cruz 2290, CABA, 1425, Argentina.
- Institute of Applied and Interdisciplinary Physics and Department of Physics, University of Buenos Aires, Pabellón 1, Ciudad Universitaria, CABA, 1428, Argentina.
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Kringelbach ML, Vuust P, Deco G. Building a science of human pleasure, meaning making, and flourishing. Neuron 2024:S0896-6273(24)00200-9. [PMID: 38608705 DOI: 10.1016/j.neuron.2024.03.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 03/19/2024] [Accepted: 03/19/2024] [Indexed: 04/14/2024]
Abstract
"Supporting human flourishing" is a goal of governments and societies, yet the construct may appear hard to define. We discuss the emerging science of pleasure and flourishing, insights into the brain mechanisms of meaning making and thriving, and the potential for interdisciplinary studies to advance this promising scientific field.
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Affiliation(s)
- Morten L Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK; Department of Psychiatry, University of Oxford, Oxford, UK; Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; International Centre for Flourishing, Universities of Oxford and Aarhus and Pompeu Fabra University, Oxford, UK.
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; International Centre for Flourishing, Universities of Oxford and Aarhus and Pompeu Fabra University, Oxford, UK
| | - Gustavo Deco
- International Centre for Flourishing, Universities of Oxford and Aarhus and Pompeu Fabra University, Oxford, UK; Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, 08018 Barcelona, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, 08010 Barcelona, Spain
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Ibanez A, Kringelbach ML, Deco G. A synergetic turn in cognitive neuroscience of brain diseases. Trends Cogn Sci 2024; 28:319-338. [PMID: 38246816 DOI: 10.1016/j.tics.2023.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 12/15/2023] [Accepted: 12/27/2023] [Indexed: 01/23/2024]
Abstract
Despite significant improvements in our understanding of brain diseases, many barriers remain. Cognitive neuroscience faces four major challenges: complex structure-function associations; disease phenotype heterogeneity; the lack of transdiagnostic models; and oversimplified cognitive approaches restricted to the laboratory. Here, we propose a synergetics framework that can help to perform the necessary dimensionality reduction of complex interactions between the brain, body, and environment. The key solutions include low-dimensional spatiotemporal hierarchies for brain-structure associations, whole-brain modeling to handle phenotype diversity, model integration of shared transdiagnostic pathophysiological pathways, and naturalistic frameworks balancing experimental control and ecological validity. Creating whole-brain models with reduced manifolds combined with ecological measures can improve our understanding of brain disease and help identify novel interventions. Synergetics provides an integrated framework for future progress in clinical and cognitive neuroscience, pushing the boundaries of brain health and disease toward more mature, naturalistic approaches.
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Affiliation(s)
- Agustin Ibanez
- Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Santiago, Chile; Global Brain Health Institute (GBHI), University California San Francisco (UCSF), San Francisco, CA, USA; Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland; Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina; Department of Psychiatry, University of Oxford, Oxford, UK.
| | - Morten L Kringelbach
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain.
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Martínez-Molina N, Escrichs A, Sanz-Perl Y, Sihvonen AJ, Särkämö T, Kringelbach ML, Deco G. The evolution of whole-brain turbulent dynamics during recovery from traumatic brain injury. Netw Neurosci 2024; 8:158-177. [PMID: 38562284 PMCID: PMC10898780 DOI: 10.1162/netn_a_00346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 10/23/2023] [Indexed: 04/04/2024] Open
Abstract
It has been previously shown that traumatic brain injury (TBI) is associated with reductions in metastability in large-scale networks in resting-state fMRI (rsfMRI). However, little is known about how TBI affects the local level of synchronization and how this evolves during the recovery trajectory. Here, we applied a novel turbulent dynamics framework to investigate whole-brain dynamics using an rsfMRI dataset from a cohort of moderate to severe TBI patients and healthy controls (HCs). We first examined how several measures related to turbulent dynamics differ between HCs and TBI patients at 3, 6, and 12 months post-injury. We found a significant reduction in these empirical measures after TBI, with the largest change at 6 months post-injury. Next, we built a Hopf whole-brain model with coupled oscillators and conducted in silico perturbations to investigate the mechanistic principles underlying the reduced turbulent dynamics found in the empirical data. A simulated attack was used to account for the effect of focal lesions. This revealed a shift to lower coupling parameters in the TBI dataset and, critically, decreased susceptibility and information-encoding capability. These findings confirm the potential of the turbulent framework to characterize longitudinal changes in whole-brain dynamics and in the reactivity to external perturbations after TBI.
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Affiliation(s)
- Noelia Martínez-Molina
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
- Cognitive Brain Research Unit, Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Centre of Excellence in Music, Mind, Body and Brain, University of Helsinki, Helsinki, Finland
| | - Anira Escrichs
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
| | - Yonatan Sanz-Perl
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
| | - Aleksi J. Sihvonen
- Cognitive Brain Research Unit, Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Centre of Excellence in Music, Mind, Body and Brain, University of Helsinki, Helsinki, Finland
- School of Health and Rehabilitation Sciences, Queensland Aphasia Research Centre and UQ Centre for Clinical Research, University of Queensland, Brisbane, Australia
- Department of Neurology, University of Helsinki, and Helsinki University Hospital, Helsinki, Finland
| | - Teppo Särkämö
- Cognitive Brain Research Unit, Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Centre of Excellence in Music, Mind, Body and Brain, University of Helsinki, Helsinki, Finland
| | - Morten L. Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Gustavo Deco
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain
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Patow G, Escrichs A, Ritter P, Deco G. Whole-Brain Dynamics Disruptions in the Progression of Alzheimer's Disease: Understanding the Influence of Amyloid-Beta and Tau. bioRxiv 2024:2024.03.29.587333. [PMID: 38585882 PMCID: PMC10996678 DOI: 10.1101/2024.03.29.587333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
INTRODUCTION Alzheimer's disease (AD) affects brain structure and function along its evolution, but brain network dynamic changes remain largely unknown. METHODS To understand how AD shapes brain activity, we investigated the spatiotemporal dynamics and resting state functional networks using the intrinsic ignition framework, which characterizes how an area transmits neuronal activity to others, resulting in different degrees of integration. Healthy participants, MCI, and AD patients were scanned using resting state fMRI. Mixed effects models were used to assess the impact of ABeta and tau, at the regional and whole-brain levels. RESULTS Dynamic complexity is progressively reduced, with Healthy participants showing higher metastability (i.e., a more complex dynamical regime over time) than observed in the other stages, while AD subjects showed the lowest. DISCUSSION Our study provides further insight into how AD modulates brain network dynamics along its evolution, progressively disrupting the whole-brain and resting state network dynamics.
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Affiliation(s)
- Gustavo Patow
- ViRVIG, Universitat de Girona, Girona, Catalonia, Spain
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
| | - Anira Escrichs
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
| | - Petra Ritter
- Berlin Institute of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Gustavo Deco
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain
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Zhang S, Larsen B, Sydnor VJ, Zeng T, An L, Yan X, Kong R, Kong X, Gur RC, Gur RE, Moore TM, Wolf DH, Holmes AJ, Xie Y, Zhou JH, Fortier MV, Tan AP, Gluckman P, Chong YS, Meaney MJ, Deco G, Satterthwaite TD, Yeo BT. In-vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth. bioRxiv 2024:2023.06.22.546023. [PMID: 38586012 PMCID: PMC10996460 DOI: 10.1101/2023.06.22.546023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
A balanced excitation-inhibition ratio (E/I ratio) is critical for healthy brain function. Normative development of cortex-wide E/I ratio remains unknown. Here we non-invasively estimate a putative marker of whole-cortex E/I ratio by fitting a large-scale biophysically-plausible circuit model to resting-state functional MRI (fMRI) data. We first confirm that our model generates realistic brain dynamics in the Human Connectome Project. Next, we show that the estimated E/I ratio marker is sensitive to the GABA-agonist benzodiazepine alprazolam during fMRI. Alprazolam-induced E/I changes are spatially consistent with positron emission tomography measurement of benzodiazepine receptor density. We then investigate the relationship between the E/I ratio marker and neurodevelopment. We find that the E/I ratio marker declines heterogeneously across the cerebral cortex during youth, with the greatest reduction occurring in sensorimotor systems relative to association systems. Importantly, among children with the same chronological age, a lower E/I ratio marker (especially in association cortex) is linked to better cognitive performance. This result is replicated across North American (8.2 to 23.0 years old) and Asian (7.2 to 7.9 years old) cohorts, suggesting that a more mature E/I ratio indexes improved cognition during normative development. Overall, our findings open the door to studying how disrupted E/I trajectories may lead to cognitive dysfunction in psychopathology that emerges during youth.
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Affiliation(s)
- Shaoshi Zhang
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National Univeristy of Singapore, Signapore
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Valerie J. Sydnor
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tianchu Zeng
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National Univeristy of Singapore, Signapore
| | - Lijun An
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National Univeristy of Singapore, Signapore
| | - Xiaoxuan Yan
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National Univeristy of Singapore, Signapore
| | - Ru Kong
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National Univeristy of Singapore, Signapore
| | - Xiaolu Kong
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National Univeristy of Singapore, Signapore
- ByteDance, Singapore
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tyler M. Moore
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel H. Wolf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Avram J Holmes
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, United States
- Wu Tsai Institute, Yale University, New Haven, CT, United States
| | - Yapei Xie
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National Univeristy of Singapore, Signapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National Univeristy of Singapore, Signapore
| | - Marielle V Fortier
- Department of Diagnostic and Interventional Imaging, KK Women’s and Children’s Hospital, Singapore
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
| | - Ai Peng Tan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
- Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Peter Gluckman
- UK Centre for Human Evolution, Adaptation and Disease, Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michael J Meaney
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Gustavo Deco
- Center for Brain and Cognition, Department of Technology and Information, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats, Universitat Barcelona, Barcelona, Spain
| | - Theodore D. Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - B.T. Thomas Yeo
- Centre for Sleep and Cognition & Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore
- Department of Medicine, Human Potential Translational Research Programme & Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National Univeristy of Singapore, Signapore
- Martinos Center for Biomedical Imaging, Massachusetts General Hopstial, Charlestown, MA, USA
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Martínez-Molina N, Sanz-Perl Y, Escrichs A, Kringelbach ML, Deco G. Turbulent dynamics and whole-brain modeling: toward new clinical applications for traumatic brain injury. Front Neuroinform 2024; 18:1382372. [PMID: 38590709 PMCID: PMC10999628 DOI: 10.3389/fninf.2024.1382372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 03/01/2024] [Indexed: 04/10/2024] Open
Abstract
Traumatic Brain Injury (TBI) is a prevalent disorder mostly characterized by persistent impairments in cognitive function that poses a substantial burden on caregivers and the healthcare system worldwide. Crucially, severity classification is primarily based on clinical evaluations, which are non-specific and poorly predictive of long-term disability. In this Mini Review, we first provide a description of our model-free and model-based approaches within the turbulent dynamics framework as well as our vision on how they can potentially contribute to provide new neuroimaging biomarkers for TBI. In addition, we report the main findings of our recent study examining longitudinal changes in moderate-severe TBI (msTBI) patients during a one year spontaneous recovery by applying the turbulent dynamics framework (model-free approach) and the Hopf whole-brain computational model (model-based approach) combined with in silico perturbations. Given the neuroinflammatory response and heightened risk for neurodegeneration after TBI, we also offer future directions to explore the association with genomic information. Moreover, we discuss how whole-brain computational modeling may advance our understanding of the impact of structural disconnection on whole-brain dynamics after msTBI in light of our recent findings. Lastly, we suggest future avenues whereby whole-brain computational modeling may assist the identification of optimal brain targets for deep brain stimulation to promote TBI recovery.
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Affiliation(s)
- Noelia Martínez-Molina
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Yonatan Sanz-Perl
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Anira Escrichs
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Morten L. Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Department of Clinical Medicine, Center for Music in the Brain, Aarhus University and The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark
| | - Gustavo Deco
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats, Barcelona, Spain
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9
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Szakács H, Mutlu MC, Balestrieri G, Gombos F, Braun J, Kringelbach ML, Deco G, Kovács I. Navigating Pubertal Goldilocks: The Optimal Pace for Hierarchical Brain Organization. Adv Sci (Weinh) 2024:e2308364. [PMID: 38489748 DOI: 10.1002/advs.202308364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 02/22/2024] [Indexed: 03/17/2024]
Abstract
Adolescence is a timed process with an onset, tempo, and duration. Nevertheless, the temporal dimension, especially the pace of maturation, remains an insufficiently studied aspect of developmental progression. The primary objective is to estimate the precise influence of pubertal maturational tempo on the configuration of associative brain regions. To this end, the connection between maturational stages and the level of hierarchical organization of large-scale brain networks in 12-13-year-old females is analyzed. Skeletal maturity is used as a proxy for pubertal progress. The degree of maturity is defined by the difference between bone age and chronological age. To assess the level of hierarchical organization in the brain, the temporal dynamic of closed eye resting state high-density electroencephalography (EEG) in the alpha frequency range is analyzed. Different levels of hierarchical order are captured by the measured asymmetry in the directionality of information flow between different regions. The calculated EEG-based entropy production of participant groups is then compared with accelerated, average, and decelerated maturity. Results indicate that an average maturational trajectory optimally aligns with cerebral hierarchical order, and both accelerated and decelerated timelines result in diminished cortical organization. This suggests that a "Goldilocks rule" of brain development is favoring a particular maturational tempo.
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Affiliation(s)
- Hanna Szakács
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth Square, Budapest, 1088, Hungary
- Semmelweis University Doctoral School, Division of Mental Health Sciences, 26 Üllői road, Budapest, 1085, Hungary
| | - Murat Can Mutlu
- Institute of Biology, Otto-von-Guericke University, 44 Leipziger Straße, 39120, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Otto-von-Guericke University, 44 Leipziger Straße, 39120, Magdeburg, Germany
| | - Giulio Balestrieri
- Center for Brain and Cognition, Universitat Pompeu Fabra, 25-27 Ramon Trias Fargas, Barcelona, 08005, Spain
| | - Ferenc Gombos
- Laboratory for Psychological Research, Pázmány Péter Catholic University, 1 Mikszáth Square, Budapest, 1088, Hungary
- HUN-REN-ELTE-PPKE Adolescent Development Research Group, 1 Mikszáth Kálmán Square, Budapest, 1088, Hungary
| | - Jochen Braun
- Institute of Biology, Otto-von-Guericke University, 44 Leipziger Straße, 39120, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Otto-von-Guericke University, 44 Leipziger Straße, 39120, Magdeburg, Germany
| | - Morten L Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Wellington Square, Oxford, OX3 9BX, UK
- Department of Psychiatry, University of Oxford, Wellington Square, Oxford, OX3 7JX, UK
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Nordre Ringgade 1, Aarhus, 8000, Denmark
| | - Gustavo Deco
- Center for Brain and Cognition, Universitat Pompeu Fabra, 25-27 Ramon Trias Fargas, Barcelona, 08005, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, 122-140 Carrer de Tànger, Barcelona, 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), 23 Passeig de Lluís Companys, Barcelona, 08010, Spain
| | - Ilona Kovács
- HUN-REN-ELTE-PPKE Adolescent Development Research Group, 1 Mikszáth Kálmán Square, Budapest, 1088, Hungary
- Institute of Psychology, Faculty of Education and Psychology, Eötvös Loránd University, 25-27 Kazinczy Street, Budapest, 1075, Hungary
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10
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Vohryzek J, Cabral J, Lord LD, Fernandes HM, Roseman L, Nutt DJ, Carhart-Harris RL, Deco G, Kringelbach ML. Brain dynamics predictive of response to psilocybin for treatment-resistant depression. Brain Commun 2024; 6:fcae049. [PMID: 38515439 PMCID: PMC10957168 DOI: 10.1093/braincomms/fcae049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 10/16/2023] [Accepted: 02/14/2024] [Indexed: 03/23/2024] Open
Abstract
Psilocybin therapy for depression has started to show promise, yet the underlying causal mechanisms are not currently known. Here, we leveraged the differential outcome in responders and non-responders to psilocybin (10 and 25 mg, 7 days apart) therapy for depression-to gain new insights into regions and networks implicated in the restoration of healthy brain dynamics. We used large-scale brain modelling to fit the spatiotemporal brain dynamics at rest in both responders and non-responders before treatment. Dynamic sensitivity analysis of systematic perturbation of these models enabled us to identify specific brain regions implicated in a transition from a depressive brain state to a healthy one. Binarizing the sample into treatment responders (>50% reduction in depressive symptoms) versus non-responders enabled us to identify a subset of regions implicated in this change. Interestingly, these regions correlate with in vivo density maps of serotonin receptors 5-hydroxytryptamine 2a and 5-hydroxytryptamine 1a, which psilocin, the active metabolite of psilocybin, has an appreciable affinity for, and where it acts as a full-to-partial agonist. Serotonergic transmission has long been associated with depression, and our findings provide causal mechanistic evidence for the role of brain regions in the recovery from depression via psilocybin.
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Affiliation(s)
- Jakub Vohryzek
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Joana Cabral
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B’s—PT Government Associate Laboratory, Braga/Guimarães, University of Minho, Portugal
| | - Louis-David Lord
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Henrique M Fernandes
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Leor Roseman
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK
| | - David J Nutt
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK
| | - Robin L Carhart-Harris
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK
- Psychedelics Division, Neuroscape, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center for Music in the Brain, Aarhus University, Aarhus, Denmark
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
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11
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França LGS, Ciarrusta J, Gale-Grant O, Fenn-Moltu S, Fitzgibbon S, Chew A, Falconer S, Dimitrova R, Cordero-Grande L, Price AN, Hughes E, O'Muircheartaigh J, Duff E, Tuulari JJ, Deco G, Counsell SJ, Hajnal JV, Nosarti C, Arichi T, Edwards AD, McAlonan G, Batalle D. Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment. Nat Commun 2024; 15:16. [PMID: 38331941 PMCID: PMC10853532 DOI: 10.1038/s41467-023-44050-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 11/28/2023] [Indexed: 02/10/2024] Open
Abstract
Brain dynamic functional connectivity characterises transient connections between brain regions. Features of brain dynamics have been linked to emotion and cognition in adult individuals, and atypical patterns have been associated with neurodevelopmental conditions such as autism. Although reliable functional brain networks have been consistently identified in neonates, little is known about the early development of dynamic functional connectivity. In this study we characterise dynamic functional connectivity with functional magnetic resonance imaging (fMRI) in the first few weeks of postnatal life in term-born (n = 324) and preterm-born (n = 66) individuals. We show that a dynamic landscape of brain connectivity is already established by the time of birth in the human brain, characterised by six transient states of neonatal functional connectivity with changing dynamics through the neonatal period. The pattern of dynamic connectivity is atypical in preterm-born infants, and associated with atypical social, sensory, and repetitive behaviours measured by the Quantitative Checklist for Autism in Toddlers (Q-CHAT) scores at 18 months of age.
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Affiliation(s)
- Lucas G S França
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- Department of Computer and Information Sciences, Faculty of Engineering and Environment, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK
| | - Judit Ciarrusta
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Oliver Gale-Grant
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Sunniva Fenn-Moltu
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Sean Fitzgibbon
- Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Ralica Dimitrova
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid, 28040, Madrid, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Jonathan O'Muircheartaigh
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
| | - Eugene Duff
- Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK
- Department of Brain Sciences, Imperial College London, London, W12 0BZ, UK
- UK Dementia Research Institute at Imperial College London, London, W12 0BZ, UK
| | - Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, 20500, Turku, Finland
- Turku Collegium for Science and Medicine and Technology, University of Turku, 20500, Turku, Finland
- Department of Psychiatry, University of Turku and Turku University Hospital, 20500, Turku, Finland
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Pompeu Fabra University, 08002, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies, 08010, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, VIC, 3010, Australia
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
- Department of Paediatric Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London, SE1 7EH, UK
- Department of Bioengineering, Imperial College London, London, SW7 2AZ, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Dafnis Batalle
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK.
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12
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Ponce-Alvarez A, Deco G. The Hopf whole-brain model and its linear approximation. Sci Rep 2024; 14:2615. [PMID: 38297071 PMCID: PMC10831083 DOI: 10.1038/s41598-024-53105-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 01/27/2024] [Indexed: 02/02/2024] Open
Abstract
Whole-brain models have proven to be useful to understand the emergence of collective activity among neural populations or brain regions. These models combine connectivity matrices, or connectomes, with local node dynamics, noise, and, eventually, transmission delays. Multiple choices for the local dynamics have been proposed. Among them, nonlinear oscillators corresponding to a supercritical Hopf bifurcation have been used to link brain connectivity and collective phase and amplitude dynamics in different brain states. Here, we studied the linear fluctuations of this model to estimate its stationary statistics, i.e., the instantaneous and lagged covariances and the power spectral densities. This linear approximation-that holds in the case of heterogeneous parameters and time-delays-allows analytical estimation of the statistics and it can be used for fast parameter explorations to study changes in brain state, changes in brain activity due to alterations in structural connectivity, and modulations of parameter due to non-equilibrium dynamics.
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Affiliation(s)
- Adrián Ponce-Alvarez
- Departament de Matemàtiques, Universitat Politècnica de Catalunya, 08028, Barcelona, Spain.
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08005, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), 08010, Barcelona, Spain
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13
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Rolls ET, Deco G, Huang CC, Feng J. The connectivity of the human frontal pole cortex, and a theory of its involvement in exploit versus explore. Cereb Cortex 2024; 34:bhad416. [PMID: 37991264 DOI: 10.1093/cercor/bhad416] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/16/2023] [Accepted: 10/17/2023] [Indexed: 11/23/2023] Open
Abstract
The frontal pole is implicated in humans in whether to exploit resources versus explore alternatives. Effective connectivity, functional connectivity, and tractography were measured between six human frontal pole regions and for comparison 13 dorsolateral and dorsal prefrontal cortex regions, and the 360 cortical regions in the Human Connectome Project Multi-modal-parcellation atlas in 171 HCP participants. The frontal pole regions have effective connectivity with Dorsolateral Prefrontal Cortex regions, the Dorsal Prefrontal Cortex, both implicated in working memory; and with the orbitofrontal and anterior cingulate cortex reward/non-reward system. There is also connectivity with temporal lobe, inferior parietal, and posterior cingulate regions. Given this new connectivity evidence, and evidence from activations and damage, it is proposed that the frontal pole cortex contains autoassociation attractor networks that are normally stable in a short-term memory state, and maintain stability in the other prefrontal networks during stable exploitation of goals and strategies. However, if an input from the orbitofrontal or anterior cingulate cortex that expected reward, non-reward, or punishment is received, this destabilizes the frontal pole and thereby other prefrontal networks to enable exploration of competing alternative goals and strategies. The frontal pole connectivity with reward systems may be key in exploit versus explore.
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Affiliation(s)
- Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, United Kingdom
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain
- Brain and Cognition, Pompeu Fabra University, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Passeig Lluís Companys 23, Barcelona 08010, Spain
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200602, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 200602, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
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14
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Idesis S, Geli S, Faskowitz J, Vohryzek J, Sanz Perl Y, Pieper F, Galindo-Leon E, Engel AK, Deco G. Functional hierarchies in brain dynamics characterized by signal reversibility in ferret cortex. PLoS Comput Biol 2024; 20:e1011818. [PMID: 38241383 PMCID: PMC10836715 DOI: 10.1371/journal.pcbi.1011818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 02/02/2024] [Accepted: 01/09/2024] [Indexed: 01/21/2024] Open
Abstract
Brain signal irreversibility has been shown to be a promising approach to study neural dynamics. Nevertheless, the relation with cortical hierarchy and the influence of different electrophysiological features is not completely understood. In this study, we recorded local field potentials (LFPs) during spontaneous behavior, including awake and sleep periods, using custom micro-electrocorticographic (μECoG) arrays implanted in ferrets. In contrast to humans, ferrets remain less time in each state across the sleep-wake cycle. We deployed a diverse set of metrics in order to measure the levels of complexity of the different behavioral states. In particular, brain irreversibility, which is a signature of non-equilibrium dynamics, captured by the arrow of time of the signal, revealed the hierarchical organization of the ferret's cortex. We found different signatures of irreversibility and functional hierarchy of large-scale dynamics in three different brain states (active awake, quiet awake, and deep sleep), showing a lower level of irreversibility in the deep sleep stage, compared to the other. Irreversibility also allowed us to disentangle the influence of different cortical areas and frequency bands in this process, showing a predominance of the parietal cortex and the theta band. Furthermore, when inspecting the embedded dynamic through a Hidden Markov Model, the deep sleep stage was revealed to have a lower switching rate and lower entropy production. These results suggest functional hierarchies in organization that can be revealed through thermodynamic features and information theory metrics.
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Affiliation(s)
- Sebastian Idesis
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Barcelona, Catalonia, Spain
| | - Sebastián Geli
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Barcelona, Catalonia, Spain
| | - Joshua Faskowitz
- Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, Indiana, United States of America
| | - Jakub Vohryzek
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Barcelona, Catalonia, Spain
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
| | - Yonatan Sanz Perl
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Barcelona, Catalonia, Spain
- National Scientific and Technical Research Council, Buenos Aires, Argentina
- Institut du Cerveau et de la Moelle épinière, ICM, Paris, France
| | - Florian Pieper
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Edgar Galindo-Leon
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Andreas K. Engel
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gustavo Deco
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Barcelona, Catalonia, Spain
- Institució Catalana de Recerca I Estudis Avançats (ICREA), Barcelona, Catalonia, Spain
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15
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Capouskova K, Zamora‐López G, Kringelbach ML, Deco G. Integration and segregation manifolds in the brain ensure cognitive flexibility during tasks and rest. Hum Brain Mapp 2023; 44:6349-6363. [PMID: 37846551 PMCID: PMC10681658 DOI: 10.1002/hbm.26511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/14/2023] [Accepted: 09/25/2023] [Indexed: 10/18/2023] Open
Abstract
Adapting to a constantly changing environment requires the human brain to flexibly switch among many demanding cognitive tasks, processing both specialized and integrated information associated with the activity in functional networks over time. In this study, we investigated the nature of the temporal alternation between segregated and integrated states in the brain during rest and six cognitive tasks using functional MRI. We employed a deep autoencoder to explore the 2D latent space associated with the segregated and integrated states. Our results show that the integrated state occupies less space in the latent space manifold compared to the segregated states. Moreover, the integrated state is characterized by lower entropy of occupancy than the segregated state, suggesting that integration plays a consolidating role, while segregation may serve as cognitive expertness. Comparing rest and the tasks, we found that rest exhibits higher entropy of occupancy, indicating a more random wandering of the mind compared to the expected focus during task performance. Our study demonstrates that both transient, short-lived integrated and segregated states are present during rest and task performance, flexibly switching between them, with integration serving as information compression and segregation related to information specialization.
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Affiliation(s)
- Katerina Capouskova
- Center for Brain and Cognition, Computational Neuroscience Group, DTICUniversitat Pompeu FabraBarcelonaSpain
| | - Gorka Zamora‐López
- Center for Brain and Cognition, Computational Neuroscience Group, DTICUniversitat Pompeu FabraBarcelonaSpain
| | - Morten L. Kringelbach
- Department of PsychiatryUniversity of OxfordOxfordUnited Kingdom
- Center for Music in the Brain, Department of Clinical MedicineAarhus UniversityAarhusDenmark
- Centre for Eudaimonia and Human Flourishing, Linacre CollegeUniversity of OxfordOxfordUnited Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, DTICUniversitat Pompeu FabraBarcelonaSpain
- Institució Catalana de Recerca i Estudis Avançats (ICREA)BarcelonaSpain
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16
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Grabenhorst F, Ponce-Alvarez A, Battaglia-Mayer A, Deco G, Schultz W. A view-based decision mechanism for rewards in the primate amygdala. Neuron 2023; 111:3871-3884.e14. [PMID: 37725980 PMCID: PMC10914681 DOI: 10.1016/j.neuron.2023.08.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 07/12/2023] [Accepted: 08/23/2023] [Indexed: 09/21/2023]
Abstract
Primates make decisions visually by shifting their view from one object to the next, comparing values between objects, and choosing the best reward, even before acting. Here, we show that when monkeys make value-guided choices, amygdala neurons encode their decisions in an abstract, purely internal representation defined by the monkey's current view but not by specific object or reward properties. Across amygdala subdivisions, recorded activity patterns evolved gradually from an object-specific value code to a transient, object-independent code in which currently viewed and last-viewed objects competed to reflect the emerging view-based choice. Using neural-network modeling, we identified a sequence of computations by which amygdala neurons implemented view-based decision making and eventually recovered the chosen object's identity when the monkeys acted on their choice. These findings reveal a neural mechanism in the amygdala that derives object choices from abstract, view-based computations, suggesting an efficient solution for decision problems with many objects.
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Affiliation(s)
- Fabian Grabenhorst
- Department of Experimental Psychology, University of Oxford, Mansfield Road, Oxford OX1 3TA, UK; Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK.
| | - Adrián Ponce-Alvarez
- Center for Brain and Cognition, Department of Technology and Information, Universitat Pompeu Fabra, Carrer Ramón Trias Fargas, 25-27, 08005 Barcelona, Spain; Departament de Matemàtiques, EPSEB, Universitat Politècnica de Catalunya, Barcelona, 08028 Barcelona, Spain
| | | | - Gustavo Deco
- Center for Brain and Cognition, Department of Technology and Information, Universitat Pompeu Fabra, Carrer Ramón Trias Fargas, 25-27, 08005 Barcelona, Spain; Institució Catalana de la Recerca i Estudis Avançats, Universitat Barcelona, Passeig Lluís Companys 23, 08010 Barcelona, Spain
| | - Wolfram Schultz
- Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK
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17
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Patow G, Stefanovski L, Ritter P, Deco G, Kobeleva X. Whole-brain modeling of the differential influences of amyloid-beta and tau in Alzheimer's disease. Alzheimers Res Ther 2023; 15:210. [PMID: 38053164 PMCID: PMC10696890 DOI: 10.1186/s13195-023-01349-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 11/07/2023] [Indexed: 12/07/2023]
Abstract
BACKGROUND Alzheimer's disease is a neurodegenerative condition associated with the accumulation of two misfolded proteins, amyloid-beta (A[Formula: see text]) and tau. We study their effect on neuronal activity, with the aim of assessing their individual and combined impact. METHODS We use a whole-brain dynamic model to find the optimal parameters that best describe the effects of A[Formula: see text] and tau on the excitation-inhibition balance of the local nodes. RESULTS We found a clear dominance of A[Formula: see text] over tau in the early disease stages (MCI), while tau dominates over A[Formula: see text] in the latest stages (AD). We identify crucial roles for A[Formula: see text] and tau in complex neuronal dynamics and demonstrate the viability of using regional distributions to define models of large-scale brain function in AD. CONCLUSIONS Our study provides further insight into the dynamics and complex interplay between these two proteins, opening the path for further investigations on biomarkers and candidate therapeutic targets in-silico.
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Affiliation(s)
- Gustavo Patow
- ViRVIG, Universitat de Girona, Girona, Spain.
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, Center for Brain and Cognition, Computational Neuroscience Group, Barcelona, Spain.
| | - Leon Stefanovski
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology with Experimental Neurology, Brain Simulation Section, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, 10117, Germany
| | - Petra Ritter
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology with Experimental Neurology, Brain Simulation Section, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, 10117, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
- Einstein Center for Neuroscience Berlin, Berlin, Germany
- Einstein Center Digital Future Berlin, Berlin, Germany
| | - Gustavo Deco
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, Center for Brain and Cognition, Computational Neuroscience Group, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Xenia Kobeleva
- Computational Neurology Research Group, Ruhr University Bochum, Bochum, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurology, University Hospital Bonn, Bonn, Germany
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18
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Alonso S, Tyborowska A, Ikani N, Mocking RJT, Figueroa CA, Schene AH, Deco G, Kringelbach ML, Cabral J, Ruhé HG. Depression recurrence is accompanied by longer periods in default mode and more frequent attentional and reward processing dynamic brain-states during resting-state activity. Hum Brain Mapp 2023; 44:5770-5783. [PMID: 37672593 PMCID: PMC10619399 DOI: 10.1002/hbm.26475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 07/15/2023] [Accepted: 08/16/2023] [Indexed: 09/08/2023] Open
Abstract
Recurrence in major depressive disorder (MDD) is common, but neurobiological models capturing vulnerability for recurrences are scarce. Disturbances in multiple resting-state networks have been linked to MDD, but most approaches focus on stable (vs. dynamic) network characteristics. We investigated how the brain's dynamical repertoire changes after patients transition from remission to recurrence of a new depressive episode. Sixty two drug-free, MDD-patients with ≥2 episodes underwent a baseline resting-state fMRI scan when in remission. Over 30-months follow-up, 11 patients with a recurrence and 17 matched-remitted MDD-patients without a recurrence underwent a second fMRI scan. Recurrent patterns of functional connectivity were characterized by applying Leading Eigenvector Dynamics Analysis (LEiDA). Differences between baseline and follow-up were identified for the 11 non-remitted patients, while data from the 17 matched-remitted patients was used as a validation dataset. After the transition into a depressive state, basal ganglia-anterior cingulate cortex (ACC) and visuo-attentional networks were detected significantly more often, whereas default mode network activity was found to have a longer duration. Additionally, the fMRI signal in the basal ganglia-ACC areas underlying the reward network, were significantly less synchronized with the rest of the brain after recurrence (compared to a state of remission). No significant changes were observed in the matched-remitted patients who were scanned twice while in remission. These findings characterize changes that may be associated with the transition from remission to recurrence and provide initial evidence of altered dynamical exploration of the brain's repertoire of functional networks when a recurrent depressive episode occurs.
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Affiliation(s)
- Sonsoles Alonso
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University Medical Center GroningenUniversity of GroningenGroningenthe Netherlands
- Department of Clinical Medicine, Center for Functionally Integrative NeuroscienceAarhus UniversityAarhusDenmark
| | - Anna Tyborowska
- Department of PsychiatryRadboud University Medical CentreNijmegenthe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenthe Netherlands
| | - Nessa Ikani
- Department of PsychiatryRadboud University Medical CentreNijmegenthe Netherlands
- Depression Expertise CenterProPersona Mental Health CareNijmegenthe Netherlands
- Overwaal Centre of Expertise for Anxiety Disorders, OCD and PTSDPro Persona Mental Health CareNijmegenthe Netherlands
| | - Roel J. T. Mocking
- Department of PsychiatryAmsterdam UMC, Location AMCAmsterdamthe Netherlands
| | - Caroline A. Figueroa
- Department of PsychiatryUniversity Medical Centre UtrechtUtrechtthe Netherlands
- School of Social WelfareUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Aart H. Schene
- Department of PsychiatryRadboud University Medical CentreNijmegenthe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenthe Netherlands
| | - Gustavo Deco
- Department of Information and Communication Technologies, Center for Brain and Cognition, Computational Neuroscience GroupUniversitat Pompeu FabraBarcelonaSpain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA)BarcelonaSpain
| | - Morten L. Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre CollegeUniversity of OxfordOxfordUK
- Center for Music in the BrainAarhus UniversityAarhusDenmark
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Joana Cabral
- Centre for Eudaimonia and Human Flourishing, Linacre CollegeUniversity of OxfordOxfordUK
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
| | - Henricus G. Ruhé
- Department of PsychiatryRadboud University Medical CentreNijmegenthe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenthe Netherlands
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19
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Deco G, Lynn CW, Sanz Perl Y, Kringelbach ML. Violations of the fluctuation-dissipation theorem reveal distinct nonequilibrium dynamics of brain states. Phys Rev E 2023; 108:064410. [PMID: 38243472 DOI: 10.1103/physreve.108.064410] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 10/16/2023] [Indexed: 01/21/2024]
Abstract
The brain is a nonequilibrium system whose dynamics change in different brain states, such as wakefulness and deep sleep. Thermodynamics provides the tools for revealing these nonequilibrium dynamics. We used violations of the fluctuation-dissipation theorem to describe the hierarchy of nonequilibrium dynamics associated with different brain states. Together with a whole-brain model fitted to empirical human neuroimaging data, and deriving the appropriate analytical expressions, we were able to capture the deviation from equilibrium in different brain states that arises from asymmetric interactions and hierarchical organization.
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Affiliation(s)
- Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain
| | - Christopher W Lynn
- Initiative for the Theoretical Sciences, Graduate Center, City University of New York, New York, New York 10016, USA and Joseph Henry Laboratories of Physics, Princeton University, Princeton, New Jersey 08544, USA
| | - Yonatan Sanz Perl
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain
- Department of Physics, University of Buenos Aires, Buenos Aires 1428, Argentina and Paris Brain Institute (ICM), Paris 75013, France
| | - Morten L Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford OX3 9BX, United Kingdom; Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom; and Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus 8000, Denmark
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20
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Blair DS, Soriano-Mas C, Cabral J, Moreira P, Morgado P, Deco G. Corrigendum: Complexity changes in functional state dynamics suggest focal connectivity reductions. Front Hum Neurosci 2023; 17:1275387. [PMID: 37886692 PMCID: PMC10599009 DOI: 10.3389/fnhum.2023.1275387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 09/29/2023] [Indexed: 10/28/2023] Open
Abstract
[This corrects the article DOI: 10.3389/fnhum.2022.958706.].
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Affiliation(s)
| | - Carles Soriano-Mas
- Psychiatry and Mental Health Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge, Barcelona, Spain
- Network Center for Biomedical Research on Mental Health, Carlos III Health Institute, Madrid, Spain
- Department of Social Psychology and Quantitative Psychology, Universitat de Barcelona, Barcelona, Spain
| | - Joana Cabral
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
| | - Pedro Moreira
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, Braga, Portugal
- Psychological Neuroscience Lab, CIPsi, School of Psychology, University of Minho, Braga, Portugal
| | - Pedro Morgado
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, Braga, Portugal
- Clinical Academic Center—Braga, Braga, Portugal
| | - Gustavo Deco
- Facultad de Comunicación, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Clayton, VIC, Australia
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21
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Rolls ET, Deco G, Zhang Y, Feng J. Hierarchical organization of the human ventral visual streams revealed with magnetoencephalography. Cereb Cortex 2023; 33:10686-10701. [PMID: 37689834 DOI: 10.1093/cercor/bhad318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 08/17/2023] [Accepted: 08/17/2023] [Indexed: 09/11/2023] Open
Abstract
The hierarchical organization between 25 ventral stream visual cortical regions and 180 cortical regions was measured with magnetoencephalography using the Human Connectome Project Multimodal Parcellation atlas in 83 Human Connectome Project participants performing a visual memory task. The aim was to reveal the hierarchical organization using a whole-brain model based on generative effective connectivity with this fast neuroimaging method. V1-V4 formed a first group of interconnected regions. Especially V4 had connectivity to a ventrolateral visual stream: V8, the fusiform face cortex, and posterior inferior temporal cortex PIT. These regions in turn had effectivity connectivity to inferior temporal cortex visual regions TE2p and TE1p. TE2p and TE1p then have connectivity to anterior temporal lobe regions TE1a, TE1m, TE2a, and TGv, which are multimodal. In a ventromedial visual stream, V1-V4 connect to ventromedial regions VMV1-3 and VVC. VMV1-3 and VVC connect to the medial parahippocampal gyrus PHA1-3, which, with the VMV regions, include the parahippocampal scene area. The medial parahippocampal PHA1-3 regions have connectivity to the hippocampal system regions the perirhinal cortex, entorhinal cortex, and hippocampus. These effective connectivities of two ventral visual cortical streams measured with magnetoencephalography provide support to the hierarchical organization of brain systems measured with fMRI, and new evidence on directionality.
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Affiliation(s)
- Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, United Kingdom
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain
- Brain and Cognition, Pompeu Fabra University, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Passeig Lluís Companys 23, Barcelona 08010, Spain
| | - Yi Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
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22
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Deco G, Sanz Perl Y, de la Fuente L, Sitt JD, Yeo BTT, Tagliazucchi E, Kringelbach ML. The arrow of time of brain signals in cognition: Potential intriguing role of parts of the default mode network. Netw Neurosci 2023; 7:966-998. [PMID: 37781151 PMCID: PMC10473271 DOI: 10.1162/netn_a_00300] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 12/14/2022] [Indexed: 10/03/2023] Open
Abstract
A promising idea in human cognitive neuroscience is that the default mode network (DMN) is responsible for coordinating the recruitment and scheduling of networks for computing and solving task-specific cognitive problems. This is supported by evidence showing that the physical and functional distance of DMN regions is maximally removed from sensorimotor regions containing environment-driven neural activity directly linked to perception and action, which would allow the DMN to orchestrate complex cognition from the top of the hierarchy. However, discovering the functional hierarchy of brain dynamics requires finding the best way to measure interactions between brain regions. In contrast to previous methods measuring the hierarchical flow of information using, for example, transfer entropy, here we used a thermodynamics-inspired, deep learning based Temporal Evolution NETwork (TENET) framework to assess the asymmetry in the flow of events, 'arrow of time', in human brain signals. This provides an alternative way of quantifying hierarchy, given that the arrow of time measures the directionality of information flow that leads to a breaking of the balance of the underlying hierarchy. In turn, the arrow of time is a measure of nonreversibility and thus nonequilibrium in brain dynamics. When applied to large-scale Human Connectome Project (HCP) neuroimaging data from close to a thousand participants, the TENET framework suggests that the DMN plays a significant role in orchestrating the hierarchy, that is, levels of nonreversibility, which changes between the resting state and when performing seven different cognitive tasks. Furthermore, this quantification of the hierarchy of the resting state is significantly different in health compared to neuropsychiatric disorders. Overall, the present thermodynamics-based machine-learning framework provides vital new insights into the fundamental tenets of brain dynamics for orchestrating the interactions between cognition and brain in complex environments.
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Affiliation(s)
- Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, Clayton VIC, Australia
| | - Yonatan Sanz Perl
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
| | - Laura de la Fuente
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
| | - Jacobo D. Sitt
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | - B. T. Thomas Yeo
- Centre for Sleep & Cognition, Centre for Translational MR Research, Department of Electrical and Computer Engineering, N.1. Institute for Health and Institute for Digital Medicine, National University of Singapore, Singapore
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibanez, Santiago, Chile
| | - Morten L. Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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23
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Idesis S, Allegra M, Vohryzek J, Sanz Perl Y, Faskowitz J, Sporns O, Corbetta M, Deco G. A low dimensional embedding of brain dynamics enhances diagnostic accuracy and behavioral prediction in stroke. Sci Rep 2023; 13:15698. [PMID: 37735201 PMCID: PMC10514061 DOI: 10.1038/s41598-023-42533-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 09/11/2023] [Indexed: 09/23/2023] Open
Abstract
Large-scale brain networks reveal structural connections as well as functional synchronization between distinct regions of the brain. The latter, referred to as functional connectivity (FC), can be derived from neuroimaging techniques such as functional magnetic resonance imaging (fMRI). FC studies have shown that brain networks are severely disrupted by stroke. However, since FC data are usually large and high-dimensional, extracting clinically useful information from this vast amount of data is still a great challenge, and our understanding of the functional consequences of stroke remains limited. Here, we propose a dimensionality reduction approach to simplify the analysis of this complex neural data. By using autoencoders, we find a low-dimensional representation encoding the fMRI data which preserves the typical FC anomalies known to be present in stroke patients. By employing the latent representations emerging from the autoencoders, we enhanced patients' diagnostics and severity classification. Furthermore, we showed how low-dimensional representation increased the accuracy of recovery prediction.
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Affiliation(s)
- Sebastian Idesis
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain.
| | - Michele Allegra
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padua, Italy
- Department of Physics and Astronomy "G. Galilei", University of Padova, via Marzolo 8, 35131, Padua, Italy
| | - Jakub Vohryzek
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
| | - Yonatan Sanz Perl
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain
- Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council, Buenos Aires, Argentina
- Institut du Cerveau et de la Moelle Épinière, ICM, Paris, France
| | - Joshua Faskowitz
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
| | - Maurizio Corbetta
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padua, Italy
- Department of Neuroscience, University of Padova, via Giustiniani 5, 35128, Padua, Italy
- Veneto Institute of Molecular Medicine (VIMM), via Orus 2/B, 35129, Padua, Italy
| | - Gustavo Deco
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain
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24
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Castaldo F, Páscoa Dos Santos F, Timms RC, Cabral J, Vohryzek J, Deco G, Woolrich M, Friston K, Verschure P, Litvak V. Multi-modal and multi-model interrogation of large-scale functional brain networks. Neuroimage 2023; 277:120236. [PMID: 37355200 PMCID: PMC10958139 DOI: 10.1016/j.neuroimage.2023.120236] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 06/14/2023] [Accepted: 06/16/2023] [Indexed: 06/26/2023] Open
Abstract
Existing whole-brain models are generally tailored to the modelling of a particular data modality (e.g., fMRI or MEG/EEG). We propose that despite the differing aspects of neural activity each modality captures, they originate from shared network dynamics. Building on the universal principles of self-organising delay-coupled nonlinear systems, we aim to link distinct features of brain activity - captured across modalities - to the dynamics unfolding on a macroscopic structural connectome. To jointly predict connectivity, spatiotemporal and transient features of distinct signal modalities, we consider two large-scale models - the Stuart Landau and Wilson and Cowan models - which generate short-lived 40 Hz oscillations with varying levels of realism. To this end, we measure features of functional connectivity and metastable oscillatory modes (MOMs) in fMRI and MEG signals - and compare them against simulated data. We show that both models can represent MEG functional connectivity (FC), functional connectivity dynamics (FCD) and generate MOMs to a comparable degree. This is achieved by adjusting the global coupling and mean conduction time delay and, in the WC model, through the inclusion of balance between excitation and inhibition. For both models, the omission of delays dramatically decreased the performance. For fMRI, the SL model performed worse for FCD and MOMs, highlighting the importance of balanced dynamics for the emergence of spatiotemporal and transient patterns of ultra-slow dynamics. Notably, optimal working points varied across modalities and no model was able to achieve a correlation with empirical FC higher than 0.4 across modalities for the same set of parameters. Nonetheless, both displayed the emergence of FC patterns that extended beyond the constraints of the anatomical structure. Finally, we show that both models can generate MOMs with empirical-like properties such as size (number of brain regions engaging in a mode) and duration (continuous time interval during which a mode appears). Our results demonstrate the emergence of static and dynamic properties of neural activity at different timescales from networks of delay-coupled oscillators at 40 Hz. Given the higher dependence of simulated FC on the underlying structural connectivity, we suggest that mesoscale heterogeneities in neural circuitry may be critical for the emergence of parallel cross-modal functional networks and should be accounted for in future modelling endeavours.
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Affiliation(s)
- Francesca Castaldo
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom.
| | - Francisco Páscoa Dos Santos
- Eodyne Systems SL, Barcelona, Spain; Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Ryan C Timms
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; ICVS/3B's - Portuguese Government Associate Laboratory, Braga/Guimarães, Portugal; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, United United Kingdom
| | - Jakub Vohryzek
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, United United Kingdom; Centre for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Gustavo Deco
- Centre for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Mark Woolrich
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Paul Verschure
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
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25
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Tewarie PKB, Hindriks R, Lai YM, Sotiropoulos SN, Kringelbach M, Deco G. Non-reversibility outperforms functional connectivity in characterisation of brain states in MEG data. Neuroimage 2023; 276:120186. [PMID: 37268096 DOI: 10.1016/j.neuroimage.2023.120186] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 04/27/2023] [Accepted: 05/22/2023] [Indexed: 06/04/2023] Open
Abstract
Characterising brain states during tasks is common practice for many neuroscientific experiments using electrophysiological modalities such as electroencephalography (EEG) and magnetoencephalography (MEG). Brain states are often described in terms of oscillatory power and correlated brain activity, i.e. functional connectivity. It is, however, not unusual to observe weak task induced functional connectivity alterations in the presence of strong task induced power modulations using classical time-frequency representation of the data. Here, we propose that non-reversibility, or the temporal asymmetry in functional interactions, may be more sensitive to characterise task induced brain states than functional connectivity. As a second step, we explore causal mechanisms of non-reversibility in MEG data using whole brain computational models. We include working memory, motor, language tasks and resting-state data from participants of the Human Connectome Project (HCP). Non-reversibility is derived from the lagged amplitude envelope correlation (LAEC), and is based on asymmetry of the forward and reversed cross-correlations of the amplitude envelopes. Using random forests, we find that non-reversibility outperforms functional connectivity in the identification of task induced brain states. Non-reversibility shows especially better sensitivity to capture bottom-up gamma induced brain states across all tasks, but also alpha band associated brain states. Using whole brain computational models we find that asymmetry in the effective connectivity and axonal conduction delays play a major role in shaping non-reversibility across the brain. Our work paves the way for better sensitivity in characterising brain states during both bottom-up as well as top-down modulation in future neuroscientific experiments.
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Affiliation(s)
- Prejaas K B Tewarie
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Spain; Clinical Neurophysiology Group, University of Twente, Enschede, The Netherlands; Department of Neurology, Amsterdam UMC, Amsterdam, the Netherlands; Sir Peter Mansfield Imaging Centre, School of Physics, University of Nottingham, Nottingham, United Kingdom.
| | - Rikkert Hindriks
- Department of Mathematics, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Yi Ming Lai
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, United Kingdom
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, United Kingdom; NIHR Biomedical Research Centre, University of Nottingham, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Morten Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK; Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Psychiatry, University of Oxford, Oxford, UK
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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26
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Chakraborty P, Saha S, Deco G, Banerjee A, Roy D. Structural-and-dynamical similarity predicts compensatory brain areas driving the post-lesion functional recovery mechanism. Cereb Cortex Commun 2023; 4:tgad012. [PMID: 37559936 PMCID: PMC10409568 DOI: 10.1093/texcom/tgad012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 06/30/2023] [Accepted: 07/05/2023] [Indexed: 08/11/2023] Open
Abstract
The focal lesion alters the excitation-inhibition (E-I) balance and healthy functional connectivity patterns, which may recover over time. One possible mechanism for the brain to counter the insult is global reshaping functional connectivity alterations. However, the operational principles by which this can be achieved remain unknown. We propose a novel equivalence principle based on structural and dynamic similarity analysis to predict whether specific compensatory areas initiate lost E-I regulation after lesion. We hypothesize that similar structural areas (SSAs) and dynamically similar areas (DSAs) corresponding to a lesioned site are the crucial dynamical units to restore lost homeostatic balance within the surviving cortical brain regions. SSAs and DSAs are independent measures, one based on structural similarity properties measured by Jaccard Index and the other based on post-lesion recovery time. We unravel the relationship between SSA and DSA by simulating a whole brain mean field model deployed on top of a virtually lesioned structural connectome from human neuroimaging data to characterize global brain dynamics and functional connectivity at the level of individual subjects. Our results suggest that wiring proximity and similarity are the 2 major guiding principles of compensation-related utilization of hemisphere in the post-lesion functional connectivity re-organization process.
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Affiliation(s)
- Priyanka Chakraborty
- Cognitive Brain Dynamics Lab, National Brain Research Centre, NH-8, Manesar, Haryana 122051, India
| | - Suman Saha
- Cognitive Brain Dynamics Lab, National Brain Research Centre, NH-8, Manesar, Haryana 122051, India
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
| | - Arpan Banerjee
- Cognitive Brain Dynamics Lab, National Brain Research Centre, NH-8, Manesar, Haryana 122051, India
| | - Dipanjan Roy
- Cognitive Brain Dynamics Lab, National Brain Research Centre, NH-8, Manesar, Haryana 122051, India
- School of AIDE, Center for Brain Research and Applications, IIT Jodhpur, NH-62, Surpura Bypass Rd, Karwar, Rajasthan 342030, India
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27
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Luppi AI, Cabral J, Cofre R, Mediano PAM, Rosas FE, Qureshi AY, Kuceyeski A, Tagliazucchi E, Raimondo F, Deco G, Shine JM, Kringelbach ML, Orio P, Ching S, Sanz Perl Y, Diringer MN, Stevens RD, Sitt JD. Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness. Neuroimage 2023; 275:120162. [PMID: 37196986 PMCID: PMC10262065 DOI: 10.1016/j.neuroimage.2023.120162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 04/16/2023] [Accepted: 05/09/2023] [Indexed: 05/19/2023] Open
Abstract
Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges.
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Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
| | - Joana Cabral
- Life and Health Sciences Research Institute, University of Minho, Portugal
| | - Rodrigo Cofre
- CIMFAV-Ingemat, Facultad de Ingeniería, Universidad de Valparaíso, Valparaíso, Chile; Centre National de la Recherche Scientifique (CNRS), Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Gif-sur-Yvette, France
| | - Pedro A M Mediano
- Department of Computing, Imperial College London, London, UK; Department of Psychology, University of Cambridge, Cambridge, UK
| | - Fernando E Rosas
- Department of Informatics, University of Sussex, Brighton, UK; Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, UK; Centre for Complexity Science, Imperial College London, London, UK; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
| | - Abid Y Qureshi
- University of Kansas Medical Center, Kansas City, MO, USA
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, USA
| | - Enzo Tagliazucchi
- Departamento de Física (UBA) e Instituto de Fisica de Buenos Aires (CONICET), Buenos Aires, Argentina; Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Federico Raimondo
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Germany; Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Gustavo Deco
- Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain; Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - James M Shine
- Brain and Mind Center, The University of Sydney, Sydney, Australia
| | - Morten L Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK; Department of Psychiatry, University of Oxford, Oxford, UK; Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Patricio Orio
- Centro Interdisciplinario de Neurociencia de Valparaíso and Instituto de Neurociencia, Universidad de Valparaíso, Valparaíso, Chile
| | - ShiNung Ching
- Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Yonatan Sanz Perl
- Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain; Institut du Cerveau et de la Moelle épinière - Paris Brain Institute, ICM, Paris, France; National Scientific and Technical Research Council (CONICET), Godoy Cruz, CABA 2290, Argentina
| | - Michael N Diringer
- Department of Neurology and Neurosurgery, Washington University in St. Louis, St. Louis, MO, USA
| | - Robert D Stevens
- Departments of Anesthesiology and Critical Care Medicine, Neurology, and Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jacobo Diego Sitt
- Institut du Cerveau et de la Moelle épinière - Paris Brain Institute, ICM, Paris, France; Sorbonne Université, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France.
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28
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Perl YS, Zamora-Lopez G, Montbrió E, Monge-Asensio M, Vohryzek J, Fittipaldi S, Campo CG, Moguilner S, Ibañez A, Tagliazucchi E, Yeo BTT, Kringelbach ML, Deco G. The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations. Netw Neurosci 2023; 7:632-660. [PMID: 37397876 PMCID: PMC10312285 DOI: 10.1162/netn_a_00299] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 12/02/2022] [Indexed: 12/25/2023] Open
Abstract
Large variability exists across brain regions in health and disease, considering their cellular and molecular composition, connectivity, and function. Large-scale whole-brain models comprising coupled brain regions provide insights into the underlying dynamics that shape complex patterns of spontaneous brain activity. In particular, biophysically grounded mean-field whole-brain models in the asynchronous regime were used to demonstrate the dynamical consequences of including regional variability. Nevertheless, the role of heterogeneities when brain dynamics are supported by synchronous oscillating state, which is a ubiquitous phenomenon in brain, remains poorly understood. Here, we implemented two models capable of presenting oscillatory behavior with different levels of abstraction: a phenomenological Stuart-Landau model and an exact mean-field model. The fit of these models informed by structural- to functional-weighted MRI signal (T1w/T2w) allowed us to explore the implication of the inclusion of heterogeneities for modeling resting-state fMRI recordings from healthy participants. We found that disease-specific regional functional heterogeneity imposed dynamical consequences within the oscillatory regime in fMRI recordings from neurodegeneration with specific impacts on brain atrophy/structure (Alzheimer's patients). Overall, we found that models with oscillations perform better when structural and functional regional heterogeneities are considered, showing that phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.
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Affiliation(s)
- Yonatan Sanz Perl
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Gorka Zamora-Lopez
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Ernest Montbrió
- Neuronal Dynamics Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Martí Monge-Asensio
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Jakub Vohryzek
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom
| | - Sol Fittipaldi
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, CA, USA; and Trinity College Dublin, Dublin, Ireland
| | - Cecilia González Campo
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
| | - Sebastián Moguilner
- Global Brain Health Institute, University of California, San Francisco, CA, USA; and Trinity College Dublin, Dublin, Ireland
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Agustín Ibañez
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, CA, USA; and Trinity College Dublin, Dublin, Ireland
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Trinity College Institute of Neuroscience (TCIN), Trinity College Dublin, Dublin, Ireland
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - B. T. Thomas Yeo
- Centre for Sleep and Cognition, Centre for Translational MR Research, Department of Electrical and Computer Engineering, N.1 Institute for Health and Institute for Digital Medicine, National University of Singapore, Singapore
| | - Morten L. Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avancats (ICREA), Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, Australia
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29
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Eraifej J, Cabral J, Fernandes HM, Kahan J, He S, Mancini L, Thornton J, White M, Yousry T, Zrinzo L, Akram H, Limousin P, Foltynie T, Aziz TZ, Deco G, Kringelbach M, Green AL. Modulation of limbic resting-state networks by subthalamic nucleus deep brain stimulation. Netw Neurosci 2023; 7:478-495. [PMID: 37397890 PMCID: PMC10312264 DOI: 10.1162/netn_a_00297] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 11/29/2022] [Indexed: 09/03/2023] Open
Abstract
Beyond the established effects of subthalamic nucleus deep brain stimulation (STN-DBS) in reducing motor symptoms in Parkinson's disease, recent evidence has highlighted the effect on non-motor symptoms. However, the impact of STN-DBS on disseminated networks remains unclear. This study aimed to perform a quantitative evaluation of network-specific modulation induced by STN-DBS using Leading Eigenvector Dynamics Analysis (LEiDA). We calculated the occupancy of resting-state networks (RSNs) in functional MRI data from 10 patients with Parkinson's disease implanted with STN-DBS and statistically compared between ON and OFF conditions. STN-DBS was found to specifically modulate the occupancy of networks overlapping with limbic RSNs. STN-DBS significantly increased the occupancy of an orbitofrontal limbic subsystem with respect to both DBS OFF (p = 0.0057) and 49 age-matched healthy controls (p = 0.0033). Occupancy of a diffuse limbic RSN was increased with STN-DBS OFF when compared with healthy controls (p = 0.021), but not when STN-DBS was ON, which indicates rebalancing of this network. These results highlight the modulatory effect of STN-DBS on components of the limbic system, particularly within the orbitofrontal cortex, a structure associated with reward processing. These results reinforce the value of quantitative biomarkers of RSN activity in evaluating the disseminated impact of brain stimulation techniques and the personalization of therapeutic strategies.
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Affiliation(s)
- John Eraifej
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Henrique M. Fernandes
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Joshua Kahan
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Shenghong He
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Laura Mancini
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - John Thornton
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Mark White
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Tarek Yousry
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Ludvic Zrinzo
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Harith Akram
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Patricia Limousin
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Tom Foltynie
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Tipu Z. Aziz
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Morten Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Alexander L. Green
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
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Padilla N, Escrichs A, del Agua E, Kringelbach M, Donaire A, Deco G, Åden U. Disrupted resting-sate brain network dynamics in children born extremely preterm. Cereb Cortex 2023; 33:8101-8109. [PMID: 37083266 PMCID: PMC10321088 DOI: 10.1093/cercor/bhad101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 02/19/2023] [Accepted: 02/20/2023] [Indexed: 04/22/2023] Open
Abstract
The developing brain has to adapt to environmental and intrinsic insults after extremely preterm (EPT) birth. Ongoing maturational processes maximize their fit to the environment and this can provide a substrate for neurodevelopmental failures. Resting-state functional magnetic resonance imaging was used to scan 33 children born EPT, at < 27 weeks of gestational age, and 26 full-term controls at 10 years of age. We studied the capability of a brain area to propagate neural information (intrinsic ignition) and its variability across time (node-metastability). This framework was computed for the dorsal attention network (DAN), frontoparietal, default-mode network (DMN), and the salience, limbic, visual, and somatosensory networks. The EPT group showed reduced intrinsic ignition in the DMN and DAN, compared with the controls, and reduced node-metastability in the DMN, DAN, and salience networks. Intrinsic ignition and node-metastability values correlated with cognitive performance at 12 years of age in both groups, but only survived in the term group after adjustment. Preterm birth disturbed the signatures of functional brain organization at rest in 3 core high-order networks: DMN, salience, and DAN. Identifying vulnerable resting-state networks after EPT birth may lead to interventions that aim to rebalance brain function.
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Affiliation(s)
- Nelly Padilla
- Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm S- 171 76, Sweden
| | - Anira Escrichs
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, C/ de Ramon Trias Fargas, 25, 08018 Barcelona, España
| | - Elvira del Agua
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, C/ de Ramon Trias Fargas, 25, 08018 Barcelona, España
| | - Morten Kringelbach
- Department of Psychiatry, University of Oxford, Warneford Hospital, Warneford Ln, Oxford OX3 7JX, United Kingdom
- Center for Music in the Brain, Aarhus University Hospital Nørrebrogade 44, Building 10G, 4th and 5th floor, 8000 Aarhus C, Denmark
| | - Antonio Donaire
- Department of Neurology, Institute of Neuroscience, Hospital Clinic, Universidad de Barcelona and Institut D’investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Spain
- Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Av. Monforte de Lemos, 3-5. Pabellón 11. Planta 0 28029 Madrid, Spain
| | - Gustavo Deco
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, C/ de Ramon Trias Fargas, 25, 08018 Barcelona, España
- School of Psychological Sciences, Monash University, Melbourne, Clayton, VIC 3800, Australia
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig de Lluís Companys, 23, 08010, Barcelona, Catalonia, Spain
- Department of Neuropsychology, Max Planck Institute for human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Ulrika Åden
- Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm S- 171 76, Sweden
- Department of Neonatology, Karolinska University Hospital, Stockholm S- 171 76, Sweden
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, SE 58183, Sweden
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31
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Abstract
Scale invariance is a characteristic of neural activity. How this property emerges from neural interactions remains a fundamental question. Here, we studied the relation between scale-invariant brain dynamics and structural connectivity by analyzing human resting-state (rs-) fMRI signals, together with diffusion MRI (dMRI) connectivity and its approximation as an exponentially decaying function of the distance between brain regions. We analyzed the rs-fMRI dynamics using functional connectivity and a recently proposed phenomenological renormalization group (PRG) method that tracks the change of collective activity after successive coarse-graining at different scales. We found that brain dynamics display power-law correlations and power-law scaling as a function of PRG coarse-graining based on functional or structural connectivity. Moreover, we modeled the brain activity using a network of spins interacting through large-scale connectivity and presenting a phase transition between ordered and disordered phases. Within this simple model, we found that the observed scaling features were likely to emerge from critical dynamics and connections exponentially decaying with distance. In conclusion, our study tests the PRG method using large-scale brain activity and theoretical models and suggests that scaling of rs-fMRI activity relates to criticality.
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Affiliation(s)
- Adrián Ponce-Alvarez
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, 08005, Spain.
- Departament de Matemàtiques, Universitat Politècnica de Catalunya, Barcelona, Spain.
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, 8000, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, 08005, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, 08010, Spain
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Deco G, Perl YS, Ponce-Alvarez A, Tagliazucchi E, Whybrow P, Fuster J, Kringelbach ML. One ring to rule them all: The unifying role of prefrontal cortex in steering task-related brain dynamics. Prog Neurobiol 2023:102468. [PMID: 37301532 DOI: 10.1016/j.pneurobio.2023.102468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 05/10/2023] [Accepted: 05/18/2023] [Indexed: 06/12/2023]
Abstract
Surviving and thriving in a complex world require intricate balancing of higher order brain functions with essential survival-related behaviours. Exactly how this is achieved is not fully understood but a large body of work has shown that different regions in the prefrontal cortex (PFC) play key roles for diverse cognitive and emotional tasks including emotion, control, response inhibition, mental set shifting and working memory. We hypothesised that the key regions are hierarchically organised and we developed a framework for discovering the driving brain regions at the top of the hierarchy, responsible for steering the brain dynamics of higher brain function. We fitted a time-dependent whole-brain model to the neuroimaging data from large-scale Human Connectome Project with over 1,000 participants and computed the entropy production for rest and seven tasks (covering the main domains of cognition). This thermodynamics framework allowed us to identify the main common, unifying drivers steering the orchestration of brain dynamics during difficult tasks; located in key regions of the PFC (inferior frontal gyrus, lateral orbitofrontal cortex, rostral and caudal frontal cortex and rostral anterior cingulate cortex). Selectively lesioning these regions in the whole-brain model demonstrated their causal mechanistic importance. Overall, this shows the existence of a 'ring' of specific PFC regions ruling over the orchestration of higher brain function.
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Affiliation(s)
- Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, 08010, Spain
| | - Yonatan Sanz Perl
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, 08018, Spain; Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
| | - Adrián Ponce-Alvarez
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona, 08018, Spain
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina; Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibanez, Santiago, Chile
| | - Peter Whybrow
- University of California, Los Angeles, CA 90024, USA; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
| | - Joaquín Fuster
- University of California, Los Angeles, CA 90024, USA; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
| | - Morten L Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK; Department of Psychiatry, University of Oxford, Oxford, UK; Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, DK
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G-Guzmán E, Perl YS, Vohryzek J, Escrichs A, Manasova D, Türker B, Tagliazucchi E, Kringelbach M, Sitt JD, Deco G. The lack of temporal brain dynamics asymmetry as a signature of impaired consciousness states. Interface Focus 2023; 13:20220086. [PMID: 37065259 PMCID: PMC10102727 DOI: 10.1098/rsfs.2022.0086] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/17/2023] [Indexed: 04/18/2023] Open
Abstract
Life is a constant battle against equilibrium. From the cellular level to the macroscopic scale, living organisms as dissipative systems require the violation of their detailed balance, i.e. metabolic enzymatic reactions, in order to survive. We present a framework based on temporal asymmetry as a measure of non-equilibrium. By means of statistical physics, it was discovered that temporal asymmetries establish an arrow of time useful for assessing the reversibility in human brain time series. Previous studies in human and non-human primates have shown that decreased consciousness states such as sleep and anaesthesia result in brain dynamics closer to the equilibrium. Furthermore, there is growing interest in the analysis of brain symmetry based on neuroimaging recordings and since it is a non-invasive technique, it can be extended to different brain imaging modalities and applied at different temporo-spatial scales. In the present study, we provide a detailed description of our methodological approach, paying special attention to the theories that motivated this work. We test, for the first time, the reversibility analysis in human functional magnetic resonance imaging data in patients suffering from disorder of consciousness. We verify that the tendency of a decrease in the asymmetry of the brain signal together with the decrease in non-stationarity are key characteristics of impaired consciousness states. We expect that this work will open the way for assessing biomarkers for patients' improvement and classification, as well as motivating further research on the mechanistic understanding underlying states of impaired consciousness.
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Affiliation(s)
- Elvira G-Guzmán
- Department of Information and Communication Technologies, Centre for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Yonatan Sanz Perl
- Department of Information and Communication Technologies, Centre for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm Physiological Investigation of Clinically Normal and Impaired Cognition Team, CNRS, 75013, Paris, France
| | - Jakub Vohryzek
- Department of Information and Communication Technologies, Centre for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
| | - Anira Escrichs
- Department of Information and Communication Technologies, Centre for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Dragana Manasova
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm Physiological Investigation of Clinically Normal and Impaired Cognition Team, CNRS, 75013, Paris, France
- Université Paris Cité, Paris, France
| | - Başak Türker
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm Physiological Investigation of Clinically Normal and Impaired Cognition Team, CNRS, 75013, Paris, France
| | - Enzo Tagliazucchi
- Buenos Aires Physics Institute and Physics Department, University of Buenos Aires, Buenos Aires, Argentina
- Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Morten Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
- Department of Clinical Medicine, Center for Music in the Brain, Aarhus University, Jutland, Denmark
| | - Jacobo D. Sitt
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm Physiological Investigation of Clinically Normal and Impaired Cognition Team, CNRS, 75013, Paris, France
| | - Gustavo Deco
- Department of Information and Communication Technologies, Centre for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain
- Department of Neuropsychology, Max Planck Institute for human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, Australia
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Panda R, López-González A, Gilson M, Gosseries O, Thibaut A, Frasso G, Cecconi B, Escrichs A, Deco G, Laureys S, Zamora-López G, Annen J. Whole-brain analyses indicate the impairment of posterior integration and thalamo-frontotemporal broadcasting in disorders of consciousness. Hum Brain Mapp 2023. [PMID: 37254960 DOI: 10.1002/hbm.26386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 05/05/2023] [Accepted: 05/11/2023] [Indexed: 06/01/2023] Open
Abstract
The study of the brain's dynamical activity is opening a window to help the clinical assessment of patients with disorders of consciousness. For example, glucose uptake and the dysfunctional spread of naturalistic and synthetic stimuli has proven useful to characterize hampered consciousness. However, understanding of the mechanisms behind loss of consciousness following brain injury is still missing. Here, we study the propagation of endogenous and in-silico exogenous perturbations in patients with disorders of consciousness, based upon directed and causal interactions estimated from resting-state fMRI data, fitted to a linear model of activity propagation. We found that patients with disorders of consciousness suffer decreased capacity for neural propagation and responsiveness to events, and that this can be related to severe reduction of glucose metabolism as measured with [18 F]FDG-PET. In particular, we show that loss of consciousness is related to the malfunctioning of two neural circuits: the posterior cortical regions failing to convey information, in conjunction with reduced broadcasting of information from subcortical, temporal, parietal and frontal regions. These results shed light on the mechanisms behind disorders of consciousness, triangulating network function with basic measures of brain integrity and behavior.
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Affiliation(s)
- Rajanikant Panda
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
- University Hospital of Liège, Liège, Belgium
| | - Ane López-González
- Center for Brain and Cognition, Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain
| | - Matthieu Gilson
- Center for Brain and Cognition, Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain
- Institut des Neurosciences des Systemes, INSERM-AMU, Marseille, France
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
- University Hospital of Liège, Liège, Belgium
| | - Aurore Thibaut
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
- University Hospital of Liège, Liège, Belgium
| | - Gianluca Frasso
- Wageningen Food Safety Research, Wageningen, The Netherlands
| | - Benedetta Cecconi
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
- University Hospital of Liège, Liège, Belgium
| | - Anira Escrichs
- Center for Brain and Cognition, Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain
| | - Gustavo Deco
- Center for Brain and Cognition, Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain
- Institució Catalana de la Recerça i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Victoria, Australia
| | - Steven Laureys
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
- University Hospital of Liège, Liège, Belgium
- CERVO Research Center, Laval University, Québec, Quebec, Canada
| | - Gorka Zamora-López
- Center for Brain and Cognition, Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain
| | - Jitka Annen
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
- University Hospital of Liège, Liège, Belgium
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35
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Schirner M, Deco G, Ritter P. Learning how network structure shapes decision-making for bio-inspired computing. Nat Commun 2023; 14:2963. [PMID: 37221168 DOI: 10.1038/s41467-023-38626-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 05/10/2023] [Indexed: 05/25/2023] Open
Abstract
To better understand how network structure shapes intelligent behavior, we developed a learning algorithm that we used to build personalized brain network models for 650 Human Connectome Project participants. We found that participants with higher intelligence scores took more time to solve difficult problems, and that slower solvers had higher average functional connectivity. With simulations we identified a mechanistic link between functional connectivity, intelligence, processing speed and brain synchrony for trading accuracy with speed in dependence of excitation-inhibition balance. Reduced synchrony led decision-making circuits to quickly jump to conclusions, while higher synchrony allowed for better integration of evidence and more robust working memory. Strict tests were applied to ensure reproducibility and generality of the obtained results. Here, we identify links between brain structure and function that enable to learn connectome topology from noninvasive recordings and map it to inter-individual differences in behavior, suggesting broad utility for research and clinical applications.
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Affiliation(s)
- Michael Schirner
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, Berlin, Germany.
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Einstein Center Digital Future, Wilhelmstraße 67, 10117, Berlin, Germany.
| | - Gustavo Deco
- Department of Information and Communication Technologies, Center for Brain and Cognition, Computational Neuroscience Group, University of Pompeu Fabra, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, Melbourne, VIC, Australia
| | - Petra Ritter
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, Berlin, Germany.
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Einstein Center Digital Future, Wilhelmstraße 67, 10117, Berlin, Germany.
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Perl YS, Pallavicini C, Piccinini J, Demertzi A, Bonhomme V, Martial C, Panda R, Alnagger N, Annen J, Gosseries O, Ibañez A, Laufs H, Sitt JD, Jirsa VK, Kringelbach ML, Laureys S, Deco G, Tagliazucchi E. Low-dimensional organization of global brain states of reduced consciousness. Cell Rep 2023; 42:112491. [PMID: 37171963 DOI: 10.1016/j.celrep.2023.112491] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 03/19/2023] [Accepted: 04/24/2023] [Indexed: 05/14/2023] Open
Abstract
Brain states are frequently represented using a unidimensional scale measuring the richness of subjective experience (level of consciousness). This description assumes a mapping between the high-dimensional space of whole-brain configurations and the trajectories of brain states associated with changes in consciousness, yet this mapping and its properties remain unclear. We combine whole-brain modeling, data augmentation, and deep learning for dimensionality reduction to determine a mapping representing states of consciousness in a low-dimensional space, where distances parallel similarities between states. An orderly trajectory from wakefulness to patients with brain injury is revealed in a latent space whose coordinates represent metrics related to functional modularity and structure-function coupling, increasing alongside loss of consciousness. Finally, we investigate the effects of model perturbations, providing geometrical interpretation for the stability and reversibility of states. We conclude that conscious awareness depends on functional patterns encoded as a low-dimensional trajectory within the vast space of brain configurations.
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Affiliation(s)
- Yonatan Sanz Perl
- Department of Physics, University of Buenos Aires, Intendente Guiraldes 2160 (Ciudad Universitaria), Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina; Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina; Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain; Paris Brain Institute (ICM), Paris, France.
| | - Carla Pallavicini
- Department of Physics, University of Buenos Aires, Intendente Guiraldes 2160 (Ciudad Universitaria), Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina; Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia (FLENI), Buenos Aires, Argentina
| | - Juan Piccinini
- Department of Physics, University of Buenos Aires, Intendente Guiraldes 2160 (Ciudad Universitaria), Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
| | - Athena Demertzi
- Physiology of Cognition Research Lab, GIGA CRC-In Vivo Imaging Center, GIGA Institute, University of Liège, Liège, Belgium
| | - Vincent Bonhomme
- Anesthesia and Intensive Care Laboratory, GIGA-Consciousness, GIGA Institute, University of Liège, Liège, Belgium; University Department of Anesthesia and Intensive Care Medicine, Centre Hospitalier Régional de la Citadelle (CHR Citadelle), Liège, Belgium; Department of Anesthesia and Intensive Care Medicine, Centre Hospitalier Universitaire de Liège (CHU Liège), Liège, Belgium
| | - Charlotte Martial
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), Centre Hospitalier Universitaire de Liège (CHU Liège), Liège, Belgium
| | - Rajanikant Panda
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), Centre Hospitalier Universitaire de Liège (CHU Liège), Liège, Belgium
| | - Naji Alnagger
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), Centre Hospitalier Universitaire de Liège (CHU Liège), Liège, Belgium
| | - Jitka Annen
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), Centre Hospitalier Universitaire de Liège (CHU Liège), Liège, Belgium
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), Centre Hospitalier Universitaire de Liège (CHU Liège), Liège, Belgium
| | - Agustin Ibañez
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina; Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina; Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile; Global Brain Health Institute (GBHI), University of California-San Francisco (UCSF), San Francisco, CA, USA; Trinity College, Dublin, Ireland
| | - Helmut Laufs
- Department of Neurology and Brain Imaging Center, Goethe University, Frankfurt am Main, Germany; Department of Neurology, Christian Albrechts University, Kiel, Germany
| | - Jacobo D Sitt
- Paris Brain Institute (ICM), Paris, France; INSERM U 1127, Paris, France; CNRS UMR 7225, Paris, France
| | - Viktor K Jirsa
- Institut de Neurosciences des Systèmes, Aix Marseille Université, Marseille, France
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, UK; Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Århus, Denmark; Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, UK
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau(2), Centre Hospitalier Universitaire de Liège (CHU Liège), Liège, Belgium
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain; Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain; Institució Catalana de la Recerca i Estudis Avancats (ICREA), Barcelona, Spain
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos Aires, Intendente Guiraldes 2160 (Ciudad Universitaria), Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina; Centre du Cerveau(2), Centre Hospitalier Universitaire de Liège (CHU Liège), Liège, Belgium.
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Rolls ET, Rauschecker JP, Deco G, Huang CC, Feng J. Auditory cortical connectivity in humans. Cereb Cortex 2023; 33:6207-6227. [PMID: 36573464 PMCID: PMC10422925 DOI: 10.1093/cercor/bhac496] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 11/27/2022] [Accepted: 11/29/2022] [Indexed: 12/28/2022] Open
Abstract
To understand auditory cortical processing, the effective connectivity between 15 auditory cortical regions and 360 cortical regions was measured in 171 Human Connectome Project participants, and complemented with functional connectivity and diffusion tractography. 1. A hierarchy of auditory cortical processing was identified from Core regions (including A1) to Belt regions LBelt, MBelt, and 52; then to PBelt; and then to HCP A4. 2. A4 has connectivity to anterior temporal lobe TA2, and to HCP A5, which connects to dorsal-bank superior temporal sulcus (STS) regions STGa, STSda, and STSdp. These STS regions also receive visual inputs about moving faces and objects, which are combined with auditory information to help implement multimodal object identification, such as who is speaking, and what is being said. Consistent with this being a "what" ventral auditory stream, these STS regions then have effective connectivity to TPOJ1, STV, PSL, TGv, TGd, and PGi, which are language-related semantic regions connecting to Broca's area, especially BA45. 3. A4 and A5 also have effective connectivity to MT and MST, which connect to superior parietal regions forming a dorsal auditory "where" stream involved in actions in space. Connections of PBelt, A4, and A5 with BA44 may form a language-related dorsal stream.
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Affiliation(s)
- Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, UK
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, East China Normal University, Shanghai 200602, China
| | - Josef P Rauschecker
- Department of Neuroscience, Georgetown University Medical Center, Washington, DC 20057, USA
- Institute for Advanced Study, Technical University, Munich, Germany
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Brain and Cognition, Pompeu Fabra University, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Passeig Lluís Companys 23, Barcelona 08010, Spain
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, East China Normal University, Shanghai 200602, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
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38
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Bergoin R, Torcini A, Deco G, Quoy M, Zamora-López G. Inhibitory neurons control the consolidation of neural assemblies via adaptation to selective stimuli. Sci Rep 2023; 13:6949. [PMID: 37117236 PMCID: PMC10147639 DOI: 10.1038/s41598-023-34165-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 04/25/2023] [Indexed: 04/30/2023] Open
Abstract
Brain circuits display modular architecture at different scales of organization. Such neural assemblies are typically associated to functional specialization but the mechanisms leading to their emergence and consolidation still remain elusive. In this paper we investigate the role of inhibition in structuring new neural assemblies driven by the entrainment to various inputs. In particular, we focus on the role of partially synchronized dynamics for the creation and maintenance of structural modules in neural circuits by considering a network of excitatory and inhibitory [Formula: see text]-neurons with plastic Hebbian synapses. The learning process consists of an entrainment to temporally alternating stimuli that are applied to separate regions of the network. This entrainment leads to the emergence of modular structures. Contrary to common practice in artificial neural networks-where the acquired weights are typically frozen after the learning session-we allow for synaptic adaptation even after the learning phase. We find that the presence of inhibitory neurons in the network is crucial for the emergence and the post-learning consolidation of the modular structures. Indeed networks made of purely excitatory neurons or of neurons not respecting Dale's principle are unable to form or to maintain the modular architecture induced by the stimuli. We also demonstrate that the number of inhibitory neurons in the network is directly related to the maximal number of neural assemblies that can be consolidated, supporting the idea that inhibition has a direct impact on the memory capacity of the neural network.
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Affiliation(s)
- Raphaël Bergoin
- ETIS, UMR 8051, ENSEA, CY Cergy Paris Université, CNRS, 6 Av. du Ponceau, 95000, Cergy-Pontoise, France.
- Center for Brain and Cognition, Department of Information and Communications Technologies, Pompeu Fabra University, Carrer Ramón Trias i Fargas 25-27, 08005, Barcelona, Spain.
| | - Alessandro Torcini
- Laboratoire de Physique Théorique et Modélisation, UMR 8089, CY Cergy Paris Université, CNRS, 2 Av. Adolphe Chauvin, 95032, Cergy-Pontoise, France
| | - Gustavo Deco
- Center for Brain and Cognition, Department of Information and Communications Technologies, Pompeu Fabra University, Carrer Ramón Trias i Fargas 25-27, 08005, Barcelona, Spain
- Instituciò Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010, Barcelona, Spain
| | - Mathias Quoy
- ETIS, UMR 8051, ENSEA, CY Cergy Paris Université, CNRS, 6 Av. du Ponceau, 95000, Cergy-Pontoise, France
- IPAL, CNRS, 1 Fusionopolis Way #21-01 Connexis (South Tower), Singapore, 138632, Singapore
| | - Gorka Zamora-López
- Center for Brain and Cognition, Department of Information and Communications Technologies, Pompeu Fabra University, Carrer Ramón Trias i Fargas 25-27, 08005, Barcelona, Spain
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Lawn T, Howard MA, Turkheimer F, Misic B, Deco G, Martins D, Dipasquale O. From Neurotransmitters to Networks: Transcending Organisational Hierarchies with Molecular-informed Functional Imaging. Neurosci Biobehav Rev 2023; 150:105193. [PMID: 37086932 PMCID: PMC10390343 DOI: 10.1016/j.neubiorev.2023.105193] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 04/01/2023] [Accepted: 04/19/2023] [Indexed: 04/24/2023]
Abstract
The human brain exhibits complex interactions across micro, meso-, and macro-scale organisational principles. Recent synergistic multi-modal approaches have begun to link micro-scale information to systems level dynamics, transcending organisational hierarchies and offering novel perspectives into the brain's function and dysfunction. Specifically, the distribution of micro-scale properties (such as receptor density or gene expression) can be mapped onto macro-scale measures from functional MRI to provide novel neurobiological insights. Methodological approaches to enrich functional imaging analyses with molecular information are rapidly evolving, with several streams of research having developed relatively independently, each offering unique potential to explore the trans-hierarchical functioning of the brain. Here, we address the three principal streams of research - spatial correlation, molecular-enriched network, and in-silico whole brain modelling analyses - to provide a critical overview of the different sources of molecular information, how this information can be utilised within analyses of fMRI data, the merits and pitfalls of each methodology, and, through the use of key examples, highlight their promise to shed new light on key domains of neuroscientific inquiry.
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Affiliation(s)
- Timothy Lawn
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Matthew A Howard
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Federico Turkheimer
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Bratislav Misic
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Québec, Canada.
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Ramon Trias Fargas 25-27, Barcelona 08005, Spain; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain; Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia.
| | - Daniel Martins
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Ottavia Dipasquale
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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40
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Sanchez-Todo R, Bastos AM, Lopez-Sola E, Mercadal B, Santarnecchi E, Miller EK, Deco G, Ruffini G. A physical neural mass model framework for the analysis of oscillatory generators from laminar electrophysiological recordings. Neuroimage 2023; 270:119938. [PMID: 36775081 DOI: 10.1016/j.neuroimage.2023.119938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 01/13/2023] [Accepted: 02/09/2023] [Indexed: 02/12/2023] Open
Abstract
Cortical function emerges from the interactions of multi-scale networks that may be studied at a high level using neural mass models (NMM) that represent the mean activity of large numbers of neurons. Here, we provide first a new framework called laminar NMM, or LaNMM for short, where we combine conduction physics with NMMs to simulate electrophysiological measurements. Then, we employ this framework to infer the location of oscillatory generators from laminar-resolved data collected from the prefrontal cortex in the macaque monkey. We define a minimal model capable of generating coupled slow and fast oscillations, and we optimize LaNMM-specific parameters to fit multi-contact recordings. We rank the candidate models using an optimization function that evaluates the match between the functional connectivity (FC) of the model and data, where FC is defined by the covariance between bipolar voltage measurements at different cortical depths. The family of best solutions reproduces the FC of the observed electrophysiology by selecting locations of pyramidal cells and their synapses that result in the generation of fast activity at superficial layers and slow activity across most depths, in line with recent literature proposals. In closing, we discuss how this hybrid modeling framework can be more generally used to infer cortical circuitry.
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Affiliation(s)
- Roser Sanchez-Todo
- Department of Brain Modeling, Neuroelectrics SL, Av. Tibidabo 47b, 08035 Barcelona, Spain; Center of Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - André M Bastos
- Department of Psychology and Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, United States
| | - Edmundo Lopez-Sola
- Department of Brain Modeling, Neuroelectrics SL, Av. Tibidabo 47b, 08035 Barcelona, Spain
| | - Borja Mercadal
- Department of Brain Modeling, Neuroelectrics SL, Av. Tibidabo 47b, 08035 Barcelona, Spain
| | - Emiliano Santarnecchi
- Precision Neuroscience & Neuromodulation Program, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Earl K Miller
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Gustavo Deco
- Center of Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain; Instituci'o Catalana de la Recerca i Estudis Avan,ats (ICREA), Passeig Llu's Companys 23, Barcelona, 08010, Spain; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany; School of Psychological Sciences, Monash University, Melbourne, Clayton, VIC 3800, Australia
| | - Giulio Ruffini
- Department of Brain Modeling, Neuroelectrics SL, Av. Tibidabo 47b, 08035 Barcelona, Spain; Starlab Barcelona, Av. Tibidabo 47b, 08035 Barcelona, Spain; Haskins Laboratories, 300 George Street, New Haven, CT, 06511, USA.
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41
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Clusella P, Deco G, Kringelbach ML, Ruffini G, Garcia-Ojalvo J. Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks. PLoS Comput Biol 2023; 19:e1010781. [PMID: 37043504 PMCID: PMC10124884 DOI: 10.1371/journal.pcbi.1010781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 04/24/2023] [Accepted: 03/24/2023] [Indexed: 04/13/2023] Open
Abstract
Spatiotemporal oscillations underlie all cognitive brain functions. Large-scale brain models, constrained by neuroimaging data, aim to trace the principles underlying such macroscopic neural activity from the intricate and multi-scale structure of the brain. Despite substantial progress in the field, many aspects about the mechanisms behind the onset of spatiotemporal neural dynamics are still unknown. In this work we establish a simple framework for the emergence of complex brain dynamics, including high-dimensional chaos and travelling waves. The model consists of a complex network of 90 brain regions, whose structural connectivity is obtained from tractography data. The activity of each brain area is governed by a Jansen neural mass model and we normalize the total input received by each node so it amounts the same across all brain areas. This assumption allows for the existence of an homogeneous invariant manifold, i.e., a set of different stationary and oscillatory states in which all nodes behave identically. Stability analysis of these homogeneous solutions unveils a transverse instability of the synchronized state, which gives rise to different types of spatiotemporal dynamics, such as chaotic alpha activity. Additionally, we illustrate the ubiquity of this route towards complex spatiotemporal activity in a network of next-generation neural mass models. Altogehter, our results unveil the bifurcation landscape that underlies the emergence of function from structure in the brain.
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Affiliation(s)
- Pau Clusella
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Gustavo Deco
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Giulio Ruffini
- Brain Modeling Department, Neuroelectrics, Barcelona, Spain
| | - Jordi Garcia-Ojalvo
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
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42
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Rolls ET, Deco G, Huang CC, Feng J. Prefrontal and somatosensory-motor cortex effective connectivity in humans. Cereb Cortex 2023; 33:4939-4963. [PMID: 36227217 DOI: 10.1093/cercor/bhac1496] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 09/07/2022] [Accepted: 09/08/2022] [Indexed: 05/27/2023] Open
Abstract
Effective connectivity, functional connectivity, and tractography were measured between 57 cortical frontal and somatosensory regions and the 360 cortical regions in the Human Connectome Project (HCP) multimodal parcellation atlas for 171 HCP participants. A ventral somatosensory stream connects from 3b and 3a via 1 and 2 and then via opercular and frontal opercular regions to the insula, which then connects to inferior parietal PF regions. This stream is implicated in "what"-related somatosensory processing of objects and of the body and in combining with visual inputs in PF. A dorsal "action" somatosensory stream connects from 3b and 3a via 1 and 2 to parietal area 5 and then 7. Inferior prefrontal regions have connectivity with the inferior temporal visual cortex and orbitofrontal cortex, are implicated in working memory for "what" processing streams, and provide connectivity to language systems, including 44, 45, 47l, TPOJ1, and superior temporal visual area. The dorsolateral prefrontal cortex regions that include area 46 have connectivity with parietal area 7 and somatosensory inferior parietal regions and are implicated in working memory for actions and planning. The dorsal prefrontal regions, including 8Ad and 8Av, have connectivity with visual regions of the inferior parietal cortex, including PGs and PGi, and are implicated in visual and auditory top-down attention.
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Affiliation(s)
- Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, UK
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
| | - Gustavo Deco
- Computational Neuroscience Group, Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain
- Brain and Cognition, Pompeu Fabra University, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Passeig Lluís Companys 23, Barcelona 08010, Spain
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200602, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 200602, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
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43
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Idesis S, Allegra M, Vohryzek J, Sanz Perl Y, Faskowitz J, Corbetta M, Sporns O, Deco G. P-107 Dimensionality reduction in stroke patients neuroimaging data. Clin Neurophysiol 2023. [DOI: 10.1016/j.clinph.2023.02.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
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44
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Sanz Perl Y, Fittipaldi S, Gonzalez Campo C, Moguilner S, Cruzat J, Fraile-Vazquez ME, Herzog R, Kringelbach ML, Deco G, Prado P, Ibanez A, Tagliazucchi E. Model-based whole-brain perturbational landscape of neurodegenerative diseases. eLife 2023; 12:83970. [PMID: 36995213 PMCID: PMC10063230 DOI: 10.7554/elife.83970] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 03/15/2023] [Indexed: 03/31/2023] Open
Abstract
The treatment of neurodegenerative diseases is hindered by lack of interventions capable of steering multimodal whole-brain dynamics towards patterns indicative of preserved brain health. To address this problem, we combined deep learning with a model capable of reproducing whole-brain functional connectivity in patients diagnosed with Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD). These models included disease-specific atrophy maps as priors to modulate local parameters, revealing increased stability of hippocampal and insular dynamics as signatures of brain atrophy in AD and bvFTD, respectively. Using variational autoencoders, we visualized different pathologies and their severity as the evolution of trajectories in a low-dimensional latent space. Finally, we perturbed the model to reveal key AD- and bvFTD-specific regions to induce transitions from pathological to healthy brain states. Overall, we obtained novel insights on disease progression and control by means of external stimulation, while identifying dynamical mechanisms that underlie functional alterations in neurodegeneration.
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Affiliation(s)
- Yonatan Sanz Perl
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
| | - Sol Fittipaldi
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
| | - Cecilia Gonzalez Campo
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
| | - Sebastián Moguilner
- Global Brain Health Institute, University of California, San Francisco, San Francisco, United States
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Josephine Cruzat
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | | | - Rubén Herzog
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Århus, Denmark
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avancats (ICREA), Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Clayton, Australia
| | - Pavel Prado
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
| | - Agustin Ibanez
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, San Francisco, United States
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Trinity College Institute of Neuroscience (TCIN), Trinity College Dublin, Dublin, Ireland
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), CABA, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
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45
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Mana L, Vila-Vidal M, Köckeritz C, Aquino K, Fornito A, Kringelbach ML, Deco G. Using in silico perturbational approach to identify critical areas in schizophrenia. Cereb Cortex 2023:7078818. [PMID: 36929009 DOI: 10.1093/cercor/bhad067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/10/2023] [Accepted: 02/11/2023] [Indexed: 03/17/2023] Open
Abstract
Schizophrenia is a debilitating neuropsychiatric disorder whose underlying correlates remain unclear despite decades of neuroimaging investigation. One contentious topic concerns the role of global signal (GS) fluctuations and how they affect more focal functional changes. Moreover, it has been difficult to pinpoint causal mechanisms of circuit disruption. Here, we analyzed resting-state fMRI data from 47 schizophrenia patients and 118 age-matched healthy controls and used dynamical analyses to investigate how global fluctuations and other functional metastable states are affected by this disorder. We found that brain dynamics in the schizophrenia group were characterized by an increased probability of globally coherent states and reduced recurrence of a substate dominated by coupled activity in the default mode and limbic networks. We then used the in silico perturbation of a whole-brain model to identify critical areas involved in the disease. Perturbing a set of temporo-parietal sensory and associative areas in a model of the healthy brain reproduced global pathological dynamics. Healthy brain dynamics were instead restored by perturbing a set of medial fronto-temporal and cingulate regions in the model of pathology. These results highlight the relevance of GS alterations in schizophrenia and identify a set of vulnerable areas involved in determining a shift in brain state.
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Affiliation(s)
- Ludovica Mana
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain
| | - Manel Vila-Vidal
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain.,Computational Biology and Complex Systems Group, Department of Physics, Universitat Politècnica de Catalunya, Barcelona 08028, Spain
| | - Charlotte Köckeritz
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain
| | - Kevin Aquino
- School of Psychological Sciences and Monash Biomedical Imaging, Turner Institute for Brain and Mental Health, Monash University, Clayton, Melbourne, state of Victoria 3800, Australia
| | - Alex Fornito
- School of Psychological Sciences and Monash Biomedical Imaging, Turner Institute for Brain and Mental Health, Monash University, Clayton, Melbourne, state of Victoria 3800, Australia
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford OX1 4BH, United Kingdom.,Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford OX1 4BH, United Kingdom.,Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus 8000, Denmark
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain.,Institució Catalana de la Recerca i Estudis Avancats (ICREA), Passeig Lluis Companys 23, Barcelona 08010, Spain
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46
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Rolls ET, Deco G, Huang CC, Feng J. The human posterior parietal cortex: effective connectome, and its relation to function. Cereb Cortex 2023; 33:3142-3170. [PMID: 35834902 PMCID: PMC10401905 DOI: 10.1093/cercor/bhac266] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 06/10/2022] [Accepted: 06/11/2022] [Indexed: 01/04/2023] Open
Abstract
The effective connectivity between 21 regions in the human posterior parietal cortex, and 360 cortical regions was measured in 171 Human Connectome Project (HCP) participants using the HCP atlas, and complemented with functional connectivity and diffusion tractography. Intraparietal areas LIP, VIP, MIP, and AIP have connectivity from early cortical visual regions, and to visuomotor regions such as the frontal eye fields, consistent with functions in eye saccades and tracking. Five superior parietal area 7 regions receive from similar areas and from the intraparietal areas, but also receive somatosensory inputs and connect with premotor areas including area 6, consistent with functions in performing actions to reach for, grasp, and manipulate objects. In the anterior inferior parietal cortex, PFop, PFt, and PFcm are mainly somatosensory, and PF in addition receives visuo-motor and visual object information, and is implicated in multimodal shape and body image representations. In the posterior inferior parietal cortex, PFm and PGs combine visuo-motor, visual object, and reward input and connect with the hippocampal system. PGi in addition provides a route to motion-related superior temporal sulcus regions involved in social interactions. PGp has connectivity with intraparietal regions involved in coordinate transforms and may be involved in idiothetic update of hippocampal visual scene representations.
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Affiliation(s)
- Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, United Kingdom
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
| | - Gustavo Deco
- Computational Neuroscience Group, Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain
- Brain and Cognition, Pompeu Fabra University, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Passeig Lluís Companys 23, Barcelona 08010, Spain
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), School of Psychology and Cognitive Science, Institute of Brain and Education Innovation, East China Normal University, Shanghai 200602, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 200602, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
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47
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Cruzat J, Herzog R, Prado P, Sanz-Perl Y, Gonzalez-Gomez R, Moguilner S, Kringelbach ML, Deco G, Tagliazucchi E, Ibañez A. Temporal Irreversibility of Large-Scale Brain Dynamics in Alzheimer's Disease. J Neurosci 2023; 43:1643-1656. [PMID: 36732071 PMCID: PMC10008060 DOI: 10.1523/jneurosci.1312-22.2022] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 12/12/2022] [Accepted: 12/25/2022] [Indexed: 02/04/2023] Open
Abstract
Healthy brain dynamics can be understood as the emergence of a complex system far from thermodynamic equilibrium. Brain dynamics are temporally irreversible and thus establish a preferred direction in time (i.e., arrow of time). However, little is known about how the time-reversal symmetry of spontaneous brain activity is affected by Alzheimer's disease (AD). We hypothesized that the level of irreversibility would be compromised in AD, signaling a fundamental shift in the collective properties of brain activity toward equilibrium dynamics. We investigated the irreversibility from resting-state fMRI and EEG data in male and female human patients with AD and elderly healthy control subjects (HCs). We quantified the level of irreversibility and, thus, proximity to nonequilibrium dynamics by comparing forward and backward time series through time-shifted correlations. AD was associated with a breakdown of temporal irreversibility at the global, local, and network levels, and at multiple oscillatory frequency bands. At the local level, temporoparietal and frontal regions were affected by AD. The limbic, frontoparietal, default mode, and salience networks were the most compromised at the network level. The temporal reversibility was associated with cognitive decline in AD and gray matter volume in HCs. The irreversibility of brain dynamics provided higher accuracy and more distinctive information than classical neurocognitive measures when differentiating AD from control subjects. Findings were validated using an out-of-sample cohort. Present results offer new evidence regarding pathophysiological links between the entropy generation rate of brain dynamics and the clinical presentation of AD, opening new avenues for dementia characterization at different levels.SIGNIFICANCE STATEMENT By assessing the irreversibility of large-scale dynamics across multiple brain signals, we provide a precise signature capable of distinguishing Alzheimer's disease (AD) at the global, local, and network levels and different oscillatory regimes. Irreversibility of limbic, frontoparietal, default-mode, and salience networks was the most compromised by AD compared with more sensory-motor networks. Moreover, the time-irreversibility properties associated with cognitive decline and atrophy outperformed and complemented classical neurocognitive markers of AD in predictive classification performance. Findings were generalized and replicated with an out-of-sample validation procedure. We provide novel multilevel evidence of reduced irreversibility in AD brain dynamics that has the potential to open new avenues for understating neurodegeneration in terms of the temporal asymmetry of brain dynamics.
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Affiliation(s)
- Josephine Cruzat
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- Fundación para el Estudio de la Conciencia Humana (ECoH), 7550000, Santiago, Chile
| | - Ruben Herzog
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- Fundación para el Estudio de la Conciencia Humana (ECoH), 7550000, Santiago, Chile
| | - Pavel Prado
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
| | - Yonatan Sanz-Perl
- Department of Physics, University of Buenos Aires, C1428EGA, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), C1033AAJ, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, C116ABJ, Buenos Aires, Argentina
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, 08005 Barcelona, Spain
| | - Raul Gonzalez-Gomez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
| | - Sebastian Moguilner
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- Global Brain Health Institute, University of California, San Francisco, San Francisco, California 94143
- Global Brain Health Institute, Trinity College, Dublin 2, Ireland
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, 8000 Århus, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford OX3 9BX, United Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, 08005 Barcelona, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avancats (ICREA), 08010 Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, D-04303 Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne 3168, Australia
| | - Enzo Tagliazucchi
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- Department of Physics, University of Buenos Aires, C1428EGA, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), C1033AAJ, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, C116ABJ, Buenos Aires, Argentina
| | - Agustín Ibañez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, 7911328, Santiago, Chile
- National Scientific and Technical Research Council (CONICET), C1033AAJ, Buenos Aires, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, C116ABJ, Buenos Aires, Argentina
- Global Brain Health Institute, University of California, San Francisco, San Francisco, California 94143
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
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48
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Martí-Juan G, Sastre-Garriga J, Martinez-Heras E, Vidal-Jordana A, Llufriu S, Groppa S, Gonzalez-Escamilla G, Rocca MA, Filippi M, Høgestøl EA, Harbo HF, Foster MA, Toosy AT, Schoonheim MM, Tewarie P, Pontillo G, Petracca M, Rovira À, Deco G, Pareto D. Using The Virtual Brain to study the relationship between structural and functional connectivity in patients with multiple sclerosis: a multicenter study. Cereb Cortex 2023:7051071. [PMID: 36813475 DOI: 10.1093/cercor/bhad041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/25/2023] [Accepted: 01/26/2023] [Indexed: 02/24/2023] Open
Abstract
The relationship between structural connectivity (SC) and functional connectivity (FC) captured from magnetic resonance imaging, as well as its interaction with disability and cognitive impairment, is not well understood in people with multiple sclerosis (pwMS). The Virtual Brain (TVB) is an open-source brain simulator for creating personalized brain models using SC and FC. The aim of this study was to explore SC-FC relationship in MS using TVB. Two different model regimes have been studied: stable and oscillatory, with the latter including conduction delays in the brain. The models were applied to 513 pwMS and 208 healthy controls (HC) from 7 different centers. Models were analyzed using structural damage, global diffusion properties, clinical disability, cognitive scores, and graph-derived metrics from both simulated and empirical FC. For the stable model, higher SC-FC coupling was associated with pwMS with low Single Digit Modalities Test (SDMT) score (F=3.48, P$\lt$0.05), suggesting that cognitive impairment in pwMS is associated with a higher SC-FC coupling. Differences in entropy of the simulated FC between HC, high and low SDMT groups (F=31.57, P$\lt$1e-5), show that the model captures subtle differences not detected in the empirical FC, suggesting the existence of compensatory and maladaptive mechanisms between SC and FC in MS.
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Affiliation(s)
- Gerard Martí-Juan
- Neuroradiology Group, Vall d'Hebron Research Institute (VHIR), Barcelona 08035, Spain
| | - Jaume Sastre-Garriga
- Department of Neurology, Multiple Sclerosis center of Catalonia (Cemcat), Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona (UAB), Barcelona 08035, Spain
| | - Eloy Martinez-Heras
- Center of Neuroimmunology and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Angela Vidal-Jordana
- Department of Neurology, Multiple Sclerosis center of Catalonia (Cemcat), Vall d'Hebron University Hospital, Universitat Autònoma de Barcelona (UAB), Barcelona 08035, Spain
| | - Sara Llufriu
- Center of Neuroimmunology and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM), Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), University Medical Center of the Johannes Gutenberg University Mainz, Rhine Main Neuroscience Network (rmn2), Mainz 55131, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), University Medical Center of the Johannes Gutenberg University Mainz, Rhine Main Neuroscience Network (rmn2), Mainz 55131, Germany
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
- Vita-Salute, San Raffaele University, Milan 20132, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
- Vita-Salute, San Raffaele University, Milan 20132, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Einar A Høgestøl
- Department of Neurology, Oslo University Hospital, Oslo 0450 , Norway
- Department of Psychology, University of Olso, Oslo 0315, Norway
| | - Hanne F Harbo
- Department of Neurology, Oslo University Hospital, Oslo 0450 , Norway
- Institute of Clinical Medicine, University of Oslo, Oslo 0315, Norway
| | - Michael A Foster
- Queen Square MS Centre, Dept of Neuroinflammation, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
| | - Ahmed T Toosy
- Queen Square MS Centre, Dept of Neuroinflammation, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
| | - Menno M Schoonheim
- Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, The Netherlands
| | - Prejaas Tewarie
- MS Center Amsterdam, Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, The Netherlands
| | - Giuseppe Pontillo
- Queen Square MS Centre, Dept of Neuroinflammation, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
- Departments of Advanced Biomedical Sciences and Electrical Engineering and Information Technology, University of Naples "Federico II", Naples 80138, Italy
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1081 HZ, The Netherlands
| | - Maria Petracca
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University of Naples "Federico II", Naples 80138, Italy
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Àlex Rovira
- Neuroradiology Group, Vall d'Hebron Research Institute (VHIR), Barcelona 08035, Spain
- Radiology (IDI), Vall d'Hebron University Hospital, Barcelona 08036, Spain
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats, Universitat Pompeu Fabra, Barcelona 08010, Spain
| | - Deborah Pareto
- Neuroradiology Group, Vall d'Hebron Research Institute (VHIR), Barcelona 08035, Spain
- Radiology (IDI), Vall d'Hebron University Hospital, Barcelona 08036, Spain
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49
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de la Fuente LA, Zamberlan F, Bocaccio H, Kringelbach M, Deco G, Perl YS, Pallavicini C, Tagliazucchi E. Temporal irreversibility of neural dynamics as a signature of consciousness. Cereb Cortex 2023; 33:1856-1865. [PMID: 35512291 DOI: 10.1093/cercor/bhac177] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 04/16/2022] [Accepted: 04/18/2022] [Indexed: 11/14/2022] Open
Abstract
Dissipative systems evolve in the preferred temporal direction indicated by the thermodynamic arrow of time. The fundamental nature of this temporal asymmetry led us to hypothesize its presence in the neural activity evoked by conscious perception of the physical world, and thus its covariance with the level of conscious awareness. We implemented a data-driven deep learning framework to decode the temporal inversion of electrocorticography signals acquired from non-human primates. Brain activity time series recorded during conscious wakefulness could be distinguished from their inverted counterparts with high accuracy, both using frequency and phase information. However, classification accuracy was reduced for data acquired during deep sleep and under ketamine-induced anesthesia; moreover, the predictions obtained from multiple independent neural networks were less consistent for sleep and anesthesia than for conscious wakefulness. Finally, the analysis of feature importance scores highlighted transitions between slow ($\approx$20 Hz) and fast frequencies (>40 Hz) as the main contributors to the temporal asymmetry observed during conscious wakefulness. Our results show that a preferred temporal direction is manifest in the neural activity evoked by conscious mentation and in the phenomenology of the passage of time, establishing common ground to tackle the relationship between brain and subjective experience.
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Affiliation(s)
- Laura Alethia de la Fuente
- Department of Physics, University of Buenos Aires 1428, Argentina.,Institute of Cognitive and Translational Neuroscience, INECO Foundation, Favaloro University, Buenos Aires 1058, Argentina.,National Scientific and Technical Research Council, Buenos Aires 1425, Argentina
| | - Federico Zamberlan
- Department of Physics, University of Buenos Aires 1428, Argentina.,National Scientific and Technical Research Council, Buenos Aires 1425, Argentina.,Cognitive Science and Artificial Intelligence Department, Tilburg University, Tilburg 5000, The Netherlands
| | - Hernán Bocaccio
- Department of Physics, University of Buenos Aires 1428, Argentina.,National Scientific and Technical Research Council, Buenos Aires 1425, Argentina
| | - Morten Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford OX1, UK.,Department of Psychiatry, University of Oxford, Oxford OX3, UK.,Center for Music in the Brain, Department of Clinical Medicine, Aarhus University 8000, DK
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain.,Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona 08010, Spain.,Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany.,School of Psychological Sciences, Monash University, Melbourne, Clayton VIC 3800, Australia
| | - Yonatan Sanz Perl
- Department of Physics, University of Buenos Aires 1428, Argentina.,Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain
| | - Carla Pallavicini
- Department of Physics, University of Buenos Aires 1428, Argentina.,National Scientific and Technical Research Council, Buenos Aires 1425, Argentina
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos Aires 1428, Argentina.,National Scientific and Technical Research Council, Buenos Aires 1425, Argentina.,Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibanez, Santiago 7910000, Chile
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50
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Ruffini G, Damiani G, Lozano-Soldevilla D, Deco N, Rosas FE, Kiani NA, Ponce-Alvarez A, Kringelbach ML, Carhart-Harris R, Deco G. LSD-induced increase of Ising temperature and algorithmic complexity of brain dynamics. PLoS Comput Biol 2023; 19:e1010811. [PMID: 36735751 PMCID: PMC9943020 DOI: 10.1371/journal.pcbi.1010811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 02/21/2023] [Accepted: 12/11/2022] [Indexed: 02/04/2023] Open
Abstract
A topic of growing interest in computational neuroscience is the discovery of fundamental principles underlying global dynamics and the self-organization of the brain. In particular, the notion that the brain operates near criticality has gained considerable support, and recent work has shown that the dynamics of different brain states may be modeled by pairwise maximum entropy Ising models at various distances from a phase transition, i.e., from criticality. Here we aim to characterize two brain states (psychedelics-induced and placebo) as captured by functional magnetic resonance imaging (fMRI), with features derived from the Ising spin model formalism (system temperature, critical point, susceptibility) and from algorithmic complexity. We hypothesized, along the lines of the entropic brain hypothesis, that psychedelics drive brain dynamics into a more disordered state at a higher Ising temperature and increased complexity. We analyze resting state blood-oxygen-level-dependent (BOLD) fMRI data collected in an earlier study from fifteen subjects in a control condition (placebo) and during ingestion of lysergic acid diethylamide (LSD). Working with the automated anatomical labeling (AAL) brain parcellation, we first create "archetype" Ising models representative of the entire dataset (global) and of the data in each condition. Remarkably, we find that such archetypes exhibit a strong correlation with an average structural connectome template obtained from dMRI (r = 0.6). We compare the archetypes from the two conditions and find that the Ising connectivity in the LSD condition is lower than in the placebo one, especially in homotopic links (interhemispheric connectivity), reflecting a significant decrease of homotopic functional connectivity in the LSD condition. The global archetype is then personalized for each individual and condition by adjusting the system temperature. The resulting temperatures are all near but above the critical point of the model in the paramagnetic (disordered) phase. The individualized Ising temperatures are higher in the LSD condition than in the placebo condition (p = 9 × 10-5). Next, we estimate the Lempel-Ziv-Welch (LZW) complexity of the binarized BOLD data and the synthetic data generated with the individualized model using the Metropolis algorithm for each participant and condition. The LZW complexity computed from experimental data reveals a weak statistical relationship with condition (p = 0.04 one-tailed Wilcoxon test) and none with Ising temperature (r(13) = 0.13, p = 0.65), presumably because of the limited length of the BOLD time series. Similarly, we explore complexity using the block decomposition method (BDM), a more advanced method for estimating algorithmic complexity. The BDM complexity of the experimental data displays a significant correlation with Ising temperature (r(13) = 0.56, p = 0.03) and a weak but significant correlation with condition (p = 0.04, one-tailed Wilcoxon test). This study suggests that the effects of LSD increase the complexity of brain dynamics by loosening interhemispheric connectivity-especially homotopic links. In agreement with earlier work using the Ising formalism with BOLD data, we find the brain state in the placebo condition is already above the critical point, with LSD resulting in a shift further away from criticality into a more disordered state.
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Affiliation(s)
- Giulio Ruffini
- Neuroelectrics Barcelona, Barcelona, Spain
- Starlab Barcelona, Barcelona, Spain
- Haskins Laboratories, New Haven, Connecticut, United States of America
- * E-mail:
| | | | | | | | - Fernando E. Rosas
- Department of Informatics, University of Sussex, Brighton, United Kingdom
- Centre For Psychedelic Research (Department of Brain Science), Imperial College London, London, United Kingdom
- Centre for Complexity Science, Imperial College London, London, United Kingdom
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom
| | - Narsis A. Kiani
- Algorithmic Dynamics Lab, Center of Molecular Medicine, Karolinksa Institutet, Stockholm, Sweden
- Oncology and Pathology Department, Karolinksa Institutet, Stockholm, Sweden
| | - Adrián Ponce-Alvarez
- Computational Neuroscience Group, Center for Brain and Cognition (Department of Information and Communication Technologies), Universitat Pompeu Fabra, Barcelona, Spain
| | - Morten L. Kringelbach
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Robin Carhart-Harris
- Centre For Psychedelic Research (Department of Brain Science), Imperial College London, London, United Kingdom
- Psychedelics Division - Neuroscape, University of California San Francisco, San Francisco, California, United States of America
| | - Gustavo Deco
- The Catalan Institution for Research and Advanced Studies (ICREA), Universitat Pompeu Fabra, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, Australia
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