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Cardone P, Alnagger N, Annen J, Bicego A, Gosseries O, Martial C. Psychedelics and disorders of consciousness: the current landscape and the path forward. Neurosci Conscious 2024; 2024:niae025. [PMID: 38881630 PMCID: PMC11179162 DOI: 10.1093/nc/niae025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 02/16/2024] [Accepted: 05/20/2024] [Indexed: 06/18/2024] Open
Abstract
Modern medicine has been shaken by the surge of psychedelic science that proposes a new approach to mitigate mental disorders, such as depression and post-traumatic stress disorder. Clinical trials to investigate whether psychedelic substances can treat psychiatric conditions are now underway, yet less discussion gravitates around their use in neurological disorders due to brain injury. One suggested implementation of brain-complexity enhancing psychedelics is to treat people with post-comatose disorders of consciousness (DoC). In this article, we discuss the rationale of this endeavour, examining possible outcomes of such experiments by postulating the existence of an optimal level of complexity. We consider the possible counterintuitive effects of both psychedelics and DoC on the functional connectivity of the default mode network and its possible impact on selfhood. We also elaborate on the role of computational modelling in providing complementary information to experimental studies, both contributing to our understanding of the treatment mechanisms and providing a path towards personalized medicine. Finally, we update the discourse surrounding the ethical considerations, encompassing clinical and scientific values.
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Affiliation(s)
- Paolo Cardone
- Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Centre du Cerveau2, University Hospital of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
| | - Naji Alnagger
- Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Centre du Cerveau2, University Hospital of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
| | - Jitka Annen
- Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Centre du Cerveau2, University Hospital of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Department of Data Analysis, University of Ghent, Henri Dunantlaan 1, Ghent 9000, Belgium
| | - Aminata Bicego
- Sensation and Perception Research Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Centre du Cerveau2, University Hospital of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Sensation and Perception Research Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
| | - Charlotte Martial
- Coma Science Group, GIGA-Consciousness, University of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
- Centre du Cerveau2, University Hospital of Liège, Avenue de l'hôpital 11, Liège 4000, Belgium
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2
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Shallow MC, Tian L, Lin H, Lefton KB, Chen S, Dougherty JD, Culver JP, Lambo ME, Hengen KB. At the onset of active whisking, the input layer of barrel cortex exhibits a 24 h window of increased excitability that depends on prior experience. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.04.597353. [PMID: 38895408 PMCID: PMC11185658 DOI: 10.1101/2024.06.04.597353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
The development of motor control over sensory organs is a critical milestone in sensory processing, enabling active exploration and shaping of the sensory environment. However, whether the onset of sensory organ motor control directly influences the development of corresponding sensory cortices remains unknown. Here, we exploit the late onset of whisking behavior in mice to address this question in the somatosensory system. Using ex vivo electrophysiology, we discovered a transient increase in the intrinsic excitability of excitatory neurons in layer IV of the barrel cortex, which processes whisker input, precisely coinciding with the onset of active whisking at postnatal day 14 (P14). This increase in neuronal gain was specific to layer IV, independent of changes in synaptic strength, and required prior sensory experience. Strikingly, the effect was not observed in layer II/III of the barrel cortex or in the visual cortex upon eye opening, suggesting a unique interaction between the development of active sensing and the thalamocortical input layer in the somatosensory system. Predictive modeling indicated that changes in active membrane conductances alone could reliably distinguish P14 neurons in control but not whisker-deprived hemispheres. Our findings demonstrate an experience-dependent, lamina-specific refinement of neuronal excitability tightly linked to the emergence of active whisking. This transient increase in the gain of the thalamic input layer coincides with a critical period for synaptic plasticity in downstream layers, suggesting a role in facilitating cortical maturation and sensory processing. Together, our results provide evidence for a direct interaction between the development of motor control and sensory cortex, offering new insights into the experience-dependent development and refinement of sensory systems. These findings have broad implications for understanding the interplay between motor and sensory development, and how the mechanisms of perception cooperate with behavior.
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Wen W, Turrigiano GG. Modular Arrangement of Synaptic and Intrinsic Homeostatic Plasticity within Visual Cortical Circuits. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.01.596982. [PMID: 38853882 PMCID: PMC11160741 DOI: 10.1101/2024.06.01.596982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Neocortical circuits use synaptic and intrinsic forms of homeostatic plasticity to stabilize key features of network activity, but whether these different homeostatic mechanisms act redundantly, or can be independently recruited to stabilize different network features, is unknown. Here we used pharmacological and genetic perturbations both in vitro and in vivo to determine whether synaptic scaling and intrinsic homeostatic plasticity (IHP) are arranged and recruited in a hierarchical or modular manner within L2/3 pyramidal neurons in rodent V1. Surprisingly, although the expression of synaptic scaling and IHP was dependent on overlapping trafficking pathways, they could be independently recruited by manipulating spiking activity or NMDAR signaling, respectively. Further, we found that changes in visual experience that affect NMDAR activation but not mean firing selectively trigger IHP, without recruiting synaptic scaling. These findings support a modular model in which synaptic and intrinsic homeostatic plasticity respond to and stabilize distinct aspects of network activity.
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Affiliation(s)
- Wei Wen
- Department of Biology, Brandeis University, Waltham, MA 02453, USA
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Fontenele AJ, Sooter JS, Norman VK, Gautam SH, Shew WL. Low-dimensional criticality embedded in high-dimensional awake brain dynamics. SCIENCE ADVANCES 2024; 10:eadj9303. [PMID: 38669340 PMCID: PMC11051676 DOI: 10.1126/sciadv.adj9303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 03/26/2024] [Indexed: 04/28/2024]
Abstract
Whether cortical neurons operate in a strongly or weakly correlated dynamical regime determines fundamental information processing capabilities and has fueled decades of debate. We offer a resolution of this debate; we show that two important dynamical regimes, typically considered incompatible, can coexist in the same local cortical circuit by separating them into two different subspaces. In awake mouse motor cortex, we find a low-dimensional subspace with large fluctuations consistent with criticality-a dynamical regime with moderate correlations and multi-scale information capacity and transmission. Orthogonal to this critical subspace, we find a high-dimensional subspace containing a desynchronized dynamical regime, which may optimize input discrimination. The critical subspace is apparent only at long timescales, which explains discrepancies among some previous studies. Using a computational model, we show that the emergence of a low-dimensional critical subspace at large timescales agrees with established theory of critical dynamics. Our results suggest that the cortex leverages its high dimensionality to multiplex dynamical regimes across different subspaces.
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Morrell MC, Nemenman I, Sederberg A. Neural criticality from effective latent variables. eLife 2024; 12:RP89337. [PMID: 38470471 PMCID: PMC10957169 DOI: 10.7554/elife.89337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2024] Open
Abstract
Observations of power laws in neural activity data have raised the intriguing notion that brains may operate in a critical state. One example of this critical state is 'avalanche criticality', which has been observed in various systems, including cultured neurons, zebrafish, rodent cortex, and human EEG. More recently, power laws were also observed in neural populations in the mouse under an activity coarse-graining procedure, and they were explained as a consequence of the neural activity being coupled to multiple latent dynamical variables. An intriguing possibility is that avalanche criticality emerges due to a similar mechanism. Here, we determine the conditions under which latent dynamical variables give rise to avalanche criticality. We find that populations coupled to multiple latent variables produce critical behavior across a broader parameter range than those coupled to a single, quasi-static latent variable, but in both cases, avalanche criticality is observed without fine-tuning of model parameters. We identify two regimes of avalanches, both critical but differing in the amount of information carried about the latent variable. Our results suggest that avalanche criticality arises in neural systems in which activity is effectively modeled as a population driven by a few dynamical variables and these variables can be inferred from the population activity.
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Affiliation(s)
- Mia C Morrell
- Department of Physics, New York UniversityNew YorkUnited States
| | - Ilya Nemenman
- Department of Physics, Department of Biology, Initiative in Theory and Modeling of Living Systems, Emory UniversityAtlantaUnited States
| | - Audrey Sederberg
- Department of Neuroscience, University of Minnesota Medical SchoolMinneapolisUnited States
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6
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Jäger AP, Bailey A, Huntenburg JM, Tardif CL, Villringer A, Gauthier CJ, Nikulin V, Bazin P, Steele CJ. Decreased long-range temporal correlations in the resting-state functional magnetic resonance imaging blood-oxygen-level-dependent signal reflect motor sequence learning up to 2 weeks following training. Hum Brain Mapp 2024; 45:e26539. [PMID: 38124341 PMCID: PMC10915743 DOI: 10.1002/hbm.26539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 11/03/2023] [Accepted: 11/07/2023] [Indexed: 12/23/2023] Open
Abstract
Decreased long-range temporal correlations (LRTC) in brain signals can be used to measure cognitive effort during task execution. Here, we examined how learning a motor sequence affects long-range temporal memory within resting-state functional magnetic resonance imaging signal. Using the Hurst exponent (HE), we estimated voxel-wise LRTC and assessed changes over 5 consecutive days of training, followed by a retention scan 12 days later. The experimental group learned a complex visuomotor sequence while a complementary control group performed tightly matched movements. An interaction analysis revealed that HE decreases were specific to the complex sequence and occurred in well-known motor sequence learning associated regions including left supplementary motor area, left premotor cortex, left M1, left pars opercularis, bilateral thalamus, and right striatum. Five regions exhibited moderate to strong negative correlations with overall behavioral performance improvements. Following learning, HE values returned to pretraining levels in some regions, whereas in others, they remained decreased even 2 weeks after training. Our study presents new evidence of HE's possible relevance for functional plasticity during the resting-state and suggests that a cortical subset of sequence-specific regions may continue to represent a functional signature of learning reflected in decreased long-range temporal dependence after a period of inactivity.
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Affiliation(s)
- Anna‐Thekla P. Jäger
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Center for Stroke Research Berlin (CSB)Charité—Universitätsmedizin BerlinBerlinGermany
- Brain Language LabFreie Universität BerlinBerlinGermany
| | - Alexander Bailey
- Temerty Faculty of MedicineUniversity of TorontoTorontoOntarioCanada
| | - Julia M. Huntenburg
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Max Planck Institute for Biological CyberneticsTuebingenGermany
| | - Christine L. Tardif
- Department of Biomedical EngineeringMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMontrealQuébecCanada
| | - Arno Villringer
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Center for Stroke Research Berlin (CSB)Charité—Universitätsmedizin BerlinBerlinGermany
- Clinic for Cognitive NeurologyLeipzigGermany
- Leipzig University Medical Centre, IFB Adiposity DiseasesLeipzigGermany
- Collaborative Research Centre 1052‐A5University of LeipzigLeipzigGermany
| | - Claudine J. Gauthier
- Department of Physics/School of HealthConcordia UniversityMontrealQuébecCanada
- Montreal Heart InstituteMontrealQuébecCanada
| | - Vadim Nikulin
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Pierre‐Louis Bazin
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Faculty of Social and Behavioral SciencesUniversity of AmsterdamAmsterdamNetherlands
| | - Christopher J. Steele
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Department of Psychology/School of HealthConcordia UniversityMontrealQuébecCanada
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Srinivasan K, Ribeiro TL, Kells P, Plenz D. The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.26.582056. [PMID: 38464324 PMCID: PMC10925085 DOI: 10.1101/2024.02.26.582056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Scaling relationships characterize complex systems at criticality. In the brain, these relationships are evident in scale-invariant activity cascades, so-called neuronal avalanches, quantified by power laws in avalanche size and duration. At the cellular level, neuronal avalanches are identified in spatially distributed groups of neurons that participate in cascades of coincident action potential firing. Such spatiotemporal synchronization is central to theories on brain function, yet scaling relationships in avalanche synchronization have been challenging to study when only a fraction of neurons is observed, underestimating avalanche properties. Here, we study these biases from fractional sampling in an all-to-all, balanced network of excitatory and inhibitory neurons with critical branching process dynamics. We focus on the growth of mean avalanche size with avalanche duration. For parabolic avalanches, this growth is quadratic, quantified by the scaling exponent, χ = 2 , which signifies rapid spatial expansion of coincident firing within a relatively short period of time. In contrast, χ < < 2 for fractionally sampled networks. We show that temporal coarse-graining combined with a threshold for the minimally required coincident firing in the network recovers χ = 2 , even when sampling as few as 0.1% of the neurons. In contrast, a commonly proposed 'crackling noise' approach fails to recover χ under those conditions. Our approach robustly identifies χ = 2 for ongoing neuronal activity in frontal cortex of awake mice using cellular 2-photon imaging. Our findings demonstrate how to correct scaling bias from fractional sampling and identifies rapid, scale-invariant synchronization of cell assemblies in the brain.
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Affiliation(s)
- Keshav Srinivasan
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Tiago L. Ribeiro
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Patrick Kells
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Dietmar Plenz
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD 20892, USA
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8
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Shirani F, Choi H. On the physiological and structural contributors to the overall balance of excitation and inhibition in local cortical networks. J Comput Neurosci 2024; 52:73-107. [PMID: 37837534 DOI: 10.1007/s10827-023-00863-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/25/2023] [Accepted: 09/08/2023] [Indexed: 10/16/2023]
Abstract
Overall balance of excitation and inhibition in cortical networks is central to their functionality and normal operation. Such orchestrated co-evolution of excitation and inhibition is established through convoluted local interactions between neurons, which are organized by specific network connectivity structures and are dynamically controlled by modulating synaptic activities. Therefore, identifying how such structural and physiological factors contribute to establishment of overall balance of excitation and inhibition is crucial in understanding the homeostatic plasticity mechanisms that regulate the balance. We use biologically plausible mathematical models to extensively study the effects of multiple key factors on overall balance of a network. We characterize a network's baseline balanced state by certain functional properties, and demonstrate how variations in physiological and structural parameters of the network deviate this balance and, in particular, result in transitions in spontaneous activity of the network to high-amplitude slow oscillatory regimes. We show that deviations from the reference balanced state can be continuously quantified by measuring the ratio of mean excitatory to mean inhibitory synaptic conductances in the network. Our results suggest that the commonly observed ratio of the number of inhibitory to the number of excitatory neurons in local cortical networks is almost optimal for their stability and excitability. Moreover, the values of inhibitory synaptic decay time constants and density of inhibitory-to-inhibitory network connectivity are critical to overall balance and stability of cortical networks. However, network stability in our results is sufficiently robust against modulations of synaptic quantal conductances, as required by their role in learning and memory. Our study based on extensive bifurcation analyses thus reveal the functional optimality and criticality of structural and physiological parameters in establishing the baseline operating state of local cortical networks.
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Affiliation(s)
- Farshad Shirani
- School of Mathematics, Georgia Institute of Technology, Atlanta, 30332, Georgia, USA.
| | - Hannah Choi
- School of Mathematics, Georgia Institute of Technology, Atlanta, 30332, Georgia, USA
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9
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Xu Y, Schneider A, Wessel R, Hengen KB. Sleep restores an optimal computational regime in cortical networks. Nat Neurosci 2024; 27:328-338. [PMID: 38182837 DOI: 10.1038/s41593-023-01536-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 11/29/2023] [Indexed: 01/07/2024]
Abstract
Sleep is assumed to subserve homeostatic processes in the brain; however, the set point around which sleep tunes circuit computations is unknown. Slow-wave activity (SWA) is commonly used to reflect the homeostatic aspect of sleep; although it can indicate sleep pressure, it does not explain why animals need sleep. This study aimed to assess whether criticality may be the computational set point of sleep. By recording cortical neuron activity continuously for 10-14 d in freely behaving rats, we show that normal waking experience progressively disrupts criticality and that sleep functions to restore critical dynamics. Criticality is perturbed in a context-dependent manner, and waking experience is causal in driving these effects. The degree of deviation from criticality predicts future sleep/wake behavior more accurately than SWA, behavioral history or other neural measures. Our results demonstrate that perturbation and recovery of criticality is a network homeostatic mechanism consistent with the core, restorative function of sleep.
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Affiliation(s)
- Yifan Xu
- Department of Biology, Washington University in St. Louis, St. Louis, MO, USA
| | - Aidan Schneider
- Department of Biology, Washington University in St. Louis, St. Louis, MO, USA
| | - Ralf Wessel
- Department of Physics, Washington University in St. Louis, St. Louis, MO, USA
| | - Keith B Hengen
- Department of Biology, Washington University in St. Louis, St. Louis, MO, USA.
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Liang J, Yang Z, Zhou C. Excitation-Inhibition Balance, Neural Criticality, and Activities in Neuronal Circuits. Neuroscientist 2024:10738584231221766. [PMID: 38291889 DOI: 10.1177/10738584231221766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Neural activities in local circuits exhibit complex and multilevel dynamic features. Individual neurons spike irregularly, which is believed to originate from receiving balanced amounts of excitatory and inhibitory inputs, known as the excitation-inhibition balance. The spatial-temporal cascades of clustered neuronal spikes occur in variable sizes and durations, manifested as neural avalanches with scale-free features. These may be explained by the neural criticality hypothesis, which posits that neural systems operate around the transition between distinct dynamic states. Here, we summarize the experimental evidence for and the underlying theory of excitation-inhibition balance and neural criticality. Furthermore, we review recent studies of excitatory-inhibitory networks with synaptic kinetics as a simple solution to reconcile these two apparently distinct theories in a single circuit model. This provides a more unified understanding of multilevel neural activities in local circuits, from spontaneous to stimulus-response dynamics.
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Affiliation(s)
- Junhao Liang
- Eberhard Karls University of Tübingen and Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Zhuda Yang
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
- Life Science Imaging Centre, Hong Kong Baptist University, Kowloon Tong, Hong Kong
- Research Centre, Hong Kong Baptist University Institute of Research and Continuing Education, Shenzhen, China
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11
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Ruffini G, Lopez-Sola E, Vohryzek J, Sanchez-Todo R. Neural Geometrodynamics, Complexity, and Plasticity: A Psychedelics Perspective. ENTROPY (BASEL, SWITZERLAND) 2024; 26:90. [PMID: 38275498 PMCID: PMC11154528 DOI: 10.3390/e26010090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/14/2024] [Accepted: 01/17/2024] [Indexed: 01/27/2024]
Abstract
We explore the intersection of neural dynamics and the effects of psychedelics in light of distinct timescales in a framework integrating concepts from dynamics, complexity, and plasticity. We call this framework neural geometrodynamics for its parallels with general relativity's description of the interplay of spacetime and matter. The geometry of trajectories within the dynamical landscape of "fast time" dynamics are shaped by the structure of a differential equation and its connectivity parameters, which themselves evolve over "slow time" driven by state-dependent and state-independent plasticity mechanisms. Finally, the adjustment of plasticity processes (metaplasticity) takes place in an "ultraslow" time scale. Psychedelics flatten the neural landscape, leading to heightened entropy and complexity of neural dynamics, as observed in neuroimaging and modeling studies linking increases in complexity with a disruption of functional integration. We highlight the relationship between criticality, the complexity of fast neural dynamics, and synaptic plasticity. Pathological, rigid, or "canalized" neural dynamics result in an ultrastable confined repertoire, allowing slower plastic changes to consolidate them further. However, under the influence of psychedelics, the destabilizing emergence of complex dynamics leads to a more fluid and adaptable neural state in a process that is amplified by the plasticity-enhancing effects of psychedelics. This shift manifests as an acute systemic increase of disorder and a possibly longer-lasting increase in complexity affecting both short-term dynamics and long-term plastic processes. Our framework offers a holistic perspective on the acute effects of these substances and their potential long-term impacts on neural structure and function.
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Affiliation(s)
- Giulio Ruffini
- Brain Modeling Department, Neuroelectrics, 08035 Barcelona, Spain; (E.L.-S.); (R.S.-T.)
| | - Edmundo Lopez-Sola
- Brain Modeling Department, Neuroelectrics, 08035 Barcelona, Spain; (E.L.-S.); (R.S.-T.)
- Computational Neuroscience Group, Universitat Pompeu Fabra, 08018 Barcelona, Spain;
| | - Jakub Vohryzek
- Computational Neuroscience Group, Universitat Pompeu Fabra, 08018 Barcelona, Spain;
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford OX3 9BX, UK
| | - Roser Sanchez-Todo
- Brain Modeling Department, Neuroelectrics, 08035 Barcelona, Spain; (E.L.-S.); (R.S.-T.)
- Computational Neuroscience Group, Universitat Pompeu Fabra, 08018 Barcelona, Spain;
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12
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Bottorff J, Padgett S, Turrigiano GG. Basal forebrain cholinergic activity is necessary for upward firing rate homeostasis in the rodent visual cortex. Proc Natl Acad Sci U S A 2024; 121:e2317987121. [PMID: 38147559 PMCID: PMC10769829 DOI: 10.1073/pnas.2317987121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 11/22/2023] [Indexed: 12/28/2023] Open
Abstract
Bidirectional homeostatic plasticity allows neurons and circuits to maintain stable firing in the face of developmental or learning-induced perturbations. In the primary visual cortex (V1), upward firing rate homeostasis (FRH) only occurs during active wake (AW) and downward during sleep, but how this behavioral state-dependent gating is accomplished is unknown. Here, we focus on how AW enables upward FRH in V1 of juvenile Long Evans rats. A major difference between quiet wake (QW), when upward FRH is absent, and AW, when it is present, is increased cholinergic (ACh) tone, and the main cholinergic projections to V1 arise from the horizontal diagonal band of the basal forebrain (HDB ACh). We therefore chemogenetically inhibited HDB ACh neurons while inducing upward homeostatic compensation using direct activity-suppression in V1. We found that synaptic scaling up and intrinsic homeostatic plasticity, two important cellular mediators of upward FRH, were both impaired when HDB ACh neurons were inhibited. Most strikingly, HDB ACh inhibition flipped the sign of intrinsic plasticity so that it became anti-homeostatic, and this effect was phenocopied by knockdown of the M1 ACh receptor in V1, indicating that this modulation of intrinsic plasticity is the result of direct actions of ACh within V1. Finally, we found that upward FRH induced by visual deprivation was completely prevented by HDB ACh inhibition. Together, our results show that HDB ACh modulation is a key enabler of upward homeostatic plasticity and FRH, and more broadly suggest that neuromodulatory inputs can segregate upward and downward homeostatic plasticity into distinct behavioral states.
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Affiliation(s)
- Juliet Bottorff
- Department of Biology and Neuroscience Program, Brandeis University, Waltham, MA02453
| | - Sydney Padgett
- Department of Biology and Neuroscience Program, Brandeis University, Waltham, MA02453
| | - Gina G. Turrigiano
- Department of Biology and Neuroscience Program, Brandeis University, Waltham, MA02453
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13
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Hutt A, Trotter D, Pariz A, Valiante TA, Lefebvre J. Diversity-induced trivialization and resilience of neural dynamics. CHAOS (WOODBURY, N.Y.) 2024; 34:013147. [PMID: 38285722 DOI: 10.1063/5.0165773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 01/01/2024] [Indexed: 01/31/2024]
Abstract
Heterogeneity is omnipresent across all living systems. Diversity enriches the dynamical repertoire of these systems but remains challenging to reconcile with their manifest robustness and dynamical persistence over time, a fundamental feature called resilience. To better understand the mechanism underlying resilience in neural circuits, we considered a nonlinear network model, extracting the relationship between excitability heterogeneity and resilience. To measure resilience, we quantified the number of stationary states of this network, and how they are affected by various control parameters. We analyzed both analytically and numerically gradient and non-gradient systems modeled as non-linear sparse neural networks evolving over long time scales. Our analysis shows that neuronal heterogeneity quenches the number of stationary states while decreasing the susceptibility to bifurcations: a phenomenon known as trivialization. Heterogeneity was found to implement a homeostatic control mechanism enhancing network resilience to changes in network size and connection probability by quenching the system's dynamic volatility.
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Affiliation(s)
- Axel Hutt
- MLMS, MIMESIS, Université de Strasbourg, CNRS, Inria, ICube, 67000 Strasbourg, France
| | - Daniel Trotter
- Department of Physics, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
- Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 0S8, Canada
| | - Aref Pariz
- Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 0S8, Canada
- Department of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
| | - Taufik A Valiante
- Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 0S8, Canada
- Department of Electrical and Computer Engineering, Institute of Medical Science, Institute of Biomedical Engineering, Division of Neurosurgery, Department of Surgery, CRANIA (Center for Advancing Neurotechnological Innovation to Application), Max Planck-University of Toronto Center for Neural Science and Technology, University of Toronto, Toronto, Ontario M5S 3G8, Canada
| | - Jérémie Lefebvre
- Department of Physics, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
- Krembil Brain Institute, University Health Network, Toronto, Ontario M5T 0S8, Canada
- Department of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
- Department of Mathematics, University of Toronto, Toronto, Ontario M5S 2E4, Canada
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14
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van der Molen T, Spaeth A, Chini M, Bartram J, Dendukuri A, Zhang Z, Bhaskaran-Nair K, Blauvelt LJ, Petzold LR, Hansma PK, Teodorescu M, Hierlemann A, Hengen KB, Hanganu-Opatz IL, Kosik KS, Sharf T. Protosequences in human cortical organoids model intrinsic states in the developing cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.29.573646. [PMID: 38234832 PMCID: PMC10793448 DOI: 10.1101/2023.12.29.573646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development.
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Affiliation(s)
- Tjitse van der Molen
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA 93106, USA
- Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Alex Spaeth
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Mattia Chini
- Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Julian Bartram
- Department of Biosystems Science and Engineering, ETH Zürich, Klingelbergstrasse 48, 4056 Basel, Switzerland
| | - Aditya Dendukuri
- Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Zongren Zhang
- Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106
| | - Kiran Bhaskaran-Nair
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Lon J. Blauvelt
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
| | - Linda R. Petzold
- Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Paul K. Hansma
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA 93106, USA
- Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106
| | - Mircea Teodorescu
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zürich, Klingelbergstrasse 48, 4056 Basel, Switzerland
| | - Keith B. Hengen
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Ileana L. Hanganu-Opatz
- Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Kenneth S. Kosik
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA 93106, USA
- Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA 93106, USA
| | - Tal Sharf
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
- Institute for the Biology of Stem Cells, University of California Santa Cruz, Santa Cruz, CA 95064, USA
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15
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Vazquez-Juarez E, Srivastava I, Lindskog M. The effect of ketamine on synaptic mistuning induced by impaired glutamate reuptake. Neuropsychopharmacology 2023; 48:1859-1868. [PMID: 37301901 PMCID: PMC10584870 DOI: 10.1038/s41386-023-01617-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 05/05/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023]
Abstract
Mistuning of synaptic transmission has been proposed to underlie many psychiatric disorders, with decreased reuptake of the excitatory neurotransmitter glutamate as one contributing factor. Synaptic tuning occurs through several diverging and converging forms of plasticity. By recording evoked field postsynaptic potentials in the CA1 area in hippocampal slices, we found that inhibiting glutamate transporters using DL-TBOA causes retuning of synaptic transmission, resulting in a new steady state with reduced synaptic strength and a lower threshold for inducing long-term synaptic potentiation (LTP). Moreover, a similar reduced threshold for LTP was observed in a rat model of depression with decreased levels of glutamate transporters. Most importantly, we found that the antidepressant ketamine counteracts the effects of increased glutamate on the various steps involved in synaptic retuning. We, therefore, propose that ketamine's mechanism of action as an antidepressant is to restore adequate synaptic tuning.
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Affiliation(s)
- Erika Vazquez-Juarez
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Ipsit Srivastava
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 77, Stockholm, Sweden
- Department of Medical Cell Biology, Uppsala University, 751 24, Uppsala, Sweden
| | - Maria Lindskog
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 171 77, Stockholm, Sweden.
- Department of Medical Cell Biology, Uppsala University, 751 24, Uppsala, Sweden.
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16
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Hadeiy SK, Habtemariam S, Shankayi Z, Shahyad S, Sahraei H, Asghardoust Rezaei M, Bahrami F. Amelioration of pain and anxiety in sleep-deprived rats by intra-amygdala injection of cinnamaldehyde. Sleep Med X 2023. [DOI: 10.1016/j.sleepx.2023.100069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/03/2023] Open
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17
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Radulescu CI, Doostdar N, Zabouri N, Melgosa-Ecenarro L, Wang X, Sadeh S, Pavlidi P, Airey J, Kopanitsa M, Clopath C, Barnes SJ. Age-related dysregulation of homeostatic control in neuronal microcircuits. Nat Neurosci 2023; 26:2158-2170. [PMID: 37919424 PMCID: PMC10689243 DOI: 10.1038/s41593-023-01451-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 09/06/2023] [Indexed: 11/04/2023]
Abstract
Neuronal homeostasis prevents hyperactivity and hypoactivity. Age-related hyperactivity suggests homeostasis may be dysregulated in later life. However, plasticity mechanisms preventing age-related hyperactivity and their efficacy in later life are unclear. We identify the adult cortical plasticity response to elevated activity driven by sensory overstimulation, then test how plasticity changes with age. We use in vivo two-photon imaging of calcium-mediated cellular/synaptic activity, electrophysiology and c-Fos-activity tagging to show control of neuronal activity is dysregulated in the visual cortex in late adulthood. Specifically, in young adult cortex, mGluR5-dependent population-wide excitatory synaptic weakening and inhibitory synaptogenesis reduce cortical activity following overstimulation. In later life, these mechanisms are downregulated, so that overstimulation results in synaptic strengthening and elevated activity. We also find overstimulation disrupts cognition in older but not younger animals. We propose that specific plasticity mechanisms fail in later life dysregulating neuronal microcircuit homeostasis and that the age-related response to overstimulation can impact cognitive performance.
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Affiliation(s)
- Carola I Radulescu
- UK Dementia Research Institute, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, London, UK
| | - Nazanin Doostdar
- UK Dementia Research Institute, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, London, UK
| | - Nawal Zabouri
- Department of Biomedical Engineering, Imperial College London, South Kensington Campus, London, UK
| | - Leire Melgosa-Ecenarro
- UK Dementia Research Institute, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, London, UK
| | - Xingjian Wang
- UK Dementia Research Institute, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, London, UK
| | - Sadra Sadeh
- Department of Biomedical Engineering, Imperial College London, South Kensington Campus, London, UK
- Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, London, UK
| | - Pavlina Pavlidi
- UK Dementia Research Institute, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, London, UK
- Department of Pharmacology, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Joe Airey
- UK Dementia Research Institute, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, London, UK
| | | | - Claudia Clopath
- Department of Biomedical Engineering, Imperial College London, South Kensington Campus, London, UK
| | - Samuel J Barnes
- UK Dementia Research Institute, Department of Brain Sciences, Imperial College London, Hammersmith Hospital Campus, London, UK.
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18
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Rubinov M. Circular and unified analysis in network neuroscience. eLife 2023; 12:e79559. [PMID: 38014843 PMCID: PMC10684154 DOI: 10.7554/elife.79559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 10/18/2023] [Indexed: 11/29/2023] Open
Abstract
Genuinely new discovery transcends existing knowledge. Despite this, many analyses in systems neuroscience neglect to test new speculative hypotheses against benchmark empirical facts. Some of these analyses inadvertently use circular reasoning to present existing knowledge as new discovery. Here, I discuss that this problem can confound key results and estimate that it has affected more than three thousand studies in network neuroscience over the last decade. I suggest that future studies can reduce this problem by limiting the use of speculative evidence, integrating existing knowledge into benchmark models, and rigorously testing proposed discoveries against these models. I conclude with a summary of practical challenges and recommendations.
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Affiliation(s)
- Mika Rubinov
- Departments of Biomedical Engineering, Computer Science, and Psychology, Vanderbilt UniversityNashvilleUnited States
- Janelia Research Campus, Howard Hughes Medical InstituteAshburnUnited States
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19
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Kagan BJ, Gyngell C, Lysaght T, Cole VM, Sawai T, Savulescu J. The technology, opportunities, and challenges of Synthetic Biological Intelligence. Biotechnol Adv 2023; 68:108233. [PMID: 37558186 PMCID: PMC7615149 DOI: 10.1016/j.biotechadv.2023.108233] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 07/15/2023] [Accepted: 08/05/2023] [Indexed: 08/11/2023]
Abstract
Integrating neural cultures developed through synthetic biology methods with digital computing has enabled the early development of Synthetic Biological Intelligence (SBI). Recently, key studies have emphasized the advantages of biological neural systems in some information processing tasks. However, neither the technology behind this early development, nor the potential ethical opportunities or challenges, have been explored in detail yet. Here, we review the key aspects that facilitate the development of SBI and explore potential applications. Considering these foreseeable use cases, various ethical implications are proposed. Ultimately, this work aims to provide a robust framework to structure ethical considerations to ensure that SBI technology can be both researched and applied responsibly.
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Affiliation(s)
| | - Christopher Gyngell
- Murdoch Children's Research Institute, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia
| | - Tamra Lysaght
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Victor M Cole
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Tsutomu Sawai
- Graduate School of Humanities and Social Sciences, Hiroshima University, Hiroshima, Japan; Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan
| | - Julian Savulescu
- Murdoch Children's Research Institute, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia; Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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20
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Rabus A, Curic D, Ivan VE, Esteves IM, Gruber AJ, Davidsen J. Changes in functional connectivity preserve scale-free neuronal and behavioral dynamics. Phys Rev E 2023; 108:L052301. [PMID: 38115411 DOI: 10.1103/physreve.108.l052301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 09/06/2023] [Indexed: 12/21/2023]
Abstract
Does the brain optimize itself for storage and transmission of information, and if so, how? The critical brain hypothesis is based in statistical physics and posits that the brain self-tunes its dynamics to a critical point or regime to maximize the repertoire of neuronal responses. Yet, the robustness of this regime, especially with respect to changes in the functional connectivity, remains an unsolved fundamental challenge. Here, we show that both scale-free neuronal dynamics and self-similar features of behavioral dynamics persist following significant changes in functional connectivity. Specifically, we find that the psychedelic compound ibogaine that is associated with an altered state of consciousness fundamentally alters the functional connectivity in the retrosplenial cortex of mice. Yet, the scale-free statistics of movement and of neuronal avalanches among behaviorally related neurons remain largely unaltered. This indicates that the propagation of information within biological neural networks is robust to changes in functional organization of subpopulations of neurons, opening up a new perspective on how the adaptive nature of functional networks may lead to optimality of information transmission in the brain.
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Affiliation(s)
- Anja Rabus
- Complexity Science Group, Department of Physics and Astronomy University of Calgary, Calgary, Alberta, Canada T2N 1N4
| | - Davor Curic
- Complexity Science Group, Department of Physics and Astronomy University of Calgary, Calgary, Alberta, Canada T2N 1N4
| | - Victorita E Ivan
- Canadian Centre for Behavioral Neuroscience University of Lethbridge, Lethbridge, Alberta, Canada T1K 3M4
| | - Ingrid M Esteves
- Canadian Centre for Behavioral Neuroscience University of Lethbridge, Lethbridge, Alberta, Canada T1K 3M4
| | - Aaron J Gruber
- Canadian Centre for Behavioral Neuroscience University of Lethbridge, Lethbridge, Alberta, Canada T1K 3M4
| | - Jörn Davidsen
- Complexity Science Group, Department of Physics and Astronomy University of Calgary, Calgary, Alberta, Canada T2N 1N4
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada T2N 4N1
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21
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Lombardi F, Herrmann HJ, Parrino L, Plenz D, Scarpetta S, Vaudano AE, de Arcangelis L, Shriki O. Beyond pulsed inhibition: Alpha oscillations modulate attenuation and amplification of neural activity in the awake resting state. Cell Rep 2023; 42:113162. [PMID: 37777965 PMCID: PMC10842118 DOI: 10.1016/j.celrep.2023.113162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 06/07/2023] [Accepted: 09/07/2023] [Indexed: 10/03/2023] Open
Abstract
Alpha oscillations are a distinctive feature of the awake resting state of the human brain. However, their functional role in resting-state neuronal dynamics remains poorly understood. Here we show that, during resting wakefulness, alpha oscillations drive an alternation of attenuation and amplification bouts in neural activity. Our analysis indicates that inhibition is activated in pulses that last for a single alpha cycle and gradually suppress neural activity, while excitation is successively enhanced over a few alpha cycles to amplify neural activity. Furthermore, we show that long-term alpha amplitude fluctuations-the "waxing and waning" phenomenon-are an attenuation-amplification mechanism described by a power-law decay of the activity rate in the "waning" phase. Importantly, we do not observe such dynamics during non-rapid eye movement (NREM) sleep with marginal alpha oscillations. The results suggest that alpha oscillations modulate neural activity not only through pulses of inhibition (pulsed inhibition hypothesis) but also by timely enhancement of excitation (or disinhibition).
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Affiliation(s)
- Fabrizio Lombardi
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria; Department of Biomedical Sciences, University of Padova, Via Ugo Bassi 58B, 35131 Padova, Italy.
| | - Hans J Herrmann
- Departamento de Fisica, Universitade Federal do Ceara, Fortaleza 60451-970, Ceara, Brazil; PMMH, ESPCI, 7 quai St. Bernard, 75005 Paris, France
| | - Liborio Parrino
- Sleep Disorders Center, Department of Neurosciences, University of Parma, 43121 Parma, Italy
| | - Dietmar Plenz
- Section on Critical Brain Dynamics, NIH, Bethesda, MD 20892, USA
| | - Silvia Scarpetta
- Department of Physics, University of Salerno, 84084 Fisciano, Italy; INFN sez, Napoli Gr. Coll, 84084 Fisciano, Italy
| | - Anna Elisabetta Vaudano
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, OCB Hospital, 41125 Modena, Italy; Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy
| | - Lucilla de Arcangelis
- Department of Mathematics and Physics, University of Campania "Luigi Vanvitelli", Viale Lincoln 5, 81100 Caserta, Italy.
| | - Oren Shriki
- Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, Beer-sheva, Israel.
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22
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Maschke C, O'Byrne J, Colombo MA, Boly M, Gosseries O, Laureys S, Rosanova M, Jerbi K, Blain-Moraes S. Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.26.564247. [PMID: 37994368 PMCID: PMC10664178 DOI: 10.1101/2023.10.26.564247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigated dynamical properties of the resting-state electroencephalogram of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. We then studied the relation of these dynamic properties with the perturbational complexity index (PCI), which has shown remarkably high sensitivity in detecting consciousness independent of behavior. All participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams)., enabling an experimental dissociation between unresponsiveness and unconsciousness. We estimated (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related measures, and found that states of unconsciousness were characterized by a distancing from both the edge of activity propagation and the edge of chaos. We were then able to predict individual subjects' PCI (i.e., PCImax) with a mean absolute error below 7%. Our results establish a firm link between the PCI and criticality and provide further evidence for the role of criticality in the emergence of consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
| | - Jordan O'Byrne
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada
| | | | - Melanie Boly
- Department of Neurology and Department of Psychiatry, University of Wisconsin, Madison, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du cerveau, CHU of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- CERVO Brain Research Centre, Laval University, Canada
- Consciousness Science Institute, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Karim Jerbi
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada
- Centre UNIQUE (Union Neurosciences & Intelligence Artificielle), Montréal, Québec, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada
- School of Physical and Occupational Therapy, McGill University, Montreal, Canada
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23
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Morrell M, Nemenman I, Sederberg AJ. Neural criticality from effective latent variables. ARXIV 2023:arXiv:2301.00759v3. [PMID: 36713239 PMCID: PMC9882570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Observations of power laws in neural activity data have raised the intriguing notion that brains may operate in a critical state. One example of this critical state is "avalanche criticality," which has been observed in various systems, including cultured neurons, zebrafish, rodent cortex, and human EEG. More recently, power laws were also observed in neural populations in the mouse under an activity coarse-graining procedure, and they were explained as a consequence of the neural activity being coupled to multiple latent dynamical variables. An intriguing possibility is that avalanche criticality emerges due to a similar mechanism. Here, we determine the conditions under which latent dynamical variables give rise to avalanche criticality. We find that populations coupled to multiple latent variables produce critical behavior across a broader parameter range than those coupled to a single, quasi-static latent variable, but in both cases, avalanche criticality is observed without fine-tuning of model parameters. We identify two regimes of avalanches, both critical but differing in the amount of information carried about the latent variable. Our results suggest that avalanche criticality arises in neural systems in which activity is effectively modeled as a population driven by a few dynamical variables and these variables can be inferred from the population activity.
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Affiliation(s)
| | - Ilya Nemenman
- Department of Physics, Department of Biology, Initiative in Theory and Modeling of Living Systems, Emory University
| | - Audrey J. Sederberg
- Department of Neuroscience, University of Minnesota Medical School
- School of Psychology and School of Physics, Georgia Institute of Technology (current)
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24
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Sepúlveda PO, Vera R, Fernández MS, Lobo FA. Linear thinking does not reflect the newer 21st-century anesthesia concepts. A narrative review. J Clin Monit Comput 2023; 37:1133-1144. [PMID: 37129792 DOI: 10.1007/s10877-023-01021-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 04/17/2023] [Indexed: 05/03/2023]
Abstract
The brain constitutes a good example of a chaotic, nonlinear biological system where large neuronal networks operate chaotically with random connectivity. This critical state is significantly affected by the anesthetic loss of consciousness induced by drugs whose pharmacological behavior has been classically based on linear kinetics and dynamics. Recent developments in pharmacology and brain monitoring during anesthesia suggest a different view that we tried to explore in this article. The concepts of effect-site for hypnotic drugs modeling a maximum effect, electroencephalographic dynamics during induction, maintenance, and recovery from anesthesia are discussed, integrated into this alternative view, and how it may be applied in daily clinical practice.
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Affiliation(s)
- Pablo O Sepúlveda
- Hospital Base San José de Osorno, Chile, Universidad Austral de Chile, Osorno, Chile.
| | - Rodrigo Vera
- Ing. Civil Industrial, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - M Silvia Fernández
- Anesthesiology Institute, Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Francisco A Lobo
- Anesthesiology Institute, Cleveland Clinic Abu Dhabi, Abu Dhabi, United Arab Emirates
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25
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McGregor JN, Farris CA, Ensley S, Schneider A, Wang C, Liu Y, Tu J, Elmore H, Ronayne KD, Wessel R, Dyer EL, Bhaskaran-Nair K, Holtzman DM, Hengen KB. Tauopathy severely disrupts homeostatic set-points in emergent neural dynamics but not in the activity of individual neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.01.555947. [PMID: 37732214 PMCID: PMC10508737 DOI: 10.1101/2023.09.01.555947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
The homeostatic regulation of neuronal activity is essential for robust computation; key set-points, such as firing rate, are actively stabilized to compensate for perturbations. From this perspective, the disruption of brain function central to neurodegenerative disease should reflect impairments of computationally essential set-points. Despite connecting neurodegeneration to functional outcomes, the impact of disease on set-points in neuronal activity is unknown. Here we present a comprehensive, theory-driven investigation of the effects of tau-mediated neurodegeneration on homeostatic set-points in neuronal activity. In a mouse model of tauopathy, we examine 27,000 hours of hippocampal recordings during free behavior throughout disease progression. Contrary to our initial hypothesis that tauopathy would impact set-points in spike rate and variance, we found that cell-level set-points are resilient to even the latest stages of disease. Instead, we find that tauopathy disrupts neuronal activity at the network-level, which we quantify using both pairwise measures of neuron interactions as well as measurement of the network's nearness to criticality, an ideal computational regime that is known to be a homeostatic set-point. We find that shifts in network criticality 1) track with symptoms, 2) predict underlying anatomical and molecular pathology, 3) occur in a sleep/wake dependent manner, and 4) can be used to reliably classify an animal's genotype. Our data suggest that the critical set-point is intact, but that homeostatic machinery is progressively incapable of stabilizing hippocampal networks, particularly during waking. This work illustrates how neurodegenerative processes can impact the computational capacity of neurobiological systems, and suggest an important connection between molecular pathology, circuit function, and animal behavior.
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Affiliation(s)
- James N McGregor
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Clayton A Farris
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Sahara Ensley
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Aidan Schneider
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Chao Wang
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer's Disease Research Center, Washington University in Saint Louis, St. Louis, MO, USA
- Institute for Brain Science and Disease, Chongqing Medical University, 400016, Chongqing, China
| | - Yuqi Liu
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Jianhong Tu
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Halla Elmore
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Keenan D Ronayne
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Ralf Wessel
- Department of Physics, Washington University in Saint Louis, St. Louis, MO, USA
| | - Eva L Dyer
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | | | - David M Holtzman
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer's Disease Research Center, Washington University in Saint Louis, St. Louis, MO, USA
| | - Keith B Hengen
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
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26
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Habibollahi F, Kagan BJ, Burkitt AN, French C. Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks. Nat Commun 2023; 14:5287. [PMID: 37648737 PMCID: PMC10469171 DOI: 10.1038/s41467-023-41020-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Accepted: 08/17/2023] [Indexed: 09/01/2023] Open
Abstract
Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of 'Pong' to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition.
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Affiliation(s)
- Forough Habibollahi
- Cortical Labs Pty Ltd, Melbourne, 3056, VIC, Australia
- Biomedical Engineering Department, University of Melbourne, Parkville, 3010, VIC, Australia
- Neural Dynamics Laboratory, Department of Medicine, University of Melbourne, Parkville, 3010, VIC, Australia
| | - Brett J Kagan
- Cortical Labs Pty Ltd, Melbourne, 3056, VIC, Australia.
| | - Anthony N Burkitt
- Biomedical Engineering Department, University of Melbourne, Parkville, 3010, VIC, Australia
| | - Chris French
- Neural Dynamics Laboratory, Department of Medicine, University of Melbourne, Parkville, 3010, VIC, Australia
- Neurology Department, Royal Melbourne Hospital, Melbourne, Australia
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27
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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] [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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28
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Meyer CT, Kralj JM. Cell-autonomous diversification in bacteria arises from calcium dynamics self-organizing at a critical point. SCIENCE ADVANCES 2023; 9:eadg3028. [PMID: 37540744 PMCID: PMC10403213 DOI: 10.1126/sciadv.adg3028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 07/03/2023] [Indexed: 08/06/2023]
Abstract
How dynamic bacterial calcium is regulated, with kinetics faster than typical mechanisms of cellular adaptation, is unknown. We discover bacterial calcium fluctuations are temporal-fractals resulting from a property known as self-organized criticality (SOC). SOC processes are poised at a phase transition separating ordered and chaotic dynamical regimes and are observed in many natural and anthropogenic systems. SOC in bacterial calcium emerges due to calcium channel coupling mediated via membrane voltage. Environmental or genetic perturbations modify calcium dynamics and the critical exponent suggesting a continuum of critical attractors. Moving along this continuum alters the collective information capacity of bacterial populations. We find that the stochastic transition from motile to sessile lifestyle is partially mediated by SOC-governed calcium fluctuations through the regulation of c-di-GMP. In summary, bacteria co-opt the physics of phase transitions to maintain dynamic calcium equilibrium, and this enables cell-autonomous population diversification during surface colonization by leveraging the stochasticity inherent at a boundary between phases.
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29
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Fontenele AJ, Sooter JS, Norman VK, Gautam SH, Shew WL. Low dimensional criticality embedded in high dimensional awake brain dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.05.522896. [PMID: 37546833 PMCID: PMC10401950 DOI: 10.1101/2023.01.05.522896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Whether cortical neurons operate in a strongly or weakly correlated dynamical regime determines fundamental information processing capabilities and has fueled decades of debate. Here we offer a resolution of this debate; we show that two important dynamical regimes, typically considered incompatible, can coexist in the same local cortical circuit by separating them into two different subspaces. In awake mouse motor cortex, we find a low-dimensional subspace with large fluctuations consistent with criticality - a dynamical regime with moderate correlations and multi-scale information capacity and transmission. Orthogonal to this critical subspace, we find a high-dimensional subspace containing a desynchronized dynamical regime, which may optimize input discrimination. The critical subspace is apparent only at long timescales, which explains discrepancies among some previous studies. Using a computational model, we show that the emergence of a low-dimensional critical subspace at large timescale agrees with established theory of critical dynamics. Our results suggest that cortex leverages its high dimensionality to multiplex dynamical regimes across different subspaces.
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Affiliation(s)
- Antonio J. Fontenele
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - J. Samuel Sooter
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - V. Kindler Norman
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - Shree Hari Gautam
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - Woodrow L. Shew
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
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30
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Hutt A, Rich S, Valiante TA, Lefebvre J. Intrinsic neural diversity quenches the dynamic volatility of neural networks. Proc Natl Acad Sci U S A 2023; 120:e2218841120. [PMID: 37399421 PMCID: PMC10334753 DOI: 10.1073/pnas.2218841120] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 05/19/2023] [Indexed: 07/05/2023] Open
Abstract
Heterogeneity is the norm in biology. The brain is no different: Neuronal cell types are myriad, reflected through their cellular morphology, type, excitability, connectivity motifs, and ion channel distributions. While this biophysical diversity enriches neural systems' dynamical repertoire, it remains challenging to reconcile with the robustness and persistence of brain function over time (resilience). To better understand the relationship between excitability heterogeneity (variability in excitability within a population of neurons) and resilience, we analyzed both analytically and numerically a nonlinear sparse neural network with balanced excitatory and inhibitory connections evolving over long time scales. Homogeneous networks demonstrated increases in excitability, and strong firing rate correlations-signs of instability-in response to a slowly varying modulatory fluctuation. Excitability heterogeneity tuned network stability in a context-dependent way by restraining responses to modulatory challenges and limiting firing rate correlations, while enriching dynamics during states of low modulatory drive. Excitability heterogeneity was found to implement a homeostatic control mechanism enhancing network resilience to changes in population size, connection probability, strength and variability of synaptic weights, by quenching the volatility (i.e., its susceptibility to critical transitions) of its dynamics. Together, these results highlight the fundamental role played by cell-to-cell heterogeneity in the robustness of brain function in the face of change.
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Affiliation(s)
- Axel Hutt
- Université de Strasbourg, CNRS, Inria, ICube, MLMS, MIMESIS, StrasbourgF-67000, France
| | - Scott Rich
- Krembil Brain Institute, Division of Clinical and Computational Neuroscience, University Health Network, Toronto, ONM5T 0S8, Canada
| | - Taufik A. Valiante
- Krembil Brain Institute, Division of Clinical and Computational Neuroscience, University Health Network, Toronto, ONM5T 0S8, Canada
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ONM5S 3G8, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, ONM5S 3G9, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ONM5S 1A8, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ONM5G 2C4, Canada
- Center for Advancing Neurotechnological Innovation to Application, University of Toronto, Toronto, ONM5G 2A2, Canada
- Max Planck-University of Toronto Center for Neural Science and Technology, University of Toronto, Toronto, ONM5S 3G8, Canada
| | - Jérémie Lefebvre
- Krembil Brain Institute, Division of Clinical and Computational Neuroscience, University Health Network, Toronto, ONM5T 0S8, Canada
- Department of Biology, University of Ottawa, Ottawa, ONK1N 6N5, Canada
- Department of Mathematics, University of Toronto, Toronto, ONM5S 2E4, Canada
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31
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Páscoa Dos Santos F, Vohryzek J, Verschure PFMJ. Multiscale effects of excitatory-inhibitory homeostasis in lesioned cortical networks: A computational study. PLoS Comput Biol 2023; 19:e1011279. [PMID: 37418506 DOI: 10.1371/journal.pcbi.1011279] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 06/18/2023] [Indexed: 07/09/2023] Open
Abstract
Stroke-related disruptions in functional connectivity (FC) often spread beyond lesioned areas and, given the localized nature of lesions, it is unclear how the recovery of FC is orchestrated on a global scale. Since recovery is accompanied by long-term changes in excitability, we propose excitatory-inhibitory (E-I) homeostasis as a driving mechanism. We present a large-scale model of the neocortex, with synaptic scaling of local inhibition, showing how E-I homeostasis can drive the post-lesion restoration of FC and linking it to changes in excitability. We show that functional networks could reorganize to recover disrupted modularity and small-worldness, but not network dynamics, suggesting the need to consider forms of plasticity beyond synaptic scaling of inhibition. On average, we observed widespread increases in excitability, with the emergence of complex lesion-dependent patterns related to biomarkers of relevant side effects of stroke, such as epilepsy, depression and chronic pain. In summary, our results show that the effects of E-I homeostasis extend beyond local E-I balance, driving the restoration of global properties of FC, and relating to post-stroke symptomatology. Therefore, we suggest the framework of E-I homeostasis as a relevant theoretical foundation for the study of stroke recovery and for understanding the emergence of meaningful features of FC from local dynamics.
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Affiliation(s)
- Francisco Páscoa Dos Santos
- Eodyne Systems SL, Barcelona, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Jakub Vohryzek
- Centre for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, United Kingdom
| | - Paul F M J Verschure
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
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32
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Nir Y, de Lecea L. Sleep and vigilance states: Embracing spatiotemporal dynamics. Neuron 2023; 111:1998-2011. [PMID: 37148873 DOI: 10.1016/j.neuron.2023.04.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 02/08/2023] [Accepted: 04/12/2023] [Indexed: 05/08/2023]
Abstract
The classic view of sleep and vigilance states is a global stationary perspective driven by the interaction between neuromodulators and thalamocortical systems. However, recent data are challenging this view by demonstrating that vigilance states are highly dynamic and regionally complex. Spatially, sleep- and wake-like states often co-occur across distinct brain regions, as in unihemispheric sleep, local sleep in wakefulness, and during development. Temporally, dynamic switching prevails around state transitions, during extended wakefulness, and in fragmented sleep. This knowledge, together with methods monitoring brain activity across multiple regions simultaneously at millisecond resolution with cell-type specificity, is rapidly shifting how we consider vigilance states. A new perspective incorporating multiple spatial and temporal scales may have important implications for considering the governing neuromodulatory mechanisms, the functional roles of vigilance states, and their behavioral manifestations. A modular and dynamic view highlights novel avenues for finer spatiotemporal interventions to improve sleep function.
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Affiliation(s)
- Yuval Nir
- Department of Physiology and Pharmacology, Faculty of Medicine, Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel; Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel; Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv 69978, Israel; The Sieratzki-Sagol Center for Sleep Medicine, Tel-Aviv Sourasky Medical Center, Tel-Aviv 64239, Israel.
| | - Luis de Lecea
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.
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33
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Yamada T, Watanabe T, Sasaki Y. Are sleep disturbances a cause or consequence of autism spectrum disorder? Psychiatry Clin Neurosci 2023; 77:377-385. [PMID: 36949621 PMCID: PMC10871071 DOI: 10.1111/pcn.13550] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 03/10/2023] [Accepted: 03/17/2023] [Indexed: 03/24/2023]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by core symptoms such as atypical social communication, stereotyped behaviors, and restricted interests. One of the comorbid symptoms of individuals with ASD is sleep disturbance. There are two major hypotheses regarding the neural mechanism underlying ASD, i.e., the excitation/inhibition (E/I) imbalance and the altered neuroplasticity hypotheses. However, the pathology of ASD remains unclear due to inconsistent research results. This paper argues that sleep is a confounding factor, thus, must be considered when examining the pathology of ASD because sleep plays an important role in modulating the E/I balance and neuroplasticity in the human brain. Investigation of the E/I balance and neuroplasticity during sleep might enhance our understanding of the neural mechanisms of ASD. It may also lead to the development of neurobiologically informed interventions to supplement existing psychosocial therapies.
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Affiliation(s)
- Takashi Yamada
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, 02912, USA
| | - Takeo Watanabe
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, 02912, USA
| | - Yuka Sasaki
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, 02912, USA
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34
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Liu S, Li F, Wan F. Distance to Criticality Undergoes Critical Transition Before Epileptic Seizure Attacks. Brain Res Bull 2023:110684. [PMID: 37353038 DOI: 10.1016/j.brainresbull.2023.110684] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 06/03/2023] [Accepted: 06/10/2023] [Indexed: 06/25/2023]
Abstract
Epilepsy is a common neurological disorder characterized by recurring seizures, but its underlying mechanisms remain poorly understood. Despite extensive research, there are still gaps in our knowledge about the relationship between brain dynamics and seizures. In this study, our aim is to address these gaps by proposing a novel approach to assess the role of brain network dynamics in the onset of seizures. Specifically, we investigate the relationship between brain dynamics and seizures by tracking the distance to criticality. Our hypothesis is that this distance plays a crucial role in brain state changes and that seizures may be related to critical transitions of this distance. To test this hypothesis, we develop a method to measure the evolution of the brain network's distance to the critical dynamic systems (i.e., the distance to the tipping point, DTP) using dynamic network biomarker theory and random matrix theory. The results show that the DTP of the brain decreases significantly immediately after onset of an epileptic seizure, suggesting that the brain loses its well-defined quasi-critical state during seizures. We refer to this phenomenon as the "criticality of the criticality" (COC). Furthermore, we observe that DTP exhibits a shape transition before and after the onset of the seizures. This phenomenon suggests the possibility of early warning signal (EWS) identification in the dynamic sequence of DTP, which could be utilized for seizure prediction. Our results show that the Hurst exponent, skewness, kurtosis, autocorrelation, and variance of the DTP sequence are potential EWS features. This study advances our understanding of the relationship between brain dynamics and seizures and highlights the potential for using criticality-based measures to predict and prevent seizures.
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Affiliation(s)
- Shun Liu
- The Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau; The Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau; The Centre for Artificial Intelligence and Robotics, Institute of Collaborative Innovation, University of Macau, Macau
| | - Fali Li
- The Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau; The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuro-information, University of Electronic Science and Technology of China, Chengdu, China; School of Life Science and Technology, the Center for Information in Bio-Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Feng Wan
- The Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau; The Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau; The Centre for Artificial Intelligence and Robotics, Institute of Collaborative Innovation, University of Macau, Macau.
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35
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Gillon CJ, Lecoq JA, Pina JE, Ahmed R, Billeh YN, Caldejon S, Groblewski P, Henley TM, Kato I, Lee E, Luviano J, Mace K, Nayan C, Nguyen TV, North K, Perkins J, Seid S, Valley MT, Williford A, Bengio Y, Lillicrap TP, Zylberberg J, Richards BA. Responses of pyramidal cell somata and apical dendrites in mouse visual cortex over multiple days. Sci Data 2023; 10:287. [PMID: 37198203 DOI: 10.1038/s41597-023-02214-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 05/05/2023] [Indexed: 05/19/2023] Open
Abstract
The apical dendrites of pyramidal neurons in sensory cortex receive primarily top-down signals from associative and motor regions, while cell bodies and nearby dendrites are heavily targeted by locally recurrent or bottom-up inputs from the sensory periphery. Based on these differences, a number of theories in computational neuroscience postulate a unique role for apical dendrites in learning. However, due to technical challenges in data collection, little data is available for comparing the responses of apical dendrites to cell bodies over multiple days. Here we present a dataset collected through the Allen Institute Mindscope's OpenScope program that addresses this need. This dataset comprises high-quality two-photon calcium imaging from the apical dendrites and the cell bodies of visual cortical pyramidal neurons, acquired over multiple days in awake, behaving mice that were presented with visual stimuli. Many of the cell bodies and dendrite segments were tracked over days, enabling analyses of how their responses change over time. This dataset allows neuroscientists to explore the differences between apical and somatic processing and plasticity.
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Affiliation(s)
- Colleen J Gillon
- Department of Cell & Systems Biology, University of Toronto, Toronto, Ontario, Canada
- Department of Biological Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada
- Mila, Montréal, Québec, Canada
| | | | - Jason E Pina
- Department of Physics and Astronomy, York University, Toronto, Ontario, Canada
- Centre for Vision Research, York University, Toronto, Ontario, Canada
| | - Ruweida Ahmed
- Allen Institute, MindScope Program, Seattle, WA, USA
| | | | | | | | - Timothy M Henley
- Department of Physics and Astronomy, York University, Toronto, Ontario, Canada
- Centre for Vision Research, York University, Toronto, Ontario, Canada
| | - India Kato
- Allen Institute, MindScope Program, Seattle, WA, USA
| | - Eric Lee
- Allen Institute, MindScope Program, Seattle, WA, USA
| | | | - Kyla Mace
- Allen Institute, MindScope Program, Seattle, WA, USA
| | - Chelsea Nayan
- Allen Institute, MindScope Program, Seattle, WA, USA
| | | | - Kat North
- Allen Institute, MindScope Program, Seattle, WA, USA
| | - Jed Perkins
- Allen Institute, MindScope Program, Seattle, WA, USA
| | - Sam Seid
- Allen Institute, MindScope Program, Seattle, WA, USA
| | | | - Ali Williford
- Allen Institute, MindScope Program, Seattle, WA, USA
| | - Yoshua Bengio
- Mila, Montréal, Québec, Canada
- Département d'informatique et de recherche opérationnelle, Université de Montréal, Montréal, Québec, Canada
- Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada
| | - Timothy P Lillicrap
- DeepMind, Inc, London, UK
- Centre for Computation, Mathematics and Physics in the Life Sciences and Experimental Biology, University College London, London, UK
| | - Joel Zylberberg
- Department of Physics and Astronomy, York University, Toronto, Ontario, Canada.
- Centre for Vision Research, York University, Toronto, Ontario, Canada.
- Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada.
- Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada.
| | - Blake A Richards
- Mila, Montréal, Québec, Canada.
- Learning in Machines and Brains Program, Canadian Institute for Advanced Research, Toronto, Ontario, Canada.
- School of Computer Science, McGill University, Montréal, Québec, Canada.
- Department of Neurology & Neurosurgery, McGill University, Montréal, Québec, Canada.
- Montreal Neurological Institute, McGill University, Montréal, Québec, Canada.
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36
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Nanda A, Johnson GW, Mu Y, Ahrens MB, Chang C, Englot DJ, Breakspear M, Rubinov M. Time-resolved correlation of distributed brain activity tracks E-I balance and accounts for diverse scale-free phenomena. Cell Rep 2023; 42:112254. [PMID: 36966391 PMCID: PMC10518034 DOI: 10.1016/j.celrep.2023.112254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 12/22/2022] [Accepted: 02/28/2023] [Indexed: 03/27/2023] Open
Abstract
Much of systems neuroscience posits the functional importance of brain activity patterns that lack natural scales of sizes, durations, or frequencies. The field has developed prominent, and sometimes competing, explanations for the nature of this scale-free activity. Here, we reconcile these explanations across species and modalities. First, we link estimates of excitation-inhibition (E-I) balance with time-resolved correlation of distributed brain activity. Second, we develop an unbiased method for sampling time series constrained by this time-resolved correlation. Third, we use this method to show that estimates of E-I balance account for diverse scale-free phenomena without need to attribute additional function or importance to these phenomena. Collectively, our results simplify existing explanations of scale-free brain activity and provide stringent tests on future theories that seek to transcend these explanations.
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Affiliation(s)
- Aditya Nanda
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA.
| | - Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Yu Mu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Misha B Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Catie Chang
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA; Department of Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA; Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Michael Breakspear
- School of Psychology, University of Newcastle, Callaghan, NSW 2308, Australia; School of Medicine and Public Health, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Mikail Rubinov
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA; Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; Department of Computer Science, Vanderbilt University, Nashville, TN 37235, USA.
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37
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Schneider A, Azabou M, McDougall-Vigier L, Parks DF, Ensley S, Bhaskaran-Nair K, Nowakowski T, Dyer EL, Hengen KB. Transcriptomic cell type structures in vivo neuronal activity across multiple timescales. Cell Rep 2023; 42:112318. [PMID: 36995938 PMCID: PMC10539488 DOI: 10.1016/j.celrep.2023.112318] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 02/04/2023] [Accepted: 03/15/2023] [Indexed: 03/30/2023] Open
Abstract
Cell type is hypothesized to be a key determinant of a neuron's role within a circuit. Here, we examine whether a neuron's transcriptomic type influences the timing of its activity. We develop a deep-learning architecture that learns features of interevent intervals across timescales (ms to >30 min). We show that transcriptomic cell-class information is embedded in the timing of single neuron activity in the intact brain of behaving animals (calcium imaging and extracellular electrophysiology) as well as in a bio-realistic model of the visual cortex. Further, a subset of excitatory cell types are distinguishable but can be classified with higher accuracy when considering cortical layer and projection class. Finally, we show that computational fingerprints of cell types may be universalizable across structured stimuli and naturalistic movies. Our results indicate that transcriptomic class and type may be imprinted in the timing of single neuron activity across diverse stimuli.
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Affiliation(s)
- Aidan Schneider
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Mehdi Azabou
- School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | | | - David F Parks
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Sahara Ensley
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Kiran Bhaskaran-Nair
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Tomasz Nowakowski
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Eva L Dyer
- School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA; Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Keith B Hengen
- Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA.
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38
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Grosu GF, Hopp AV, Moca VV, Bârzan H, Ciuparu A, Ercsey-Ravasz M, Winkel M, Linde H, Mureșan RC. The fractal brain: scale-invariance in structure and dynamics. Cereb Cortex 2023; 33:4574-4605. [PMID: 36156074 PMCID: PMC10110456 DOI: 10.1093/cercor/bhac363] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 08/09/2022] [Accepted: 08/10/2022] [Indexed: 11/12/2022] Open
Abstract
The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account of brain function. Here, we review these concepts, connecting observations across different levels of organization, from both a structural and functional perspective. We argue that, paradoxically, the level of cortical circuits is the least understood from a structural point of view and perhaps the best studied from a dynamical one. We further link observations about scale-freeness and fractality with evidence that the environment provides constraints that may explain the usefulness of fractal structure and scale-free dynamics in the brain. Moreover, we discuss evidence that behavior exhibits scale-free properties, likely emerging from similarly organized brain dynamics, enabling an organism to thrive in an environment that shares the same organizational principles. Finally, we review the sparse evidence for and try to speculate on the functional consequences of fractality and scale-freeness for brain computation. These properties may endow the brain with computational capabilities that transcend current models of neural computation and could hold the key to unraveling how the brain constructs percepts and generates behavior.
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Affiliation(s)
- George F Grosu
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, Romania
| | | | - Vasile V Moca
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
| | - Harald Bârzan
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, Romania
| | - Andrei Ciuparu
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, Romania
| | - Maria Ercsey-Ravasz
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Physics, Babes-Bolyai University, Str. Mihail Kogalniceanu 1, 400084 Cluj-Napoca, Romania
| | - Mathias Winkel
- Merck KGaA, Frankfurter Straße 250, 64293 Darmstadt, Germany
| | - Helmut Linde
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Merck KGaA, Frankfurter Straße 250, 64293 Darmstadt, Germany
| | - Raul C Mureșan
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
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39
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Affiliation(s)
- Max Dabagia
- School of Computer Science, Georgia Institute of Technology, Atlanta, GA, USA
| | - Konrad P Kording
- Department of Biomedical Engineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Eva L Dyer
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
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40
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Urzay C, Ahad N, Azabou M, Schneider A, Atamkuri G, Hengen KB, Dyer EL. Detecting change points in neural population activity with contrastive metric learning. INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING : [PROCEEDINGS]. INTERNATIONAL IEEE EMBS CONFERENCE ON NEURAL ENGINEERING 2023; 2023:10.1109/ner52421.2023.10123821. [PMID: 37808227 PMCID: PMC10559226 DOI: 10.1109/ner52421.2023.10123821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Finding points in time where the distribution of neural responses changes (change points) is an important step in many neural data analysis pipelines. However, in complex and free behaviors, where we see different types of shifts occurring at different rates, it can be difficult to use existing methods for change point (CP) detection because they can't necessarily handle different types of changes that may occur in the underlying neural distribution. Additionally, response changes are often sparse in high dimensional neural recordings, which can make existing methods detect spurious changes. In this work, we introduce a new approach for finding changes in neural population states across diverse activities and arousal states occurring in free behavior. Our model follows a contrastive learning approach: we learn a metric for CP detection based on maximizing the Sinkhorn divergences of neuron firing rates across two sides of a labeled CP. We apply this method to a 12-hour neural recording of a freely behaving mouse to detect changes in sleep stages and behavior. We show that when we learn a metric, we can better detect change points and also yield insights into which neurons and sub-groups are important for detecting certain types of switches that occur in the brain.
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Affiliation(s)
| | - Nauman Ahad
- Georgia Institute of Technology,Atlanta, GA 30308 USA
| | - Mehdi Azabou
- Georgia Institute of Technology,Atlanta, GA 30308 USA
| | | | | | - Keith B Hengen
- Washington University in St.Louis, St. Louis, MO 63130 USA
| | - Eva L Dyer
- Georgia Institute of Technology,Atlanta, GA 30308 USA
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41
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Salners T, Avila KE, Nicholson B, Myers CR, Beggs J, Dahmen KA. Recurrent activity in neuronal avalanches. Sci Rep 2023; 13:4871. [PMID: 36964158 PMCID: PMC10039060 DOI: 10.1038/s41598-023-31851-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 03/17/2023] [Indexed: 03/26/2023] Open
Abstract
A new statistical analysis of large neuronal avalanches observed in mouse and rat brain tissues reveals a substantial degree of recurrent activity and cyclic patterns of activation not seen in smaller avalanches. To explain these observations, we adapted a model of structural weakening in materials. In this model, dynamical weakening of neuron firing thresholds closely replicates experimental avalanche size distributions, firing number distributions, and patterns of cyclic activity. This agreement between model and data suggests that a mechanism like dynamical weakening plays a key role in recurrent activity found in large neuronal avalanches. We expect these results to illuminate the causes and dynamics of large avalanches, like those seen in seizures.
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Affiliation(s)
- Tyler Salners
- Department of Physics, University of Illinois at Urbana-Champaign, 1110 West Green Street, Urbana, IL, 61801, USA.
| | - Karina E Avila
- Physics Department, University Kaiserslautern, Erwin-Schrödinger-Straße, 67663, Kaiserslautern, Germany
| | - Benjamin Nicholson
- Laboratory of Atomic and Solid State Physics, Clark Hall, Cornell University, Ithaca, NY, 14853-2501, USA
| | - Christopher R Myers
- Laboratory of Atomic and Solid State Physics, Clark Hall, Cornell University, Ithaca, NY, 14853-2501, USA
- Center for Advanced Computing, Cornell University, Ithaca, NY, 14853, USA
| | - John Beggs
- Department of Physics, Indiana University, Bloomington, IN, 47405, USA
| | - Karin A Dahmen
- Department of Physics, University of Illinois at Urbana-Champaign, 1110 West Green Street, Urbana, IL, 61801, USA
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42
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Shirani F, Choi H. On the physiological and structural contributors to the overall balance of excitation and inhibition in local cortical networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.10.523489. [PMID: 36711468 PMCID: PMC9882012 DOI: 10.1101/2023.01.10.523489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Overall balance of excitation and inhibition in cortical networks is central to their functionality and normal operation. Such orchestrated co-evolution of excitation and inhibition is established through convoluted local interactions between neurons, which are organized by specific network connectivity structures and are dynamically controlled by modulating synaptic activities. Therefore, identifying how such structural and physiological factors contribute to establishment of overall balance of excitation and inhibition is crucial in understanding the homeostatic plasticity mechanisms that regulate the balance. We use biologically plausible mathematical models to extensively study the effects of multiple key factors on overall balance of a network. We characterize a network's baseline balanced state by certain functional properties, and demonstrate how variations in physiological and structural parameters of the network deviate this balance and, in particular, result in transitions in spontaneous activity of the network to high-amplitude slow oscillatory regimes. We show that deviations from the reference balanced state can be continuously quantified by measuring the ratio of mean excitatory to mean inhibitory synaptic conductances in the network. Our results suggest that the commonly observed ratio of the number of inhibitory to the number of excitatory neurons in local cortical networks is almost optimal for their stability and excitability. Moreover, the values of inhibitory synaptic decay time constants and density of inhibitory-to-inhibitory network connectivity are critical to overall balance and stability of cortical networks. However, network stability in our results is sufficiently robust against modulations of synaptic quantal conductances, as required by their role in learning and memory.
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43
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Morales GB, di Santo S, Muñoz MA. Quasiuniversal scaling in mouse-brain neuronal activity stems from edge-of-instability critical dynamics. Proc Natl Acad Sci U S A 2023; 120:e2208998120. [PMID: 36827262 PMCID: PMC9992863 DOI: 10.1073/pnas.2208998120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 12/31/2022] [Indexed: 02/25/2023] Open
Abstract
The brain is in a state of perpetual reverberant neural activity, even in the absence of specific tasks or stimuli. Shedding light on the origin and functional significance of such a dynamical state is essential to understanding how the brain transmits, processes, and stores information. An inspiring, albeit controversial, conjecture proposes that some statistical characteristics of empirically observed neuronal activity can be understood by assuming that brain networks operate in a dynamical regime with features, including the emergence of scale invariance, resembling those seen typically near phase transitions. Here, we present a data-driven analysis based on simultaneous high-throughput recordings of the activity of thousands of individual neurons in various regions of the mouse brain. To analyze these data, we construct a unified theoretical framework that synergistically combines a phenomenological renormalization group approach and techniques that infer the general dynamical state of a neural population, while designing complementary tools. This strategy allows us to uncover strong signatures of scale invariance that are "quasiuniversal" across brain regions and experiments, revealing that all the analyzed areas operate, to a greater or lesser extent, near the edge of instability.
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Affiliation(s)
- Guillermo B. Morales
- Departamento de Electromagnetismo y Física de la Materia, Instituto Carlos I de Física Teórica y Computacional Universidad de Granada, GranadaE-18071, Spain
| | - Serena di Santo
- Morton B. Zuckerman Mind Brain Behavior Institute Columbia University, New York, NY10027
| | - Miguel A. Muñoz
- Departamento de Electromagnetismo y Física de la Materia, Instituto Carlos I de Física Teórica y Computacional Universidad de Granada, GranadaE-18071, Spain
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44
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Rahimi-Majd M, Restrepo JG, Najafi MN. Stochastic and deterministic dynamics in networks with excitable nodes. CHAOS (WOODBURY, N.Y.) 2023; 33:023134. [PMID: 36859228 DOI: 10.1063/5.0103806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 01/27/2023] [Indexed: 06/18/2023]
Abstract
Networks of excitable systems provide a flexible and tractable model for various phenomena in biology, social sciences, and physics. A large class of such models undergo a continuous phase transition as the excitability of the nodes is increased. However, models of excitability that result in this continuous phase transition are based implicitly on the assumption that the probability that a node gets excited, its transfer function, is linear for small inputs. In this paper, we consider the effect of cooperative excitations, and more generally the case of a nonlinear transfer function, on the collective dynamics of networks of excitable systems. We find that the introduction of any amount of nonlinearity changes qualitatively the dynamical properties of the system, inducing a discontinuous phase transition and hysteresis. We develop a mean-field theory that allows us to understand the features of the dynamics with a one-dimensional map. We also study theoretically and numerically finite-size effects by examining the fate of initial conditions where only one node is excited in large but finite networks. Our results show that nonlinear transfer functions result in a rich effective phase diagram for finite networks, and that one should be careful when interpreting predictions of models that assume noncooperative excitations.
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Affiliation(s)
- M Rahimi-Majd
- Department of Physics, Shahid Beheshti University, 1983969411 Tehran, Iran
| | - J G Restrepo
- Department of Applied Mathematics, University of Colorado, Boulder, Colorado 80309, USA
| | - M N Najafi
- Department of Physics, University of Mohaghegh Ardabili, 5619911367 Ardabil, Iran
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45
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Jones SA, Barfield JH, Norman VK, Shew WL. Scale-free behavioral dynamics directly linked with scale-free cortical dynamics. eLife 2023; 12:e79950. [PMID: 36705565 PMCID: PMC9931391 DOI: 10.7554/elife.79950] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 01/06/2023] [Indexed: 01/28/2023] Open
Abstract
Naturally occurring body movements and collective neural activity both exhibit complex dynamics, often with scale-free, fractal spatiotemporal structure. Scale-free dynamics of both brain and behavior are important because each is associated with functional benefits to the organism. Despite their similarities, scale-free brain activity and scale-free behavior have been studied separately, without a unified explanation. Here, we show that scale-free dynamics of mouse behavior and neurons in the visual cortex are strongly related. Surprisingly, the scale-free neural activity is limited to specific subsets of neurons, and these scale-free subsets exhibit stochastic winner-take-all competition with other neural subsets. This observation is inconsistent with prevailing theories of scale-free dynamics in neural systems, which stem from the criticality hypothesis. We develop a computational model which incorporates known cell-type-specific circuit structure, explaining our findings with a new type of critical dynamics. Our results establish neural underpinnings of scale-free behavior and clear behavioral relevance of scale-free neural activity.
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Affiliation(s)
- Sabrina A Jones
- Department of Physics, University of Arkansas at FayettevilleFayettevilleUnited States
| | - Jacob H Barfield
- Department of Physics, University of Arkansas at FayettevilleFayettevilleUnited States
| | - V Kindler Norman
- Department of Physics, University of Arkansas at FayettevilleFayettevilleUnited States
| | - Woodrow L Shew
- Department of Physics, University of Arkansas at FayettevilleFayettevilleUnited States
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46
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Davenport F, Gallacher J, Kourtzi Z, Koychev I, Matthews PM, Oxtoby NP, Parkes LM, Priesemann V, Rowe JB, Smye SW, Zetterberg H. Neurodegenerative disease of the brain: a survey of interdisciplinary approaches. J R Soc Interface 2023; 20:20220406. [PMID: 36651180 PMCID: PMC9846433 DOI: 10.1098/rsif.2022.0406] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 12/16/2022] [Indexed: 01/19/2023] Open
Abstract
Neurodegenerative diseases of the brain pose a major and increasing global health challenge, with only limited progress made in developing effective therapies over the last decade. Interdisciplinary research is improving understanding of these diseases and this article reviews such approaches, with particular emphasis on tools and techniques drawn from physics, chemistry, artificial intelligence and psychology.
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Affiliation(s)
| | - John Gallacher
- Director of Dementias Platform, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Zoe Kourtzi
- Professor of Cognitive Computational Neuroscience, Department of Psychology, University of Cambridge, UK
| | - Ivan Koychev
- Senior Clinical Researcher, Department of Psychiatry, University of Oxford, Oxford, UK
- Consultant Neuropsychiatrist, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Paul M. Matthews
- Department of Brain Sciences and UK Dementia Research Institute Centre, Imperial College London, Oxford, UK
| | - Neil P. Oxtoby
- UCL Centre for Medical Image Computing and Department of Computer Science, University College London, Gower Street, London, UK
| | - Laura M. Parkes
- School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Viola Priesemann
- Max Planck Group Leader and Fellow of the Schiemann Kolleg, Max Planck Institute for Dynamics and Self-Organization and Bernstein Center for Computational Neuroscience, Göttingen, Germany
| | - James B. Rowe
- Department of Clinical Neurosciences, MRC Cognition and Brain Sciences Unit and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | | | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, People's Republic of China
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47
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Rosado OG, Amil AF, Freire IT, Verschure PFMJ. Drive competition underlies effective allostatic orchestration. Front Robot AI 2022; 9:1052998. [DOI: 10.3389/frobt.2022.1052998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 11/17/2022] [Indexed: 12/05/2022] Open
Abstract
Living systems ensure their fitness by self-regulating. The optimal matching of their behavior to the opportunities and demands of the ever-changing natural environment is crucial for satisfying physiological and cognitive needs. Although homeostasis has explained how organisms maintain their internal states within a desirable range, the problem of orchestrating different homeostatic systems has not been fully explained yet. In the present paper, we argue that attractor dynamics emerge from the competitive relation of internal drives, resulting in the effective regulation of adaptive behaviors. To test this hypothesis, we develop a biologically-grounded attractor model of allostatic orchestration that is embedded into a synthetic agent. Results show that the resultant neural mass model allows the agent to reproduce the navigational patterns of a rodent in an open field. Moreover, when exploring the robustness of our model in a dynamically changing environment, the synthetic agent pursues the stability of the self, being its internal states dependent on environmental opportunities to satisfy its needs. Finally, we elaborate on the benefits of resetting the model’s dynamics after drive-completion behaviors. Altogether, our studies suggest that the neural mass allostatic model adequately reproduces self-regulatory dynamics while overcoming the limitations of previous models.
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48
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Wu YK, Miehl C, Gjorgjieva J. Regulation of circuit organization and function through inhibitory synaptic plasticity. Trends Neurosci 2022; 45:884-898. [PMID: 36404455 DOI: 10.1016/j.tins.2022.10.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 10/02/2022] [Accepted: 10/04/2022] [Indexed: 11/15/2022]
Abstract
Diverse inhibitory neurons in the mammalian brain shape circuit connectivity and dynamics through mechanisms of synaptic plasticity. Inhibitory plasticity can establish excitation/inhibition (E/I) balance, control neuronal firing, and affect local calcium concentration, hence regulating neuronal activity at the network, single neuron, and dendritic level. Computational models can synthesize multiple experimental results and provide insight into how inhibitory plasticity controls circuit dynamics and sculpts connectivity by identifying phenomenological learning rules amenable to mathematical analysis. We highlight recent studies on the role of inhibitory plasticity in modulating excitatory plasticity, forming structured networks underlying memory formation and recall, and implementing adaptive phenomena and novelty detection. We conclude with experimental and modeling progress on the role of interneuron-specific plasticity in circuit computation and context-dependent learning.
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Affiliation(s)
- Yue Kris Wu
- School of Life Sciences, Technical University of Munich, Freising, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Christoph Miehl
- School of Life Sciences, Technical University of Munich, Freising, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Julijana Gjorgjieva
- School of Life Sciences, Technical University of Munich, Freising, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany.
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49
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Fosque LJ, Alipour A, Zare M, Williams-García RV, Beggs JM, Ortiz G. Quasicriticality explains variability of human neural dynamics across life span. Front Comput Neurosci 2022; 16:1037550. [PMID: 36532868 PMCID: PMC9747757 DOI: 10.3389/fncom.2022.1037550] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 10/27/2022] [Indexed: 08/26/2023] Open
Abstract
Aging impacts the brain's structural and functional organization and over time leads to various disorders, such as Alzheimer's disease and cognitive impairment. The process also impacts sensory function, bringing about a general slowing in various perceptual and cognitive functions. Here, we analyze the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) resting-state magnetoencephalography (MEG) dataset-the largest aging cohort available-in light of the quasicriticality framework, a novel organizing principle for brain functionality which relates information processing and scaling properties of brain activity to brain connectivity and stimulus. Examination of the data using this framework reveals interesting correlations with age and gender of test subjects. Using simulated data as verification, our results suggest a link between changes to brain connectivity due to aging and increased dynamical fluctuations of neuronal firing rates. Our findings suggest a platform to develop biomarkers of neurological health.
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Affiliation(s)
- Leandro J. Fosque
- Department of Physics, Indiana University, Bloomington, IN, United States
| | - Abolfazl Alipour
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States
| | | | | | - John M. Beggs
- Department of Physics, Indiana University, Bloomington, IN, United States
| | - Gerardo Ortiz
- Department of Physics, Indiana University, Bloomington, IN, United States
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50
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Neto JP, Spitzner FP, Priesemann V. Sampling effects and measurement overlap can bias the inference of neuronal avalanches. PLoS Comput Biol 2022; 18:e1010678. [PMID: 36445932 PMCID: PMC9733887 DOI: 10.1371/journal.pcbi.1010678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 12/09/2022] [Accepted: 10/24/2022] [Indexed: 12/02/2022] Open
Abstract
To date, it is still impossible to sample the entire mammalian brain with single-neuron precision. This forces one to either use spikes (focusing on few neurons) or to use coarse-sampled activity (averaging over many neurons, e.g. LFP). Naturally, the sampling technique impacts inference about collective properties. Here, we emulate both sampling techniques on a simple spiking model to quantify how they alter observed correlations and signatures of criticality. We describe a general effect: when the inter-electrode distance is small, electrodes sample overlapping regions in space, which increases the correlation between the signals. For coarse-sampled activity, this can produce power-law distributions even for non-critical systems. In contrast, spike recordings do not suffer this particular bias and underlying dynamics can be identified. This may resolve why coarse measures and spikes have produced contradicting results in the past.
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Affiliation(s)
- Joao Pinheiro Neto
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
| | - F. Paul Spitzner
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
| | - Viola Priesemann
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Bernstein Center for Computational Neuroscience, Göttingen, Germany
- Georg-August University Göttingen, Göttingen, Germany
- * E-mail:
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