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Griffa A, Mach M, Dedelley J, Gutierrez-Barragan D, Gozzi A, Allali G, Grandjean J, Van De Ville D, Amico E. Evidence for increased parallel information transmission in human brain networks compared to macaques and male mice. Nat Commun 2023; 14:8216. [PMID: 38081838 PMCID: PMC10713651 DOI: 10.1038/s41467-023-43971-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 11/24/2023] [Indexed: 12/18/2023] Open
Abstract
Brain communication, defined as information transmission through white-matter connections, is at the foundation of the brain's computational capacities that subtend almost all aspects of behavior: from sensory perception shared across mammalian species, to complex cognitive functions in humans. How did communication strategies in macroscale brain networks adapt across evolution to accomplish increasingly complex functions? By applying a graph- and information-theory approach to assess information-related pathways in male mouse, macaque and human brains, we show a brain communication gap between selective information transmission in non-human mammals, where brain regions share information through single polysynaptic pathways, and parallel information transmission in humans, where regions share information through multiple parallel pathways. In humans, parallel transmission acts as a major connector between unimodal and transmodal systems. The layout of information-related pathways is unique to individuals across different mammalian species, pointing at the individual-level specificity of information routing architecture. Our work provides evidence that different communication patterns are tied to the evolution of mammalian brain networks.
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Affiliation(s)
- Alessandra Griffa
- Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland.
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
| | - Mathieu Mach
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Julien Dedelley
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Daniel Gutierrez-Barragan
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Gilles Allali
- Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Joanes Grandjean
- Department of Medical Imaging, Radboud University Medical Center, 6525 GA, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6525 EN, Nijmegen, The Netherlands
| | - Dimitri Van De Ville
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Enrico Amico
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland.
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
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2
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Salvalaggio A, Pini L, Griffa A, Corbetta M. Editorial: Brain connectivity in neurological disorders. Front Syst Neurosci 2023; 17:1274801. [PMID: 37841895 PMCID: PMC10569722 DOI: 10.3389/fnsys.2023.1274801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 08/24/2023] [Indexed: 10/17/2023] Open
Affiliation(s)
- Alessandro Salvalaggio
- Padova Neuroscience Center, University of Padua, Padua, Italy
- Department of Neuroscience, University of Padua, Padua, Italy
| | - Lorenzo Pini
- Padova Neuroscience Center, University of Padua, Padua, Italy
| | - Alessandra Griffa
- Leenaards Memory Center, Department of Clinical Neurosciences, Lausanne University Hospital, Lausanne, Switzerland
| | - Maurizio Corbetta
- Padova Neuroscience Center, University of Padua, Padua, Italy
- Department of Neuroscience, University of Padua, Padua, Italy
- Veneto Institute of Molecular Medicine (VIMM), Padua, Italy
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3
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Nuber-Champier A, Cionca A, Breville G, Voruz P, Jacot de Alcântara I, Allali G, Lalive PH, Benzakour L, Lövblad KO, Braillard O, Nehme M, Coen M, Serratrice J, Reny JL, Pugin J, Guessous I, Landis BN, Griffa A, Van De Ville D, Assal F, Péron JA. Corrigendum to "Acute TNFα levels predict cognitive impairment 6-9 months after COVID-19 infection" [Psychoneuroendocrinology 153 (2023) 106104]. Psychoneuroendocrinology 2023:106324. [PMID: 37380558 PMCID: PMC10292659 DOI: 10.1016/j.psyneuen.2023.106324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Affiliation(s)
- A Nuber-Champier
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland; Neurology Division, Geneva University Hospitals, Switzerland
| | - A Cionca
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland
| | - G Breville
- Neurology Division, Geneva University Hospitals, Switzerland
| | - P Voruz
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland; Neurology Division, Geneva University Hospitals, Switzerland; Faculty of Medicine, University of Geneva, Switzerland
| | - I Jacot de Alcântara
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland; Neurology Division, Geneva University Hospitals, Switzerland; Faculty of Medicine, University of Geneva, Switzerland
| | - G Allali
- Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - P H Lalive
- Neurology Division, Geneva University Hospitals, Switzerland; Faculty of Medicine, University of Geneva, Switzerland
| | - L Benzakour
- Faculty of Medicine, University of Geneva, Switzerland; Psychiatry Department, Geneva University Hospitals, Switzerland
| | - K-O Lövblad
- Faculty of Medicine, University of Geneva, Switzerland; Diagnostic and Interventional Neuroradiology Department, Geneva University Hospitals, Switzerland
| | - O Braillard
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Switzerland
| | - M Nehme
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Switzerland
| | - M Coen
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Switzerland
| | - J Serratrice
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Switzerland
| | - J-L Reny
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Switzerland
| | - J Pugin
- Faculty of Medicine, University of Geneva, Switzerland; Intensive Care Department, Geneva University Hospitals, Switzerland
| | - I Guessous
- Faculty of Medicine, University of Geneva, Switzerland; Division and Department of Primary Care Medicine, Geneva University Hospitals, Switzerland
| | - B N Landis
- Faculty of Medicine, University of Geneva, Switzerland; Rhinology-Olfactology Unit, Otorhinolaryngology Department, Geneva University Hospitals, Switzerland
| | - A Griffa
- Neurology Division, Geneva University Hospitals, Switzerland; Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Federale de Lausanne (EPFL), Geneva, Switzerland
| | - D Van De Ville
- Faculty of Medicine, University of Geneva, Switzerland; Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Federale de Lausanne (EPFL), Geneva, Switzerland
| | - F Assal
- Neurology Division, Geneva University Hospitals, Switzerland; Faculty of Medicine, University of Geneva, Switzerland
| | - J A Péron
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland; Neurology Division, Geneva University Hospitals, Switzerland.
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4
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Thomasson M, Voruz P, Cionca A, Jacot de Alcântara I, Nuber-Champier A, Allali G, Benzakour L, Lalive PH, Lövblad KO, Braillard O, Nehme M, Coen M, Serratrice J, Reny JL, Pugin J, Guessous I, Landis BN, Griffa A, Van De Ville D, Assal F, Péron JA. Markers of limbic system damage following SARS-CoV-2 infection. Brain Commun 2023; 5:fcad177. [PMID: 37415776 PMCID: PMC10320753 DOI: 10.1093/braincomms/fcad177] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 04/21/2023] [Accepted: 06/09/2023] [Indexed: 07/08/2023] Open
Abstract
Alterations of the limbic system may be present in the chronic phase of SARS-CoV-2 infection. Our aim was to study the long-term impact of this disease on limbic system-related behaviour and its associated brain functional connectivity, according to the severity of respiratory symptoms in the acute phase. To this end, we investigated the multimodal emotion recognition abilities of 105 patients from the Geneva COVID-COG Cohort 223 days on average after SARS-CoV-2 infection (diagnosed between March 2020 and May 2021), dividing them into three groups (severe, moderate or mild) according to respiratory symptom severity in the acute phase. We used multiple regressions and partial least squares correlation analyses to investigate the relationships between emotion recognition, olfaction, cognition, neuropsychiatric symptoms and functional brain networks. Six to 9 months following SARS-CoV-2 infection, moderate patients exhibited poorer recognition abilities than mild patients for expressions of fear (P = 0.03 corrected), as did severe patients for disgust (P = 0.04 corrected) and irritation (P < 0.01 corrected). In the whole cohort, these performances were associated with decreased episodic memory and anosmia, but not with depressive symptoms, anxiety or post-traumatic stress disorder. Neuroimaging revealed a positive contribution of functional connectivity, notably between the cerebellum and the default mode, somatosensory motor and salience/ventral attention networks. These results highlight the long-term consequences of SARS-Cov-2 infection on the limbic system at both the behavioural and neuroimaging levels.
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Affiliation(s)
| | | | - Alexandre Cionca
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva 1205, Switzerland
| | - Isabele Jacot de Alcântara
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva 1205, Switzerland
- Neurology Department, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva 1205, Switzerland
| | - Anthony Nuber-Champier
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva 1205, Switzerland
| | - Gilles Allali
- Leenaards Memory Centre, Lausanne University Hospital and University of Lausanne, Lausanne 1205, Switzerland
| | - Lamyae Benzakour
- Psychiatry Department, Geneva University Hospitals, Geneva 1205, Switzerland
| | - Patrice H Lalive
- Neurology Department, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva 1205, Switzerland
- Faculty of Medicine, University of Geneva, Geneva 1011, Switzerland
| | - Karl-Olof Lövblad
- Faculty of Medicine, University of Geneva, Geneva 1011, Switzerland
- Diagnostic and Interventional Neuroradiology Department, Geneva University Hospitals, Geneva 1205, Switzerland
| | - Olivia Braillard
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva 1205, Switzerland
| | - Mayssam Nehme
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva 1205, Switzerland
| | - Matteo Coen
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Geneva 1205, Switzerland
| | - Jacques Serratrice
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Geneva 1205, Switzerland
| | - Jean-Luc Reny
- Faculty of Medicine, University of Geneva, Geneva 1011, Switzerland
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Geneva 1205, Switzerland
| | - Jérôme Pugin
- Faculty of Medicine, University of Geneva, Geneva 1011, Switzerland
- Intensive Care Department, Geneva University Hospitals, Geneva 1205, Switzerland
| | - Idris Guessous
- Faculty of Medicine, University of Geneva, Geneva 1011, Switzerland
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva 1205, Switzerland
| | - Basile N Landis
- Faculty of Medicine, University of Geneva, Geneva 1011, Switzerland
- Rhinology-Olfactology Unit, Otorhinolaryngology Department, Geneva University Hospitals, Geneva 1205, Switzerland
| | - Alessandra Griffa
- Leenaards Memory Centre, Lausanne University Hospital and University of Lausanne, Lausanne 1205, Switzerland
- Institute of Bioengineering, Centre for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva 1205, Switzerland
| | - Dimitri Van De Ville
- Faculty of Medicine, University of Geneva, Geneva 1011, Switzerland
- Institute of Bioengineering, Centre for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Frederic Assal
- Neurology Department, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva 1205, Switzerland
- Faculty of Medicine, University of Geneva, Geneva 1011, Switzerland
| | - Julie A Péron
- Correspondence to: Julie Péron Clinical and Experimental Neuropsychology Laboratory Faculté de Psychologie et des Sciences de l’Education Université de Genève, 40 bd du Pont d’Arve 1205 Geneva, Switzerland E-mail:
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5
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Nuber-Champier A, Cionca A, Breville G, Voruz P, de Alcântara IJ, Allali G, Lalive PH, Benzakour L, Lövblad KO, Braillard O, Nehme M, Coen M, Serratrice J, Reny JL, Pugin J, Guessous I, Landis BN, Griffa A, De Ville DV, Assal F, Péron JA. Acute TNFα levels predict cognitive impairment 6-9 months after COVID-19 infection. Psychoneuroendocrinology 2023; 153:106104. [PMID: 37104966 PMCID: PMC10066791 DOI: 10.1016/j.psyneuen.2023.106104] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/22/2023] [Accepted: 03/28/2023] [Indexed: 04/03/2023]
Abstract
BACKGROUND A neurocognitive phenotype of post-COVID-19 infection has recently been described that is characterized by a lack of awareness of memory impairment (i.e., anosognosia), altered functional connectivity in the brain's default mode and limbic networks, and an elevated monocyte count. However, the relationship between these cognitive and brain functional connectivity alterations in the chronic phase with the level of cytokines during the acute phase has yet to be identified. AIM Determine whether acute cytokine type and levels is associated with anosognosia and functional patterns of brain connectivity 6-9 months after infection. METHODS We analyzed the predictive value of the concentration of acute cytokines (IL-1RA, IL-1β, IL-6, IL-8, IFNγ, G-CSF, GM-CSF) (cytokine panel by multiplex immunoassay) in the plasma of 39 patients (mean age 59 yrs, 38-78) in relation to their anosognosia scores for memory deficits via stepwise linear regression. Then, associations between the different cytokines and brain functional connectivity patterns were analyzed by MRI and multivariate partial least squares correlations for the whole group. RESULTS Stepwise regression modeling allowed us to show that acute TNFα levels predicted (R2 = 0.145; β = -0.38; p = .017) and were associated (r = -0.587; p < .001) with scores of anosognosia for memory deficits observed 6-9 months post-infection. Finally, high TNFα levels were associated with hippocampal, temporal pole, accumbens nucleus, amygdala, and cerebellum connectivity. CONCLUSION Increased plasma TNFα levels in the acute phase of COVID-19 predict the presence of long-term anosognosia scores and changes in limbic system functional connectivity.
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Affiliation(s)
- A Nuber-Champier
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland; Neurology Division, Geneva University Hospitals, Switzerland
| | - A Cionca
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland
| | - G Breville
- Neurology Division, Geneva University Hospitals, Switzerland
| | - P Voruz
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland; Neurology Division, Geneva University Hospitals, Switzerland; Faculty of Medicine, University of Geneva, Switzerland
| | - I Jacot de Alcântara
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland; Neurology Division, Geneva University Hospitals, Switzerland; Faculty of Medicine, University of Geneva, Switzerland
| | - G Allali
- Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - P H Lalive
- Neurology Division, Geneva University Hospitals, Switzerland; Faculty of Medicine, University of Geneva, Switzerland
| | - L Benzakour
- Faculty of Medicine, University of Geneva, Switzerland; Psychiatry Department, Geneva University Hospitals, Switzerland
| | - K-O Lövblad
- Faculty of Medicine, University of Geneva, Switzerland; Diagnostic and Interventional Neuroradiology Department, Geneva University Hospitals, Switzerland
| | - O Braillard
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Switzerland
| | - M Nehme
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Switzerland
| | - M Coen
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Switzerland
| | - J Serratrice
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Switzerland
| | - J-L Reny
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Switzerland
| | - J Pugin
- Faculty of Medicine, University of Geneva, Switzerland; Intensive Care Department, Geneva University Hospitals, Switzerland
| | - I Guessous
- Faculty of Medicine, University of Geneva, Switzerland; Division and Department of Primary Care Medicine, Geneva University Hospitals, Switzerland
| | - B N Landis
- Faculty of Medicine, University of Geneva, Switzerland; Rhinology-Olfactology Unit, Otorhinolaryngology Department, Geneva University Hospitals, Switzerland
| | - A Griffa
- Neurology Division, Geneva University Hospitals, Switzerland; Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - D Van De Ville
- Faculty of Medicine, University of Geneva, Switzerland; Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - F Assal
- Neurology Division, Geneva University Hospitals, Switzerland; Faculty of Medicine, University of Geneva, Switzerland
| | - J A Péron
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland; Neurology Division, Geneva University Hospitals, Switzerland.
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6
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Colenbier N, Sareen E, Del-Aguila Puntas T, Griffa A, Pellegrino G, Mantini D, Marinazzo D, Arcara G, Amico E. Task matters: Individual MEG signatures from naturalistic and neurophysiological brain states. Neuroimage 2023; 271:120021. [PMID: 36918139 DOI: 10.1016/j.neuroimage.2023.120021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/21/2023] [Accepted: 03/10/2023] [Indexed: 03/14/2023] Open
Abstract
The discovery that human brain connectivity data can be used as a "fingerprint" to identify a given individual from a population, has become a burgeoning research area in the neuroscience field. Recent studies have identified the possibility to extract these brain signatures from the temporal rich dynamics of resting-state magneto encephalography (MEG) recordings. Nevertheless, it is still uncertain to what extent MEG signatures can serve as an indicator of human identifiability during task-related conduct. Here, using MEG data from naturalistic and neurophysiological tasks, we show that identification improves in tasks relative to resting-state, providing compelling evidence for a task dependent axis of MEG signatures. Notably, improvements in identifiability were more prominent in strictly controlled tasks. Lastly, the brain regions contributing most towards individual identification were also modified when engaged in task activities. We hope that this investigation advances our understanding of the driving factors behind brain identification from MEG signals.
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Affiliation(s)
| | - Ekansh Sareen
- Medical Image Processing Laboratory, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - Tamara Del-Aguila Puntas
- Laboratorio de Psicobiologia, Departmento de Psicología Experimental, Facultad de Psicología, Universidad de Sevilla, Spain
| | - Alessandra Griffa
- Medical Image Processing Laboratory, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Switzerland; Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU Leuven, Belgium
| | - Daniele Marinazzo
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium
| | | | - Enrico Amico
- Medical Image Processing Laboratory, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Switzerland.
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7
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Voruz P, Cionca A, Jacot de Alcântara I, Nuber-Champier A, Allali G, Benzakour L, Lalive PH, Lövblad KO, Braillard O, Nehme M, Coen M, Serratrice J, Reny JL, Pugin J, Guessous I, Ptak R, Landis BN, Adler D, Griffa A, Van De Ville D, Assal F, Péron JA. Brain functional connectivity alterations associated with neuropsychological performance 6-9 months following SARS-CoV-2 infection. Hum Brain Mapp 2023; 44:1629-1646. [PMID: 36458984 PMCID: PMC9878070 DOI: 10.1002/hbm.26163] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 11/11/2022] [Indexed: 12/05/2022] Open
Abstract
Neuropsychological deficits and brain damage following SARS-CoV-2 infection are not well understood. Then, 116 patients, with either severe, moderate, or mild disease in the acute phase underwent neuropsychological and olfactory tests, as well as completed psychiatric and respiratory questionnaires at 223 ± 42 days postinfection. Additionally, a subgroup of 50 patients underwent functional magnetic resonance imaging. Patients in the severe group displayed poorer verbal episodic memory performances, and moderate patients had reduced mental flexibility. Neuroimaging revealed patterns of hypofunctional and hyperfunctional connectivities in severe patients, while only hyperconnectivity patterns were observed for moderate. The default mode, somatosensory, dorsal attention, subcortical, and cerebellar networks were implicated. Partial least squares correlations analysis confirmed specific association between memory, executive functions performances and brain functional connectivity. The severity of the infection in the acute phase is a predictor of neuropsychological performance 6-9 months following SARS-CoV-2 infection. SARS-CoV-2 infection causes long-term memory and executive dysfunctions, related to large-scale functional brain connectivity alterations.
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Affiliation(s)
- Philippe Voruz
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland.,Department of Clinical Neurosciences, Neurology Department, Geneva University Hospitals, Geneva, Switzerland.,Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Alexandre Cionca
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland
| | - Isabele Jacot de Alcântara
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland.,Department of Clinical Neurosciences, Neurology Department, Geneva University Hospitals, Geneva, Switzerland
| | - Anthony Nuber-Champier
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland
| | - Gilles Allali
- Department of Clinical Neurosciences, Neurology Department, Geneva University Hospitals, Geneva, Switzerland.,Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Lamyae Benzakour
- Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Psychiatry Department, Geneva University Hospitals, Geneva, Switzerland
| | - Patrice H Lalive
- Department of Clinical Neurosciences, Neurology Department, Geneva University Hospitals, Geneva, Switzerland.,Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Karl O Lövblad
- Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Diagnostic and Interventional Neuroradiology Department, Geneva University Hospitals, Geneva, Switzerland
| | - Olivia Braillard
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Mayssam Nehme
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Matteo Coen
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Geneva, Switzerland
| | - Jacques Serratrice
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Geneva, Switzerland
| | - Jean-Luc Reny
- Division of General Internal Medicine, Department of Medicine, Geneva University Hospitals and Geneva University, Geneva, Switzerland
| | - Jérôme Pugin
- Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Intensive Care Department, Geneva University Hospitals, Geneva, Switzerland
| | - Idris Guessous
- Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Radek Ptak
- Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Neurorehabilitation Department, Geneva University Hospitals, Geneva, Switzerland
| | - Basile N Landis
- Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Rhinology-Olfactology Unit, Otorhinolaryngology Department, Geneva University Hospitals, Geneva, Switzerland
| | - Dan Adler
- Division of Pulmonary Diseases, Geneva University Hospitals, Geneva, Switzerland
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Neurology Department, Geneva University Hospitals, Geneva, Switzerland.,Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Dimitri Van De Ville
- Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Frédéric Assal
- Department of Clinical Neurosciences, Neurology Department, Geneva University Hospitals, Geneva, Switzerland.,Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Julie A Péron
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland.,Department of Clinical Neurosciences, Neurology Department, Geneva University Hospitals, Geneva, Switzerland
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8
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Govaarts R, Scheijbeler E, Beeldman E, Fraschini M, Griffa A, Engels M, van der Kooi A, Pijnenburg Y, de Visser M, Stam C, Raaphorst J, Hillebrand A. P.218 Moving along the ALS-bvFTD spectrum: longitudinal changes in MEG-based brain network topology of ALS patients with cognitive/behavioural impairment. Neuromuscul Disord 2022. [DOI: 10.1016/j.nmd.2022.07.386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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9
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Alemán-Gómez Y, Griffa A, Houde JC, Najdenovska E, Magon S, Cuadra MB, Descoteaux M, Hagmann P. A multi-scale probabilistic atlas of the human connectome. Sci Data 2022; 9:516. [PMID: 35999243 PMCID: PMC9399115 DOI: 10.1038/s41597-022-01624-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 08/03/2022] [Indexed: 11/10/2022] Open
Abstract
The human brain is a complex system that can be efficiently represented as a network of structural connectivity. Many imaging studies would benefit from such network information, which is not always available. In this work, we present a whole-brain multi-scale structural connectome atlas. This tool has been derived from a cohort of 66 healthy subjects imaged with optimal technology in the setting of the Human Connectome Project. From these data we created, using extensively validated diffusion-data processing, tractography and gray-matter parcellation tools, a multi-scale probabilistic atlas of the human connectome. In addition, we provide user-friendly and accessible code to match this atlas to individual brain imaging data to extract connection-specific quantitative information. This can be used to associate individual imaging findings, such as focal white-matter lesions or regional alterations, to specific connections and brain circuits. Accordingly, network-level consequences of regional changes can be analyzed even in absence of diffusion and tractography data. This method is expected to broaden the accessibility and lower the yield for connectome research.
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Affiliation(s)
- Yasser Alemán-Gómez
- Connectomics Lab, Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland. .,Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Prilly, Switzerland.
| | - Alessandra Griffa
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.,Medical Image Processing Laboratory, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.,Leenaards Memory Centre, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | - Elena Najdenovska
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), Lausanne, Switzerland.,Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Stefano Magon
- Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Meritxell Bach Cuadra
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Centre d'Imagerie BioMédicale (CIBM), Lausanne, Switzerland.,Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab, Sherbrooke University, Sherbrooke, Canada
| | - Patric Hagmann
- Connectomics Lab, Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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10
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Griffa A, Bommarito G, Assal F, Preti MG, Goldstein R, Armand S, Herrmann FR, Van De Ville D, Allali G. CSF tap test in idiopathic normal pressure hydrocephalus: still a necessary prognostic test? J Neurol 2022; 269:5114-5126. [PMID: 35598251 PMCID: PMC9363476 DOI: 10.1007/s00415-022-11168-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 04/29/2022] [Accepted: 05/01/2022] [Indexed: 12/05/2022]
Abstract
Objective To assess whether gait, neuropsychological, and multimodal MRI parameters predict short-term symptom reversal after cerebrospinal fluid (CSF) tap test in idiopathic normal pressure hydrocephalus (iNPH). Methods Thirty patients (79.3 ± 5.9 years, 12 women) with a diagnosis of probable iNPH and 46 healthy controls (74.7 ± 5.4 years, 35 women) underwent comprehensive neuropsychological, quantitative gait, and multimodal MRI assessments of brain morphology, periventricular white-matter microstructure, cortical and subcortical blood perfusion, default mode network function, and white-matter lesion load. Responders were defined as an improvement of at least 10% in walking speed or timed up and go test 24 h after tap test. Univariate and multivariable tap test outcome prediction models were evaluated with logistic regression and linear support vector machine classification. Results Sixteen patients (53%) respondedpositively to tap test. None of the gait, neuropsychological, or neuroimaging parameters considered separately predicted outcome. A multivariable classifier achieved modest out-of-sample outcome prediction accuracy of 70% (p = .028); gait parameters, white-matter lesion load and periventricular microstructure were the main contributors. Conclusions Our negative findings show that short-term symptom reversal after tap test cannot be predicted from single gait, neuropsychological, or MRI parameters, thus supporting the use of tap test as prognostic procedure. However, multivariable approaches integrating non-invasive multimodal data are informative of outcome and may be included in patient-screening procedures. Their value in predicting shunting outcome should be further explored, particularly in relation to gait and white-matter parameters. Supplementary Information The online version contains supplementary material available at 10.1007/s00415-022-11168-x.
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11
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Govaarts R, Beeldman E, Fraschini M, Griffa A, Engels MMA, van Es MA, Veldink JH, van den Berg LH, van der Kooi AJ, Pijnenburg YAL, de Visser M, Stam CJ, Raaphorst J, Hillebrand A. Cortical and subcortical changes in resting-state neuronal activity and connectivity in early symptomatic ALS and advanced frontotemporal dementia. Neuroimage Clin 2022; 34:102965. [PMID: 35217500 PMCID: PMC8867127 DOI: 10.1016/j.nicl.2022.102965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/08/2022] [Accepted: 02/09/2022] [Indexed: 01/17/2023]
Abstract
The objective of this study was to examine if patterns of resting-state brain activity and functional connectivity in cortical and subcortical regions in patients with early symptomatic amyotrophic lateral sclerosis (ALS) resemble those of behavioural variant frontotemporal dementia (bvFTD). In a cross-sectional design, eyes-closed resting-state magnetoencephalography (MEG) data of 34 ALS patients, 18 bvFTD patients and 18 age- and gender-matched healthy controls (HCs) were projected to source-space using an atlas-based beamformer. Group differences in peak frequency, band-specific oscillatory activity and functional connectivity (corrected amplitude envelope correlation) in 78 cortical regions and 12 subcortical regions were determined. False discovery rate was used to correct for multiple comparisons. BvFTD patients, as compared to ALS and HCs, showed lower relative beta power in parietal, occipital, temporal and nearly all subcortical regions. Compared to HCs, patients with ALS and patients with bvFTD had a higher delta (0.5-4 Hz) and gamma (30-48 Hz) band resting-state functional connectivity in a high number of overlapping regions in the frontal lobe and in limbic and subcortical regions. Higher delta band connectivity was widespread in the bvFTD patients compared to HCs. ALS showed a more widespread higher gamma band functional connectivity compared to bvFTD. In conclusion, MEG in early symptomatic ALS patients shows resting-state functional connectivity changes in frontal, limbic and subcortical regions that overlap considerably with bvFTD. The findings show the potential of MEG to detect brain changes in early symptomatic phases of ALS and contribute to our understanding of the disease spectrum, with ALS and bvFTD at the two extreme ends.
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Affiliation(s)
- Rosanne Govaarts
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Emma Beeldman
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Matteo Fraschini
- University of Cagliari, Department of Electrical and Electronic Engineering, Cagliari, Italy
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Institute of Bioengineering, Center of Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Marjolein M A Engels
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Michael A van Es
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Jan H Veldink
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Leonard H van den Berg
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Anneke J van der Kooi
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Yolande A L Pijnenburg
- Amsterdam University Medical Centers, Vrije Universiteit, Alzheimer Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Marianne de Visser
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Joost Raaphorst
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
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12
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Bommarito G, Garibotto V, Frisoni GB, Ribaldi F, Stampacchia S, Assal F, Armand S, Allali G, Griffa A. The Biological Substrate of the Motoric Cognitive Risk Syndrome: A Pilot Study Using Amyloid-/Tau-PET and MR Imaging. J Alzheimers Dis 2022; 87:1483-1490. [PMID: 35491777 PMCID: PMC9277684 DOI: 10.3233/jad-215461] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
We conducted a cross-sectional pilot study to explore the biological substrate of the Motoric Cognitive Risk (MCR) syndrome in a Memory Clinic cohort, using a multimodal imaging approach. Twenty participants were recruited and classified as MCR+/−. Amyloid- and tau-PET uptakes, temporal atrophy, white matter hyperintensities, lateral ventricular volume (LVV), and diffusion tensor parameters were compared between groups. No significant differences were found in imaging features related to Alzheimer’s disease or gross vascular damage. MCR+ patients had increased LVV and altered diffusion parameters in the superior corona radiata. Ventricular enlargement and microstructural damage of the surrounding white matter tracts could contribute to MCR pathophysiology.
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Affiliation(s)
- Giulia Bommarito
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and NIMTlab, Geneva University, Geneva, Switzerland
| | - Giovanni B. Frisoni
- Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Federica Ribaldi
- Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Sara Stampacchia
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and NIMTlab, Geneva University, Geneva, Switzerland
| | - Frédéric Assal
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Stéphane Armand
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Switzerland
| | - Gilles Allali
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA
- Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Institute of Bioengineering, Center of Neuroprosthetics, Ecole Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
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13
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Griffa A, Amico E, Liégeois R, Ville DVD, Preti MG. Brain structure-function coupling provides signatures for task decoding and individual fingerprinting. Neuroimage 2022; 250:118970. [DOI: 10.1016/j.neuroimage.2022.118970] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 01/12/2022] [Accepted: 02/03/2022] [Indexed: 11/17/2022] Open
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14
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Voruz P, Cionca A, Jacot de Alcântara I, Nuber-Champier A, Allali G, Benzakour L, Thomasson M, Lalive PH, Lövblad KO, Braillard O, Nehme M, Coen M, Serratrice J, Pugin J, Guessous I, Landis BN, Adler D, Griffa A, Van De Ville D, Assal F, Péron JA. OUP accepted manuscript. Brain Commun 2022; 4:fcac057. [PMID: 35350554 PMCID: PMC8956133 DOI: 10.1093/braincomms/fcac057] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Revised: 01/17/2022] [Accepted: 03/06/2022] [Indexed: 11/13/2022] Open
Abstract
Lack of awareness of cognitive impairment (i.e. anosognosia) could be a key
factor for distinguishing between neuropsychological post-COVID-19 condition
phenotypes. In this context, the 2-fold aim of the present study was to (i)
establish the prevalence of anosognosia for memory impairment, according to the
severity of the infection in the acute phase and (ii) determine whether
anosognosic patients with post-COVID syndrome have a different cognitive and
psychiatric profile from nosognosic patients, with associated differences in
brain functional connectivity. A battery of neuropsychological, psychiatric,
olfactory, dyspnoea, fatigue and quality-of-life tests was administered
227.07 ± 42.69 days post-SARS-CoV-2 infection to 102
patients (mean age: 56.35 years, 65 men, no history of neurological,
psychiatric, neuro-oncological or neurodevelopmental disorder prior to
infection) who had experienced either a mild (not hospitalized;
n = 45), moderate (conventional
hospitalization; n = 34) or severe
(hospitalization with intensive care unit stay and mechanical ventilation;
n = 23) presentation in the acute
phase. Patients were first divided into two groups according to the presence or
absence of anosognosia for memory deficits (26 anosognosic patients and 76
nosognosic patients). Of these, 49 patients underwent an MRI. Structural images
were visually analysed, and statistical intergroup analyses were then performed
on behavioural and functional connectivity measures. Only 15.6% of
patients who presented mild disease displayed anosognosia for memory
dysfunction, compared with 32.4% of patients with moderate presentation
and 34.8% of patients with severe disease. Compared with nosognosic
patients, those with anosognosia for memory dysfunction performed significantly
more poorly on objective cognitive and olfactory measures. By contrast, they
gave significantly more positive subjective assessments of their quality of
life, psychiatric status and fatigue. Interestingly, the proportion of patients
exhibiting a lack of consciousness of olfactory deficits was significantly
higher in the anosognosic group. Functional connectivity analyses revealed a
significant decrease in connectivity, in the anosognosic group as compared with
the nosognosic group, within and between the following networks: the left
default mode, the bilateral somatosensory motor, the right executive control,
the right salient ventral attention and the bilateral dorsal attention networks,
as well as the right Lobules IV and V of the cerebellum. Lack of awareness of
cognitive disorders and, to a broader extent, impairment of the self-monitoring
brain system, may be a key factor for distinguishing between the clinical
phenotypes of post-COVID syndrome with neuropsychological deficits.
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Affiliation(s)
- Philippe Voruz
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland
- Neurology Department, Geneva University Hospitals, Geneva, Switzerland
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Alexandre Cionca
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland
| | - Isabele Jacot de Alcântara
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland
- Neurology Department, Geneva University Hospitals, Geneva, Switzerland
| | - Anthony Nuber-Champier
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland
| | - Gilles Allali
- Neurology Department, Geneva University Hospitals, Geneva, Switzerland
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Leenaards Memory Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Lamyae Benzakour
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Psychiatry Department, Geneva University Hospitals, Geneva, Switzerland
| | - Marine Thomasson
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland
- Neurology Department, Geneva University Hospitals, Geneva, Switzerland
| | - Patrice H Lalive
- Neurology Department, Geneva University Hospitals, Geneva, Switzerland
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Karl-Olof Lövblad
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Diagnostic and Interventional Neuroradiology Department, Geneva University Hospitals, Geneva, Switzerland
| | - Olivia Braillard
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Mayssam Nehme
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Matteo Coen
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Internal Medicine Department, Geneva University Hospitals, Geneva, Switzerland
| | - Jacques Serratrice
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Internal Medicine Department, Geneva University Hospitals, Geneva, Switzerland
| | - Jérôme Pugin
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Intensive Care Department, Geneva University Hospitals, Geneva, Switzerland
| | - Idris Guessous
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division and Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Basile N Landis
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Rhinology-Olfactology Unit, Otorhinolaryngology Department, Geneva University Hospitals, Geneva, Switzerland
| | - Dan Adler
- Division of Pulmonary Diseases, Geneva University Hospitals, Geneva, Switzerland
| | - Alessandra Griffa
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Dimitri Van De Ville
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Frédéric Assal
- Neurology Department, Geneva University Hospitals, Geneva, Switzerland
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Julie A Péron
- Clinical and Experimental Neuropsychology Laboratory, Faculty of Psychology, University of Geneva, Geneva, Switzerland
- Neurology Department, Geneva University Hospitals, Geneva, Switzerland
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15
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Griffa A, Legdeur N, Badissi M, van den Heuvel MP, Stam CJ, Visser PJ, Hillebrand A. Magnetoencephalography Brain Signatures Relate to Cognition and Cognitive Reserve in the Oldest-Old: The EMIF-AD 90 + Study. Front Aging Neurosci 2021; 13:746373. [PMID: 34899269 PMCID: PMC8656941 DOI: 10.3389/fnagi.2021.746373] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/01/2021] [Indexed: 11/25/2022] Open
Abstract
The oldest-old subjects represent the fastest growing segment of society and are at high risk for dementia with a prevalence of up to 40%. Lifestyle factors, such as lifelong participation in cognitive and leisure activities, may contribute to individual cognitive reserve and reduce the risk for cognitive impairments. However, the neural bases underlying cognitive functioning and cognitive reserve in this age range are still poorly understood. Here, we investigate spectral and functional connectivity features obtained from resting-state MEG recordings in a cohort of 35 cognitively normal (92.2 ± 1.8 years old, 19 women) and 11 cognitively impaired (90.9 ± 1.9 years old, 1 woman) oldest-old participants, in relation to cognitive traits and cognitive reserve. The latter was approximated with a self-reported scale on lifelong engagement in cognitively demanding activities. Cognitively impaired oldest-old participants had slower cortical rhythms in frontal, parietal and default mode network regions compared to the cognitively normal subjects. These alterations mainly concerned the theta and beta band and partially explained inter-subject variability of episodic memory scores. Moreover, a distinct spectral pattern characterized by higher relative power in the alpha band was specifically associated with higher cognitive reserve while taking into account the effect of age and education level. Finally, stronger functional connectivity in the alpha and beta band were weakly associated with better cognitive performances in the whole group of subjects, although functional connectivity effects were less prominent than the spectral ones. Our results shed new light on the neural underpinnings of cognitive functioning in the oldest-old population and indicate that cognitive performance and cognitive reserve may have distinct spectral electrophysiological substrates.
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Affiliation(s)
- Alessandra Griffa
- Division of Neurology, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Center of Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland.,Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Nienke Legdeur
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Maryam Badissi
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Martijn P van den Heuvel
- Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neuroscience and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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16
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Zuber P, Gaetano L, Griffa A, Huerbin M, Pedullà L, Bonzano L, Altermatt A, Tsagkas C, Parmar K, Hagmann P, Wuerfel J, Kappos L, Sprenger T, Sporns O, Magon S. Additive and interaction effects of working memory and motor sequence training on brain functional connectivity. Sci Rep 2021; 11:23089. [PMID: 34845312 PMCID: PMC8630199 DOI: 10.1038/s41598-021-02492-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 10/29/2021] [Indexed: 11/08/2022] Open
Abstract
Although shared behavioral and neural mechanisms between working memory (WM) and motor sequence learning (MSL) have been suggested, the additive and interactive effects of training have not been studied. This study aimed at investigating changes in brain functional connectivity (FC) induced by sequential (WM + MSL and MSL + WM) and combined (WM × MSL) training programs. 54 healthy subjects (27 women; mean age: 30.2 ± 8.6 years) allocated to three training groups underwent twenty-four 40-min training sessions over 6 weeks and four cognitive assessments including functional MRI. A double-baseline approach was applied to account for practice effects. Test performances were compared using linear mixed-effects models and t-tests. Resting state fMRI data were analysed using FSL. Processing speed, verbal WM and manual dexterity increased following training in all groups. MSL + WM training led to additive effects in processing speed and verbal WM. Increased FC was found after training in a network including the right angular gyrus, left superior temporal sulcus, right superior parietal gyrus, bilateral middle temporal gyri and left precentral gyrus. No difference in FC was found between double baselines. Results indicate distinct patterns of resting state FC modulation related to sequential and combined WM and MSL training suggesting a relevance of the order of training performance. These observations could provide new insight for the planning of effective training/rehabilitation.
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Affiliation(s)
- Priska Zuber
- Division of Cognitive Neuroscience, Faculty of Psychology, University of Basel, Basel, Switzerland
| | | | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Center of Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Manuel Huerbin
- Medical Image Analysis Center (MIAC AG), Basel, Switzerland
| | - Ludovico Pedullà
- Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Genoa, Italy
- Italian Multiple Sclerosis Foundation, Scientific Research Area, Genoa, Italy
| | - Laura Bonzano
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Anna Altermatt
- Medical Image Analysis Center (MIAC AG), Basel, Switzerland
| | - Charidimos Tsagkas
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Katrin Parmar
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Reha Rheinfelden, Rheinfelden, Switzerland
| | - Patric Hagmann
- Center of Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jens Wuerfel
- Medical Image Analysis Center (MIAC AG), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Till Sprenger
- Department of Neurology, DKD Helios Klinik, Wiesbaden, Germany
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- Indiana University Network Science Institute, Indiana University, Bloomington, IN, USA
| | - Stefano Magon
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.
- Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
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17
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Rhally A, Griffa A, Kremer S, Uginet M, Breville G, Stancu P, Assal F, Lalive PH, Lövblad KO, Allali G. C-reactive protein and white matter microstructural changes in COVID-19 patients with encephalopathy. J Neural Transm (Vienna) 2021; 128:1899-1906. [PMID: 34709472 PMCID: PMC8552620 DOI: 10.1007/s00702-021-02429-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 09/22/2021] [Indexed: 12/19/2022]
Abstract
Encephalopathy is a neurological complication of COVID-19. The objective of this exploratory study is to investigate the link between systemic inflammation and brain microstructural changes (measured by diffusion-weighted imaging) in patients with COVID-19 encephalopathy. 20 patients with COVID-19 encephalopathy (age: 67.3 [Formula: see text] 10.0 years; 90% men) hospitalized in the Geneva University Hospitals for a SARS-CoV-2 infection between March and May 2020 were included in this retrospective cohort study. COVID-19 encephalopathy was diagnosed following a comprehensive neurobiological evaluation, excluding common causes of delirium, such as hypoxemic or metabolic encephalopathy. We investigated the correlation between systemic inflammation (measured by systemic C-reactive protein (CRP)) and brain microstructural changes in radiologically normal white matter (measured by apparent diffusion coefficient (ADC)) in nine spatially widespread regions of the white matter previously associated with delirium. Systemic inflammation (CRP = 60.8 ± 50.0 mg/L) was positively correlated with ADC values in the anterior corona radiata (p = 0.0089), genu of the corpus callosum (p = 0.0064) and external capsule (p = 0.0086) after adjusting for patients' age. No statistically significant association between CRP and ADC was found in the other six white matter regions. Our findings indicate high risk of white matter abnormalities in COVID-19 encephalopathy patients with high peripheral inflammatory markers, suggesting aggressive imaging monitoring may be warranted in these patients. Future studies should clarify a possible specificity of the spatial patterns of CRP-white matter microstructure association in COVID-19 encephalopathy patients and disentangle the role of individual cytokines on brain inflammatory mechanisms.
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Affiliation(s)
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland. .,Institute of Bioengineering, Center of Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech-H4 3 232.080 (H4 building), Chemin des Mines 9, Case postale 60, CH-1211, Geneva, Switzerland.
| | - Stéphane Kremer
- Service d'imagerie 2, Hôpitaux Universitaires de Strasbourg, Strasbourg, France.,Engineering Science, Computer Science and Imaging Laboratory (ICube), Integrative Multimodal Imaging in Healthcare, UMR 7357, University of Strasbourg-CNRS, Strasbourg, France
| | - Marjolaine Uginet
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Gautier Breville
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Patrick Stancu
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Frédéric Assal
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Patrice H Lalive
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Diagnostic Department, Division of Laboratory Medicine, Geneva University Hospitals, Geneva, Switzerland.,Department of Pathology and Immunology, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Karl-Olof Lövblad
- Division of Neuroradiology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Gilles Allali
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Division of Cognitive and Motor Aging, Department of Neurology, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA
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18
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Stripeikyte G, Potheegadoo J, Progin P, Rognini G, Blondiaux E, Salomon R, Griffa A, Hagmann P, Faivre N, Do KQ, Conus P, Blanke O. Fronto-Temporal Disconnection Within the Presence Hallucination Network in Psychotic Patients With Passivity Experiences. Schizophr Bull 2021; 47:1718-1728. [PMID: 33823042 PMCID: PMC8530400 DOI: 10.1093/schbul/sbab031] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Psychosis, characterized by hallucinations and delusions, is a common feature of psychiatric disease, especially schizophrenia. One prominent theory posits that psychosis is driven by abnormal sensorimotor predictions leading to the misattribution of self-related events. This misattribution has been linked to passivity experiences (PE), such as loss of agency and, more recently, to presence hallucinations (PH), defined as the conscious experience of the presence of an alien agent while no person is actually present. PH has been observed in schizophrenia, Parkinson's disease, and neurological patients with brain lesions and, recently, the brain mechanisms of PH (PH-network) have been determined comprising bilateral posterior middle temporal gyrus (pMTG), inferior frontal gyrus (IFG), and ventral premotor cortex (vPMC). Given that the experience of an alien agent is a common feature of PE, we here analyzed the functional connectivity within the PH-network in psychotic patients with (N = 39) vs without PE (N = 26). We observed reduced fronto-temporal functional connectivity in patients with PE compared to patients without PE between the right pMTG and the right and left IFG of the PH-network. Moreover, when seeding from these altered regions, we observed specific alterations with brain regions commonly linked to auditory-verbal hallucinations (such as Heschl's gyrus). The present connectivity findings within the PH-network extend the disconnection hypothesis for hallucinations to the specific case of PH and associates the PH-network with key brain regions for frequent psychotic symptoms such as auditory-verbal hallucinations, showing that PH are relevant to the study of the brain mechanisms of psychosis and PE.
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Affiliation(s)
- Giedre Stripeikyte
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Jevita Potheegadoo
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Pierre Progin
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Giulio Rognini
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Eva Blondiaux
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Roy Salomon
- Gonda Brain Research Center, Bar Ilan University (BIU), Ramat-Gan, Israel
| | - Alessandra Griffa
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Nathan Faivre
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, 38000, Grenoble, France
| | - Kim Q Do
- Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
- Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Philippe Conus
- Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Olaf Blanke
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Department of Neurology, University Hospital, Geneva, Switzerland
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19
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Bommarito G, Van De Ville D, Frisoni GB, Garibotto V, Ribaldi F, Stampacchia S, Assal F, Allali G, Griffa A. Alzheimer's Disease Biomarkers in Idiopathic Normal Pressure Hydrocephalus: Linking Functional Connectivity and Clinical Outcome. J Alzheimers Dis 2021; 83:1717-1728. [PMID: 34459399 DOI: 10.3233/jad-210534] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) pathology impacts the response to treatment in patients with idiopathic normal pressure hydrocephalus (iNPH), possibly through changes in resting-state functional connectivity (rs-FC). OBJECTIVE To explore the relationship between cerebrospinal fluid biomarkers of AD and the default mode network (DMN)/hippocampal rs-FC in iNPH patients, based on their outcome after cerebrospinal fluid tap test (CSFTT), and in patients with AD. METHODS Twenty-six iNPH patients (mean age: 79.9±5.9 years; 12 females) underwent MRI and clinical assessment before and after CSFTT and were classified as responders (Resp) or not (NResp), based on the improvement at the timed up and go test and walking speed. Eleven AD patients (mean age: 70.91±5.2 years; 5 females), matched to iNPH for cognitive status, were also included. DMN and hippocampal rs-FC was related to amyloid-β42 and phosphorylated tau (pTau) levels. RESULTS Lower amyloid-β42 levels were associated with reduced inter- and intra-network rs-FC in NResp, and the interaction between amyloid-β42 and rs-FC was a predictor of outcome after CSFTT. The rs-FC between DMN and salience networks positively correlated to amyloid-β42 levels in both NResp and AD patients. The increase in the inter-network rs-FC after CSFTT was associated with higher pTau and lower amyloid-β42 levels in NResp, and to lower pTau levels in Resp. CONCLUSION Amyloid-β42 and pTau impact on rs-FC and its changes after CSFTT in iNPH patients. The interaction between AD biomarkers and rs-FC might explain the responder status in iNPH.
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Affiliation(s)
- Giulia Bommarito
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Dimitri Van De Ville
- Institute of Bioengineering, Center of Neuroprosthetics, Ecole Polytechnique Fédérale De Lausanne (EPFL), Lausanne, Switzerland.,Department of Radiology and Medical Informatics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Giovanni B Frisoni
- Memory Clinic, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and NIMTlab, Geneva University, Geneva, Switzerland
| | - Federica Ribaldi
- Memory Clinic, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
| | - Sara Stampacchia
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and NIMTlab, Geneva University, Geneva, Switzerland
| | - Frédéric Assal
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Gilles Allali
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Institute of Bioengineering, Center of Neuroprosthetics, Ecole Polytechnique Fédérale De Lausanne (EPFL), Lausanne, Switzerland
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20
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Sareen E, Zahar S, Ville DVD, Gupta A, Griffa A, Amico E. Exploring MEG brain fingerprints: Evaluation, pitfalls, and interpretations. Neuroimage 2021; 240:118331. [PMID: 34237444 DOI: 10.1016/j.neuroimage.2021.118331] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 06/22/2021] [Accepted: 07/01/2021] [Indexed: 12/16/2022] Open
Abstract
Individual characterization of subjects based on their functional connectome (FC), termed "FC fingerprinting", has become a highly sought-after goal in contemporary neuroscience research. Recent functional magnetic resonance imaging (fMRI) studies have demonstrated unique characterization and accurate identification of individuals as an accomplished task. However, FC fingerprinting in magnetoencephalography (MEG) data is still widely unexplored. Here, we study resting-state MEG data from the Human Connectome Project to assess the MEG FC fingerprinting and its relationship with several factors including amplitude- and phase-coupling functional connectivity measures, spatial leakage correction, frequency bands, and behavioral significance. To this end, we first employ two identification scoring methods, differential identifiability and success rate, to provide quantitative fingerprint scores for each FC measurement. Secondly, we explore the edgewise and nodal MEG fingerprinting patterns across the different frequency bands (delta, theta, alpha, beta, and gamma). Finally, we investigate the cross-modality fingerprinting patterns obtained from MEG and fMRI recordings from the same subjects. We assess the behavioral significance of FC across connectivity measures and imaging modalities using partial least square correlation analyses. Our results suggest that fingerprinting performance is heavily dependent on the functional connectivity measure, frequency band, identification scoring method, and spatial leakage correction. We report higher MEG fingerprinting performances in phase-coupling methods, central frequency bands (alpha and beta), and in the visual, frontoparietal, dorsal-attention, and default-mode networks. Furthermore, cross-modality comparisons reveal a certain degree of spatial concordance in fingerprinting patterns between the MEG and fMRI data, especially in the visual system. Finally, the multivariate correlation analyses show that MEG connectomes have strong behavioral significance, which however depends on the considered connectivity measure and temporal scale. This comprehensive, albeit preliminary investigation of MEG connectome test-retest identifiability offers a first characterization of MEG fingerprinting in relation to different methodological and electrophysiological factors and contributes to the understanding of fingerprinting cross-modal relationships. We hope that this first investigation will contribute to setting the grounds for MEG connectome identification.
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Affiliation(s)
- Ekansh Sareen
- Signal Processing and Biomedical Imaging, Dept. of Electronics and Communication Engineering, IIIT-Delhi, New Delhi, India
| | - Sélima Zahar
- Institute of Bioengineering, Center for Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Dimitri Van De Ville
- Institute of Bioengineering, Center for Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland
| | - Anubha Gupta
- Signal Processing and Biomedical Imaging, Dept. of Electronics and Communication Engineering, IIIT-Delhi, New Delhi, India
| | - Alessandra Griffa
- Institute of Bioengineering, Center for Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland; Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Enrico Amico
- Institute of Bioengineering, Center for Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland.
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21
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Griffa A, Bommarito G, Assal F, Herrmann FR, Van De Ville D, Allali G. Cover Image. Hum Brain Mapp 2021. [DOI: 10.1002/hbm.25056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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22
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Cieri F, Cera N, Griffa A, Mantini D, Esposito R. Editorial: Dynamic Functioning of Resting State Networks in Physiological and Pathological Conditions. Front Neurosci 2021; 14:624401. [PMID: 33390900 PMCID: PMC7772206 DOI: 10.3389/fnins.2020.624401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Accepted: 11/20/2020] [Indexed: 11/23/2022] Open
Affiliation(s)
- Filippo Cieri
- Department of Neurology, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States
| | - Nicoletta Cera
- Center for Psychology at University of Porto (CPUP), Faculty of Psychology and Educational Sciences, University of Porto, Porto, Portugal
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Institute of Bioengineering, Center of Neuroprosthetics, Ecole Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Dante Mantini
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Brain Imaging and Neural Dynamics Research Group, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Camillo Hospital, Venice, Italy
| | - Roberto Esposito
- Titano Diagnostic Clinic, Falciano, San Marino.,Area Vasta 1, ASUR Marche, Pesaro, Italy
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23
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Griffa A, Bommarito G, Assal F, Herrmann FR, Van De Ville D, Allali G. Dynamic functional networks in idiopathic normal pressure hydrocephalus: Alterations and reversibility by CSF tap test. Hum Brain Mapp 2020; 42:1485-1502. [PMID: 33296129 PMCID: PMC7927299 DOI: 10.1002/hbm.25308] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 11/02/2020] [Accepted: 11/26/2020] [Indexed: 12/19/2022] Open
Abstract
Idiopathic Normal Pressure Hydrocephalus (iNPH)—the leading cause of reversible dementia in aging—is characterized by ventriculomegaly and gait, cognitive and urinary impairments. Despite its high prevalence estimated at 6% among the elderlies, iNPH remains underdiagnosed and undertreated due to the lack of iNPH‐specific diagnostic markers and limited understanding of pathophysiological mechanisms. INPH diagnosis is also complicated by the frequent occurrence of comorbidities, the most common one being Alzheimer's disease (AD). Here we investigate the resting‐state functional magnetic resonance imaging dynamics of 26 iNPH patients before and after a CSF tap test, and of 48 normal older adults. Alzheimer's pathology was evaluated by CSF biomarkers. We show that the interactions between the default mode, and the executive‐control, salience and attention networks are impaired in iNPH, explain gait and executive disturbances in patients, and are not driven by AD‐pathology. In particular, AD molecular biomarkers are associated with functional changes distinct from iNPH functional alterations. Finally, we demonstrate a partial normalization of brain dynamics 24 hr after a CSF tap test, indicating functional plasticity mechanisms. We conclude that functional changes involving the default mode cross‐network interactions reflect iNPH pathophysiological mechanisms and track treatment response, possibly contributing to iNPH differential diagnosis and better clinical management.
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Affiliation(s)
- Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Institute of Bioengineering, Center of Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Giulia Bommarito
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Institute of Bioengineering, Center of Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Frédéric Assal
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - François R Herrmann
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Dimitri Van De Ville
- Institute of Bioengineering, Center of Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland.,Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Gilles Allali
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, New York, USA
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24
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Salomon R, Progin P, Griffa A, Rognini G, Do KQ, Conus P, Marchesotti S, Bernasconi F, Hagmann P, Serino A, Blanke O. Sensorimotor Induction of Auditory Misattribution in Early Psychosis. Schizophr Bull 2020; 46:947-954. [PMID: 32043142 PMCID: PMC7345777 DOI: 10.1093/schbul/sbz136] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Dysfunction of sensorimotor predictive processing is thought to underlie abnormalities in self-monitoring producing passivity symptoms in psychosis. Experimentally induced sensorimotor conflict can produce a failure in bodily self-monitoring (presence hallucination [PH]), yet it is unclear how this is related to auditory self-monitoring and psychosis symptoms. Here we show that the induction of sensorimotor conflict in early psychosis patients induces PH and impacts auditory-verbal self-monitoring. Participants manipulated a haptic robotic system inducing a bodily sensorimotor conflict. In experiment 1, the PH was measured. In experiment 2, an auditory-verbal self-monitoring task was performed during the conflict. Fifty-one participants (31 early psychosis patients, 20 matched controls) participated in the experiments. The PH was present in all participants. Psychosis patients with passivity experiences (PE+) had reduced accuracy in auditory-verbal self-other discrimination during sensorimotor stimulation, but only when sensorimotor stimulation involved a spatiotemporal conflict (F(2, 44) = 6.68, P = .002). These results show a strong link between robotically controlled alterations in sensorimotor processing and auditory misattribution in psychosis and provide evidence for the role of sensorimotor processes in altered self-monitoring in psychosis.
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Affiliation(s)
- Roy Salomon
- Laboratory of Cognitive Neuroscience, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Gonda Brain Research Center, Bar Ilan University (BIU), Ramat-Gan, Israel,Center for Neuroprosthetics, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,To whom correspondence should be addressed; Gonda Brain Research Center, Bar Ilan University (BIU), Ramat-Gan, 52900, Israel; tel: +972-3-5317755, fax: +972-3-5352184, e-mail:
| | - Pierre Progin
- Laboratory of Cognitive Neuroscience, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Center for Neuroprosthetics, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Alessandra Griffa
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland,Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Giulio Rognini
- Laboratory of Cognitive Neuroscience, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Center for Neuroprosthetics, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Kim Q Do
- Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland,Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Philippe Conus
- Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland,Service of General Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Silvia Marchesotti
- Laboratory of Cognitive Neuroscience, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Center for Neuroprosthetics, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Fosco Bernasconi
- Laboratory of Cognitive Neuroscience, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Center for Neuroprosthetics, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Andrea Serino
- Laboratory of Cognitive Neuroscience, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Center for Neuroprosthetics, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Olaf Blanke
- Laboratory of Cognitive Neuroscience, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Center for Neuroprosthetics, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland,Department of Neurology, University Hospital, Geneva, Switzerland
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25
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Griffa A, Van De Ville D, Herrmann FR, Allali G. Neural circuits of idiopathic Normal Pressure Hydrocephalus: A perspective review of brain connectivity and symptoms meta-analysis. Neurosci Biobehav Rev 2020; 112:452-471. [PMID: 32088348 DOI: 10.1016/j.neubiorev.2020.02.023] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 01/09/2020] [Accepted: 02/17/2020] [Indexed: 12/13/2022]
Abstract
Idiopathic normal pressure hydrocephalus (iNPH) is a prevalent reversible neurological disorder characterized by impaired locomotion, cognition and urinary control with ventriculomegaly. Symptoms can be relieved with cerebrospinal fluid drainage, which makes iNPH the leading cause of reversible dementia. Because of a limited understanding of pathophysiological mechanisms, unspecific symptoms and the high prevalence of comorbidity (i.e. Alzheimer's disease), iNPH is largely underdiagnosed. For these reasons, there is an urgent need for developing noninvasive quantitative biomarkers for iNPH diagnosis and prognosis. Structural and functional changes of brain circuits in relation to symptoms and treatment response are expected to deliver major advances in this direction. We review structural and functional brain connectivity findings in iNPH and complement those findings with iNPH symptom meta-analyses in healthy populations. Our goal is to reinforce our conceptualization of iNPH as to brain network mechanisms and foster the development of new hypotheses for future research and treatment options.
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Affiliation(s)
- Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Institute of Bioengineering, Center of Neuroprosthetics, Ecole Polytechnique Fédérale De Lausanne (EPFL), Lausanne, Switzerland.
| | - Dimitri Van De Ville
- Institute of Bioengineering, Center of Neuroprosthetics, Ecole Polytechnique Fédérale De Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
| | - François R Herrmann
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.
| | - Gilles Allali
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Faculty of Medicine, University of Geneva, Geneva, Switzerland; Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA.
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26
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Vohryzek J, Griffa A, Mullier E, Friedrichs-Maeder C, Sandini C, Schaer M, Eliez S, Hagmann P. Dynamic spatiotemporal patterns of brain connectivity reorganize across development. Netw Neurosci 2020; 4:115-133. [PMID: 32043046 PMCID: PMC7006876 DOI: 10.1162/netn_a_00111] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 10/16/2019] [Indexed: 01/21/2023] Open
Abstract
Late human development is characterized by the maturation of high-level functional processes, which rely on reshaping of white matter connections, as well as synaptic density. However, the relationship between the whole-brain dynamics and the underlying white matter networks in neurodevelopment is largely unknown. In this study, we focused on how the structural connectome shapes the emerging dynamics of cerebral development between the ages of 6 and 33 years, using functional and diffusion magnetic resonance imaging combined into a spatiotemporal connectivity framework. We defined two new measures of brain dynamics, namely the system diversity and the spatiotemporal diversity, which quantify the level of integration/segregation between functional systems and the level of temporal self-similarity of the functional patterns of brain dynamics, respectively. We observed a global increase in system diversity and a global decrease and local refinement in spatiotemporal diversity values with age. In support of these findings, we further found an increase in the usage of long-range and inter-system white matter connectivity and a decrease in the usage of short-range connectivity with age. These findings suggest that dynamic functional patterns in the brain progressively become more integrative and temporally self-similar with age. These functional changes are supported by a greater involvement of long-range and inter-system axonal pathways.
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Affiliation(s)
- Jakub Vohryzek
- Department of Radiology, University Hospital Centre and University of Lausanne, Lausanne, Switzerland
| | - Alessandra Griffa
- Department of Radiology, University Hospital Centre and University of Lausanne, Lausanne, Switzerland
- Dutch Connectome Lab, Department of Complex Trait Genetics, Centre for Neuroscience and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands
| | - Emeline Mullier
- Department of Radiology, University Hospital Centre and University of Lausanne, Lausanne, Switzerland
| | - Cecilia Friedrichs-Maeder
- Department of Radiology, University Hospital Centre and University of Lausanne, Lausanne, Switzerland
- Department of Neurology, Bern University Hospital, University of Bern, Switzerland
| | - Corrado Sandini
- Department of Psychiatry, University of Geneva School of Medicine, Geneva, Switzerland
| | - Marie Schaer
- Department of Psychiatry, University of Geneva School of Medicine, Geneva, Switzerland
| | - Stephan Eliez
- Department of Psychiatry, University of Geneva School of Medicine, Geneva, Switzerland
| | - Patric Hagmann
- Department of Radiology, University Hospital Centre and University of Lausanne, Lausanne, Switzerland
- Signal Processing Lab 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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27
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Cui LB, Wei Y, Xi YB, Griffa A, De Lange SC, Kahn RS, Yin H, Van den Heuvel MP. Connectome-Based Patterns of First-Episode Medication-Naïve Patients With Schizophrenia. Schizophr Bull 2019; 45:1291-1299. [PMID: 30926985 PMCID: PMC6811827 DOI: 10.1093/schbul/sbz014] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Emerging evidence indicates that a disruption in brain network organization may play an important role in the pathophysiology of schizophrenia. The neuroimaging fingerprint reflecting the pathophysiology of first-episode schizophrenia remains to be identified. Here, we aimed at characterizing the connectome organization of first-episode medication-naïve patients with schizophrenia. A cross-sectional structural and functional neuroimaging study using two independent samples (principal dataset including 42 medication-naïve, previously untreated patients and 48 healthy controls; replication dataset including 39 first-episode patients [10 untreated patients] and 66 healthy controls) was performed. Brain network architecture was assessed by means of white matter fiber integrity measures derived from diffusion-weighted imaging (DWI) and by means of structural-functional (SC-FC) coupling measured by combining DWI and resting-state functional magnetic resonance imaging. Connectome rich club organization was found to be significantly disrupted in medication-naïve patients as compared with healthy controls (P = .012, uncorrected), with rich club connection strength (P = .032, uncorrected) and SC-FC coupling (P < .001, corrected for false discovery rate) decreased in patients. Similar results were found in the replication dataset. Our findings suggest that a disruption of rich club organization and functional dynamics may reflect an early feature of schizophrenia pathophysiology. These findings add to our understanding of the neuropathological mechanisms of schizophrenia and provide new insights into the early stages of the disorder.
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Affiliation(s)
- Long-Biao Cui
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- School of Medical Psychology, Fourth Military Medical University, Xi’an, China
| | - Yongbin Wei
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Yi-Bin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Alessandra Griffa
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Siemon C De Lange
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - René S Kahn
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Martijn P Van den Heuvel
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
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28
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Allali G, Montembeault M, Griffa A, Beauchet O. Default mode network and the timed up and go in MCI: A structural covariance analysis. Exp Gerontol 2019; 129:110748. [PMID: 31634541 DOI: 10.1016/j.exger.2019.110748] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 10/02/2019] [Accepted: 10/03/2019] [Indexed: 11/18/2022]
Abstract
BACKGROUND The timed up and go (TUG) is a test used to assess mobility in older adults and patients with neurological conditions. This study aims to compare brain gray matter (GM) correlates and structural covariance networks associated with the TUG time in cognitively healthy individuals (CHI) and in patients with mild cognitive impairment (MCI). METHODS The TUG time was measured in 326 non-demented older community-dwellers (age 71.3 ± 4.5; 42% female) - 156 CHI and 170 MCI. GM covariance networks were computed using voxel-based morphometry with the main neural correlates of TUG for each group as seed regions. RESULTS Increased TUG time (i.e., poor performance) was associated with distinct brain volume reductions between CHI and MCI. The covariance analysis showed cortical regions involving the default mode network in CHI and bilateral cerebellar regions in MCI. CONCLUSIONS GM networks associated with the TUG vary between CHI and MCI, suggesting distinct brain control for locomotion between CHI and MCI patients.
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Affiliation(s)
- Gilles Allali
- Department of Neurology, Geneva University Hospital, University of Geneva, Switzerland; Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA.
| | - Maxime Montembeault
- Centre de recherche de l'Institut universitaire de gériatrie de Montréal, Montréal H3W 1W5, Quebec, Canada; Département de psychologie, Université de Montréal, Montréal H3C 3J7, Quebec, Canada
| | - Alessandra Griffa
- Department of Neurology, Geneva University Hospital, University of Geneva, Switzerland; Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Fédéerale de Lausanne (EPFL), Lausanne, Switzerland
| | - Olivier Beauchet
- Department of Medicine, Division of Geriatric Medicine, Sir Mortimer B. Davis - Jewish General Hospital, Lady Davis Institute for Medical Research, McGill University, Montreal, Quebec, Canada; Dr. Joseph Kaufmann Chair in Geriatric Medicine, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Centre of Excellence on Longevity of McGill integrated University Health Network, Quebec, Canada; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
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29
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Mišic B, Betzel RF, Griffa A, de Reus MA, He Y, Zuo XN, van den Heuvel MP, Hagmann P, Sporns O, Zatorre RJ. Network-Based Asymmetry of the Human Auditory System. Cereb Cortex 2019; 28:2655-2664. [PMID: 29722805 PMCID: PMC5998951 DOI: 10.1093/cercor/bhy101] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 04/13/2018] [Indexed: 01/12/2023] Open
Abstract
Converging evidence from activation, connectivity, and stimulation studies suggests that auditory brain networks are lateralized. Here we show that these findings can be at least partly explained by the asymmetric network embedding of the primary auditory cortices. Using diffusion-weighted imaging in 3 independent datasets, we investigate the propensity for left and right auditory cortex to communicate with other brain areas by quantifying the centrality of the auditory network across a spectrum of communication mechanisms, from shortest path communication to diffusive spreading. Across all datasets, we find that the right auditory cortex is better integrated in the connectome, facilitating more efficient communication with other areas, with much of the asymmetry driven by differences in communication pathways to the opposite hemisphere. Critically, the primacy of the right auditory cortex emerges only when communication is conceptualized as a diffusive process, taking advantage of more than just the topologically shortest paths in the network. Altogether, these results highlight how the network configuration and embedding of a particular region may contribute to its functional lateralization.
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Affiliation(s)
- Bratislav Mišic
- Montréal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Richard F Betzel
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Alessandra Griffa
- Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Marcel A de Reus
- Brain Center Rudolf Magnus, UMC Utrecht, Utrecht, The Netherlands
| | - Ye He
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, People's Republic of China.,Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Xi-Nian Zuo
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, People's Republic of China
| | | | - Patric Hagmann
- Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Robert J Zatorre
- Montréal Neurological Institute, McGill University, Montreal, Quebec, Canada
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30
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Tewarie P, Liuzzi L, O'Neill GC, Quinn AJ, Griffa A, Woolrich MW, Stam CJ, Hillebrand A, Brookes MJ. Tracking dynamic brain networks using high temporal resolution MEG measures of functional connectivity. Neuroimage 2019; 200:38-50. [DOI: 10.1016/j.neuroimage.2019.06.006] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Revised: 05/12/2019] [Accepted: 06/03/2019] [Indexed: 11/29/2022] Open
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31
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Douw L, van Dellen E, Gouw AA, Griffa A, de Haan W, van den Heuvel M, Hillebrand A, Van Mieghem P, Nissen IA, Otte WM, Reijmer YD, Schoonheim MM, Senden M, van Straaten ECW, Tijms BM, Tewarie P, Stam CJ. The road ahead in clinical network neuroscience. Netw Neurosci 2019; 3:969-993. [PMID: 31637334 PMCID: PMC6777944 DOI: 10.1162/netn_a_00103] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 07/23/2019] [Indexed: 12/15/2022] Open
Abstract
Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future investigations. These discussions revolve around questions like "How do dynamic processes alter the underlying structural network?" and "Can we use network neuroscience for disease classification?" This opinion paper is an incomplete overview of these discussions and expands on ten questions that may potentially advance the field. By no means intended as a review of the current state of the field, it is instead meant as a conversation starter and source of inspiration to others.
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Affiliation(s)
- Linda Douw
- Department of Anatomy and Neuroscience, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Edwin van Dellen
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Alida A. Gouw
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Alessandra Griffa
- Connectome Lab, Department of Neuroscience, section Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Willem de Haan
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Martijn van den Heuvel
- Connectome Lab, Department of Neuroscience, section Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Piet Van Mieghem
- Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
| | - Ida A. Nissen
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Willem M. Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Yael D. Reijmer
- Department of Neurology, Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Menno M. Schoonheim
- Department of Anatomy and Neuroscience, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Mario Senden
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Elisabeth C. W. van Straaten
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Betty M. Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Prejaas Tewarie
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Cornelis J. Stam
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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Baumann PS, Klauser P, Griffa A, Golay P, Palix J, Alameda L, Moulin V, Hagmann P, Do KQ, Conus P. Frontal cortical thickness correlates positively with impulsivity in early psychosis male patients. Early Interv Psychiatry 2019; 13:848-852. [PMID: 29770569 DOI: 10.1111/eip.12678] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2017] [Revised: 01/16/2018] [Accepted: 03/13/2018] [Indexed: 11/28/2022]
Abstract
AIM Impulsive behaviours, which are frequent in young people suffering from psychosis have been linked to risky and violent behaviours and participate to the burden of psychotic illness. Given that morphological brain correlates of impulsivity in schizophrenia have been poorly investigated especially in young adults, the aim of this study was to investigate the relationship between impulsivity and cortical thickness in early psychosis (EP) patients. METHOD A total of 17 male subjects in the early phase of psychosis were recruited. Impulsivity was assessed with the Lecrubier Impulsivity Rating Scale. Mean cortical thickness was extracted from magnetic resonance imaging brain scans, using surface-based methods. RESULTS Mean cortical thickness in the frontal lobe correlated positively with mean impulsivity in EP male patients. CONCLUSION Our results suggest that psychotic subjects exhibiting higher impulsivity have larger frontal cortical thickness, which may pave the way towards the identification of patients with a higher risk to display impulsive behaviours.
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Affiliation(s)
- Philipp S Baumann
- Department of Psychiatry, Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Department of Psychiatry, Service of General Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Paul Klauser
- Department of Psychiatry, Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Department of Psychiatry, Service of General Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Alessandra Griffa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Philippe Golay
- Department of Psychiatry, Service of General Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Service of Community Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Julie Palix
- Department of Psychiatry, Unit for Research in Legal Psychiatry and Psychology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Luis Alameda
- Department of Psychiatry, Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Lausanne University Hospital (CHUV), Lausanne, Switzerland.,Department of Psychiatry, Service of General Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Valérie Moulin
- Department of Psychiatry, Unit for Research in Legal Psychiatry and Psychology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Patric Hagmann
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Kim Q Do
- Department of Psychiatry, Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Philippe Conus
- Department of Psychiatry, Service of General Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
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Mullier E, Roine T, Griffa A, Xin L, Baumann PS, Klauser P, Cleusix M, Jenni R, Alemàn-Gómez Y, Gruetter R, Conus P, Do KQ, Hagmann P. N-Acetyl-Cysteine Supplementation Improves Functional Connectivity Within the Cingulate Cortex in Early Psychosis: A Pilot Study. Int J Neuropsychopharmacol 2019; 22:478-487. [PMID: 31283822 PMCID: PMC6672595 DOI: 10.1093/ijnp/pyz022] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 04/10/2019] [Accepted: 06/26/2019] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND There is increasing evidence that redox dysregulation, which can lead to oxidative stress and eventually to impairment of oligodendrocytes and parvalbumin interneurons, may underlie brain connectivity alterations in schizophrenia. Accordingly, we previously reported that levels of brain antioxidant glutathione in the medial prefrontal cortex were positively correlated with increased functional connectivity along the cingulum bundle in healthy controls but not in early psychosis patients. In a recent randomized controlled trial, we observed that 6-month supplementation with a glutathione precursor, N-acetyl-cysteine, increased brain glutathione levels and improved symptomatic expression and processing speed. METHODS We investigated the effect of N-acetyl-cysteine supplementation on the functional connectivity between regions of the cingulate cortex, which have been linked to positive symptoms and processing speed decline. In this pilot study, we compared structural connectivity and resting-state functional connectivity between early psychosis patients treated with 6-month N-acetyl-cysteine (n = 9) or placebo (n = 11) supplementation with sex- and age-matched healthy control subjects (n = 74). RESULTS We observed that 6-month N-acetyl-cysteine supplementation increases functional connectivity along the cingulum and more precisely between the caudal anterior part and the isthmus of the cingulate cortex. These functional changes can be partially explained by an increase of centrality of these regions in the functional brain network. CONCLUSIONS N-acetyl-cysteine supplementation has a positive effect on functional connectivity within the cingulate cortex in early psychosis patients. To our knowledge, this is the first study suggesting that increased brain glutathione levels via N-acetyl-cysteine supplementation may improve brain functional connectivity.
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Affiliation(s)
- Emeline Mullier
- Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland,Correspondence: Emeline Mullier, Centre de recherche en Radiologie RC7, CHUV, Rue du Bugnon 46, 1011 Lausanne, Suisse ()
| | - Timo Roine
- Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland,Turku Brain and Mind Center, University of Turku, Turku, Finland,Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Alessandra Griffa
- Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland,Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research (CNCR), VU Amsterdam, Amsterdam, The Netherlands
| | - Lijing Xin
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Philipp S Baumann
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Paul Klauser
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Martine Cleusix
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Raoul Jenni
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Yasser Alemàn-Gómez
- Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland,Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland,Medical Image Analysis Laboratory (MIAL), Centre d’Imagerie BioMédicale (CIBM), Lausanne, Switzerland
| | - Rolf Gruetter
- Laboratory of Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Philippe Conus
- Treatment and Early Intervention in Psychosis Program (TIPP), Service of General Psychiatry, Department of Psychiatry, Lausanne, Switzerland
| | - Kim Q Do
- Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland,Treatment and Early Intervention in Psychosis Program (TIPP), Service of General Psychiatry, Department of Psychiatry, Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
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Betzel RF, Griffa A, Hagmann P, Mišić B. Distance-dependent consensus thresholds for generating group-representative structural brain networks. Netw Neurosci 2019; 3:475-496. [PMID: 30984903 PMCID: PMC6444521 DOI: 10.1162/netn_a_00075] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Accepted: 12/03/2018] [Indexed: 12/16/2022] Open
Abstract
Large-scale structural brain networks encode white matter connectivity patterns among distributed brain areas. These connection patterns are believed to support cognitive processes and, when compromised, can lead to neurocognitive deficits and maladaptive behavior. A powerful approach for studying the organizing principles of brain networks is to construct group-representative networks from multisubject cohorts. Doing so amplifies signal to noise ratios and provides a clearer picture of brain network organization. Here, we show that current approaches for generating sparse group-representative networks overestimate the proportion of short-range connections present in a network and, as a result, fail to match subject-level networks along a wide range of network statistics. We present an alternative approach that preserves the connection-length distribution of individual subjects. We have used this method in previous papers to generate group-representative networks, though to date its performance has not been appropriately benchmarked and compared against other methods. As a result of this simple modification, the networks generated using this approach successfully recapitulate subject-level properties, outperforming similar approaches by better preserving features that promote integrative brain function rather than segregative. The method developed here holds promise for future studies investigating basic organizational principles and features of large-scale structural brain networks.
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Affiliation(s)
- Richard F. Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- Cognitive Science Program, Indiana University, Bloomington, IN, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Network Science Institute, Indiana University, Bloomington, IN, USA
| | - Alessandra Griffa
- Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands
| | - Patric Hagmann
- Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Bratislav Mišić
- Montréal Neurological Institute, McGill University, Montréal, Quebec, Canada
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35
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Griffa A, Baumann PS, Klauser P, Mullier E, Cleusix M, Jenni R, van den Heuvel MP, Do KQ, Conus P, Hagmann P. Brain connectivity alterations in early psychosis: from clinical to neuroimaging staging. Transl Psychiatry 2019; 9:62. [PMID: 30718455 PMCID: PMC6362225 DOI: 10.1038/s41398-019-0392-y] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 01/10/2019] [Indexed: 12/11/2022] Open
Abstract
Early in the course of psychosis, alterations in brain connectivity accompany the emergence of psychiatric symptoms and cognitive impairments, including processing speed. The clinical-staging model is a refined form of diagnosis that places the patient along a continuum of illness conditions, which allows stage-specific interventions with the potential of improving patient care and outcome. This cross-sectional study investigates brain connectivity features that characterize the clinical stages following a first psychotic episode. Structural brain networks were derived from diffusion-weighted MRI for 71 early-psychosis patients and 76 healthy controls. Patients were classified into stage II (first-episode), IIIa (incomplete remission), IIIb (one relapse), and IIIc (two or more relapses), according to the course of the illness until the time of scanning. Brain connectivity measures and diffusion parameters (fractional anisotropy, apparent diffusion coefficient) were investigated using general linear models and sparse linear discriminant analysis (sLDA), studying distinct subgroups of patients who were at specific stages of early psychosis. We found that brain connectivity impairments were more severe in clinical stages following the first-psychosis episode (stages IIIa, IIIb, IIIc) than in first-episode psychosis (stage II) patients. These alterations were spatially diffuse but converged on a set of vulnerable regions, whose inter-connectivity selectively correlated with processing speed in patients and controls. The sLDA suggested that relapsing-remitting (stages IIIb, IIIc) and non-remitting (stage IIIa) patients are characterized by distinct dysconnectivity profiles. Our results indicate that neuroimaging markers of brain dysconnectivity in early psychosis may reflect the heterogeneity of the illness and provide a connectomics signature of the clinical-staging model.
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Affiliation(s)
- Alessandra Griffa
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland. .,Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands.
| | - Philipp S. Baumann
- 0000 0001 0423 4662grid.8515.9Service of General Psychiatry and Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Paul Klauser
- 0000 0001 0423 4662grid.8515.9Service of General Psychiatry and Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Emeline Mullier
- 0000 0001 0423 4662grid.8515.9Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Martine Cleusix
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Raoul Jenni
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Martijn P. van den Heuvel
- grid.484519.5Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands
| | - Kim Q. Do
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Philippe Conus
- 0000 0001 0423 4662grid.8515.9Service of General Psychiatry and Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Patric Hagmann
- 0000 0001 0423 4662grid.8515.9Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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Abstract
Over the past decades, network neuroscience has played a fundamental role in the understanding of large-scale brain connectivity architecture. Brains, and more generally nervous systems, can be modeled as sets of elements (neurons, assemblies, or cortical chunks) that dynamically interact through a highly structured and adaptive neurocircuitry. An interesting property of neural networks is that elements rich in connections are central to the network organization and tend to interconnect strongly with each other, forming so-called rich clubs. The ubiquity of rich-club organization across different species and scales of investigation suggests that this topology could be a distinctive feature of biological systems with information processing capabilities. This review surveys recent neuroimaging, computational, and cross-species comparative literature to offer an insight into the function and origin of rich-club architecture in nervous systems, discussing its relevance to human cognition and behavior, and vulnerability to brain disorders.
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Affiliation(s)
- Alessandra Griffa
- Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, The Netherlands
| | - Martijn P Van den Heuvel
- Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, The Netherlands; Department of Clinical Genetics, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
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Legdeur N, Badissi M, Carter SF, de Crom S, van de Kreeke A, Vreeswijk R, Trappenburg MC, Oudega ML, Koek HL, van Campen JP, Keijsers CJPW, Amadi C, Hinz R, Gordon MF, Novak G, Podhorna J, Serné E, Verbraak F, Yaqub M, Hillebrand A, Griffa A, Pendleton N, Kramer SE, Teunissen CE, Lammertsma A, Barkhof F, van Berckel BNM, Scheltens P, Muller M, Maier AB, Herholz K, Visser PJ. Resilience to cognitive impairment in the oldest-old: design of the EMIF-AD 90+ study. BMC Geriatr 2018; 18:289. [PMID: 30477432 PMCID: PMC6258163 DOI: 10.1186/s12877-018-0984-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 11/15/2018] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND The oldest-old (subjects aged 90 years and older) population represents the fastest growing segment of society and shows a high dementia prevalence rate of up to 40%. Only a few studies have investigated protective factors for cognitive impairment in the oldest-old. The EMIF-AD 90+ Study aims to identify factors associated with resilience to cognitive impairment in the oldest-old. In this paper we reviewed previous studies on cognitive resilience in the oldest-old and described the design of the EMIF-AD 90+ Study. METHODS The EMIF-AD 90+ Study aimed to enroll 80 cognitively normal subjects and 40 subjects with cognitive impairment aged 90 years or older. Cognitive impairment was operationalized as amnestic mild cognitive impairment (aMCI), or possible or probable Alzheimer's Disease (AD). The study was part of the European Medical Information Framework for AD (EMIF-AD) and was conducted at the Amsterdam University Medical Centers (UMC) and at the University of Manchester. We will test whether cognitive resilience is associated with cognitive reserve, vascular comorbidities, mood, sleep, sensory system capacity, physical performance and capacity, genetic risk factors, hallmarks of ageing, and markers of neurodegeneration. Markers of neurodegeneration included an amyloid positron emission tomography, amyloid β and tau in cerebrospinal fluid/blood and neurophysiological measures. DISCUSSION The EMIF-AD 90+ Study will extend our knowledge on resilience to cognitive impairment in the oldest-old by extensive phenotyping of the subjects and the measurement of a wide range of potential protective factors, hallmarks of aging and markers of neurodegeneration. TRIAL REGISTRATION Nederlands Trial Register NTR5867 . Registered 20 May 2016.
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Affiliation(s)
- Nienke Legdeur
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Maryam Badissi
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Stephen F. Carter
- Wolfson Molecular Imaging Centre, Division of Neuroscience & Experimental Psychology, University of Manchester, Manchester, UK
| | - Sophie de Crom
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Aleid van de Kreeke
- Department of Ophthalmology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Ralph Vreeswijk
- Department of Geriatric Medicine, Spaarne Gasthuis, Haarlem, The Netherlands
| | | | - Mardien L. Oudega
- Department of Psychiatry, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Huiberdina L. Koek
- Department of Geriatric Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jos P. van Campen
- Department of Geriatric Medicine, MC Slotervaart Hospital, Amsterdam, The Netherlands
| | | | - Chinenye Amadi
- Wolfson Molecular Imaging Centre, Division of Neuroscience & Experimental Psychology, University of Manchester, Manchester, UK
| | - Rainer Hinz
- Wolfson Molecular Imaging Centre, Division of Neuroscience & Experimental Psychology, University of Manchester, Manchester, UK
| | | | - Gerald Novak
- Janssen Pharmaceutical Research and Development, Titusville, NJ USA
| | - Jana Podhorna
- Boehringer Ingelheim International GmbH, Ingelheim/Rhein, Germany
| | - Erik Serné
- Department of Internal Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Frank Verbraak
- Department of Ophthalmology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Alessandra Griffa
- Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neuroscience and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Neil Pendleton
- Wolfson Molecular Imaging Centre, Division of Neuroscience & Experimental Psychology, University of Manchester, Manchester, UK
| | - Sophia E. Kramer
- Department of Otolaryngology-Head and Neck Surgery, Section Ear & Hearing, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry Laboratory, Department of Clinical chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Adriaan Lammertsma
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Bart N. M. van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Majon Muller
- Department of Internal Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Andrea B. Maier
- Department of Medicine and Aged Care, @AgeMelbourne, Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia
- Department of Human Movement Sciences, @AgeAmsterdam, Amsterdam Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Karl Herholz
- Wolfson Molecular Imaging Centre, Division of Neuroscience & Experimental Psychology, University of Manchester, Manchester, UK
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, PO Box 7057, 1007 MB Amsterdam, the Netherlands
- Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
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Klauser P, Xin L, Fournier M, Griffa A, Cleusix M, Jenni R, Cuenod M, Gruetter R, Hagmann P, Conus P, Baumann PS, Do KQ. N-acetylcysteine add-on treatment leads to an improvement of fornix white matter integrity in early psychosis: a double-blind randomized placebo-controlled trial. Transl Psychiatry 2018; 8:220. [PMID: 30315150 PMCID: PMC6185923 DOI: 10.1038/s41398-018-0266-8] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 09/05/2018] [Accepted: 09/10/2018] [Indexed: 11/09/2022] Open
Abstract
Mechanism-based treatments for schizophrenia are needed, and increasing evidence suggests that oxidative stress may be a target. Previous research has shown that N-acetylcysteine (NAC), an antioxidant and glutathione (GSH) precursor almost devoid of side effects, improved negative symptoms, decreased the side effects of antipsychotics, and improved mismatch negativity and local neural synchronization in chronic schizophrenia. In a recent double-blind randomized placebo-controlled trial by Conus et al., early psychosis patients received NAC add-on therapy (2700 mg/day) for 6 months. Compared with placebo-treated controls, NAC patients showed significant improvements in neurocognition (processing speed) and a reduction of positive symptoms among patients with high peripheral oxidative status. NAC also led to a 23% increase in GSH levels in the medial prefrontal cortex (GSHmPFC) as measured by 1H magnetic resonance spectroscopy. A subgroup of the patients in this study were also scanned with multimodal MR imaging (spectroscopy, diffusion, and structural) at baseline (prior to NAC/placebo) and after 6 months of add-on treatment. Based on prior translational research, we hypothesized that NAC would protect white matter integrity in the fornix. A group × time interaction indicated a difference in the 6-month evolution of white matter integrity (as measured by generalized fractional anisotropy, gFA) in favor of the NAC group, which showed an 11% increase. The increase in gFA correlated with an increase in GSHmPFC over the same 6-month period. In this secondary study, we suggest that NAC add-on treatment may be a safe and effective way to protect white matter integrity in early psychosis patients.
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Affiliation(s)
- Paul Klauser
- 0000 0001 0423 4662grid.8515.9Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,National Center of Competence in Research (NCCR) “SYNAPSY – The Synaptic Bases of Mental Diseases”, Lausanne, Switzerland
| | - Lijing Xin
- 0000000121839049grid.5333.6Animal Imaging and Technology Core (AIT), Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Margot Fournier
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,National Center of Competence in Research (NCCR) “SYNAPSY – The Synaptic Bases of Mental Diseases”, Lausanne, Switzerland
| | - Alessandra Griffa
- 0000 0001 0423 4662grid.8515.9Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland ,Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Martine Cleusix
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,National Center of Competence in Research (NCCR) “SYNAPSY – The Synaptic Bases of Mental Diseases”, Lausanne, Switzerland
| | - Raoul Jenni
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,National Center of Competence in Research (NCCR) “SYNAPSY – The Synaptic Bases of Mental Diseases”, Lausanne, Switzerland
| | - Michel Cuenod
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Rolf Gruetter
- 0000000121839049grid.5333.6Animal Imaging and Technology Core (AIT), Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland ,0000 0001 0423 4662grid.8515.9Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Patric Hagmann
- National Center of Competence in Research (NCCR) “SYNAPSY – The Synaptic Bases of Mental Diseases”, Lausanne, Switzerland ,0000 0001 0423 4662grid.8515.9Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
| | - Philippe Conus
- 0000 0001 0423 4662grid.8515.9Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,National Center of Competence in Research (NCCR) “SYNAPSY – The Synaptic Bases of Mental Diseases”, Lausanne, Switzerland
| | - Philipp S. Baumann
- 0000 0001 0423 4662grid.8515.9Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,National Center of Competence in Research (NCCR) “SYNAPSY – The Synaptic Bases of Mental Diseases”, Lausanne, Switzerland
| | - Kim Q. Do
- 0000 0001 0423 4662grid.8515.9Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland ,National Center of Competence in Research (NCCR) “SYNAPSY – The Synaptic Bases of Mental Diseases”, Lausanne, Switzerland
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Rosenthal G, Váša F, Griffa A, Hagmann P, Amico E, Goñi J, Avidan G, Sporns O. Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes. Nat Commun 2018; 9:2178. [PMID: 29872218 PMCID: PMC5988787 DOI: 10.1038/s41467-018-04614-w] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2017] [Accepted: 04/18/2018] [Indexed: 01/01/2023] Open
Abstract
Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.
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Affiliation(s)
- Gideon Rosenthal
- Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, P.O.B. 653, 8410501, Beer-Sheva, Israel
- The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, P.O.B. 653, 8410501, Beer-Sheva, Israel
| | - František Váša
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, CB2 0SZ, UK
| | - Alessandra Griffa
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), 1011, Lausanne, Switzerland
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), 1011, Lausanne, Switzerland
| | - Enrico Amico
- School of Industrial Engineering, Purdue University, West-Lafayette, 47907, IN, USA
- Purdue Institute for Integrative Neuroscience, Purdue University, West-Lafayette, 47907, IN, USA
| | - Joaquín Goñi
- School of Industrial Engineering, Purdue University, West-Lafayette, 47907, IN, USA
- Purdue Institute for Integrative Neuroscience, Purdue University, West-Lafayette, 47907, IN, USA
- Weldon School of Biomedical Engineering, Purdue University, West-Lafayette, 47907, IN, USA
| | - Galia Avidan
- Department of Cognitive and Brain Sciences, Ben-Gurion University of the Negev, P.O.B. 653, 8410501, Beer-Sheva, Israel
- The Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, P.O.B. 653, 8410501, Beer-Sheva, Israel
- Department of Psychology, Ben-Gurion University of the Negev, P.O.B. 653, 8410501, Beer-Sheva, Israel
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA.
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40
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Griffa A. Rich-club neurocircuitry: function, evolution, and vulnerability. Dialogues Clin Neurosci 2018; 20:121-132. [PMID: 30250389 PMCID: PMC6136122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Over the past decades, network neuroscience has played a fundamental role in the understanding of large-scale brain connectivity architecture. Brains, and more generally nervous systems, can be modeled as sets of elements (neurons, assemblies, or cortical chunks) that dynamically interact through a highly structured and adaptive neurocircuitry. An interesting property of neural networks is that elements rich in connections are central to the network organization and tend to interconnect strongly with each other, forming so-called rich clubs. The ubiquity of rich-club organization across different species and scales of investigation suggests that this topology could be a distinctive feature of biological systems with information processing capabilities. This review surveys recent neuroimaging, computational, and cross-species comparative literature to offer an insight into the function and origin of rich-club architecture in nervous systems, discussing its relevance to human cognition and behavior, and vulnerability to brain disorders.
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Affiliation(s)
- Alessandra Griffa
- Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, The Netherlands
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41
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Silva Pereira S, Hindriks R, Mühlberg S, Maris E, van Ede F, Griffa A, Hagmann P, Deco G. Effect of Field Spread on Resting-State Magneto Encephalography Functional Network Analysis: A Computational Modeling Study. Brain Connect 2017; 7:541-557. [PMID: 28875718 DOI: 10.1089/brain.2017.0525] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
A popular way to analyze resting-state electroencephalography (EEG) and magneto encephalography (MEG) data is to treat them as a functional network in which sensors are identified with nodes and the interaction between channel time series and the network connections. Although conceptually appealing, the network-theoretical approach to sensor-level EEG and MEG data is challenged by the fact that EEG and MEG time series are mixtures of source activity. It is, therefore, of interest to assess the relationship between functional networks of source activity and the ensuing sensor-level networks. Since these topological features are of high interest in experimental studies, we address the question of to what extent the network topology can be reconstructed from sensor-level functional connectivity (FC) measures in case of MEG data. Simple simulations that consider only a small number of regions do not allow to assess network properties; therefore, we use a diffusion magnetic resonance imaging-constrained whole-brain computational model of resting-state activity. Our motivation lies behind the fact that still many contributions found in the literature perform network analysis at sensor level, and we aim at showing the discrepancies between source- and sensor-level network topologies by using realistic simulations of resting-state cortical activity. Our main findings are that the effect of field spread on network topology depends on the type of interaction (instantaneous or lagged) and leads to an underestimation of lagged FC at sensor level due to instantaneous mixing of cortical signals, instantaneous interaction is more sensitive to field spread than lagged interaction, and discrepancies are reduced when using planar gradiometers rather than axial gradiometers. We, therefore, recommend using lagged interaction measures on planar gradiometer data when investigating network properties of resting-state sensor-level MEG data.
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Affiliation(s)
- Silvana Silva Pereira
- 1 Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
| | - Rikkert Hindriks
- 1 Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
| | - Stefanie Mühlberg
- 1 Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
| | - Eric Maris
- 2 Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Freek van Ede
- 2 Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Alessandra Griffa
- 3 Department of Radiology, Lausanne University Hospital (CHUV-UNIL), Lausanne, Switzerland .,4 Signal Processing Laboratory 5 , Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Patric Hagmann
- 3 Department of Radiology, Lausanne University Hospital (CHUV-UNIL), Lausanne, Switzerland
| | - Gustavo Deco
- 1 Computational Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain .,5 Institució Catalana de la Recerca i Estudis Avanats (ICREA), Barcelona, Spain
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Vázquez-Rodríguez B, Avena-Koenigsberger A, Sporns O, Griffa A, Hagmann P, Larralde H. Stochastic resonance at criticality in a network model of the human cortex. Sci Rep 2017; 7:13020. [PMID: 29026142 PMCID: PMC5638949 DOI: 10.1038/s41598-017-13400-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Accepted: 09/22/2017] [Indexed: 11/24/2022] Open
Abstract
Stochastic resonance is a phenomenon in which noise enhances the response of a system to an input signal. The brain is an example of a system that has to detect and transmit signals in a noisy environment, suggesting that it is a good candidate to take advantage of stochastic resonance. In this work, we aim to identify the optimal levels of noise that promote signal transmission through a simple network model of the human brain. Specifically, using a dynamic model implemented on an anatomical brain network (connectome), we investigate the similarity between an input signal and a signal that has traveled across the network while the system is subject to different noise levels. We find that non-zero levels of noise enhance the similarity between the input signal and the signal that has traveled through the system. The optimal noise level is not unique; rather, there is a set of parameter values at which the information is transmitted with greater precision, this set corresponds to the parameter values that place the system in a critical regime. The multiplicity of critical points in our model allows it to adapt to different noise situations and remain at criticality.
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Affiliation(s)
| | | | - Olaf Sporns
- Indiana University, Department of Psychological and Brain Sciences, Bloomington IN, USA
| | - Alessandra Griffa
- Lausanne University Hospital (CHUV), Department of Radiology, Lausanne, Switzerland.,University of Lausanne (UNIL), Lausanne, Switzerland
| | - Patric Hagmann
- Lausanne University Hospital (CHUV), Department of Radiology, Lausanne, Switzerland.,University of Lausanne (UNIL), Lausanne, Switzerland
| | - Hernán Larralde
- Universidad Nacional Autónoma de México, Instituto de Ciencias Físicas, Cuernavaca, Mexico
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Csoma A, Kőrösi A, Rétvári G, Heszberger Z, Bíró J, Slíz M, Avena-Koenigsberger A, Griffa A, Hagmann P, Gulyás A. Routes Obey Hierarchy in Complex Networks. Sci Rep 2017; 7:7243. [PMID: 28775278 PMCID: PMC5543142 DOI: 10.1038/s41598-017-07412-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Accepted: 06/23/2017] [Indexed: 12/21/2022] Open
Abstract
The last two decades of network science have discovered stunning similarities in the topological characteristics of real life networks (many biological, social, transportation and organizational networks) on a strong empirical basis. However our knowledge about the operational paths used in these networks is very limited, which prohibits the proper understanding of the principles of their functioning. Today, the most widely adopted hypothesis about the structure of the operational paths is the shortest path assumption. Here we present a striking result that the paths in various networks are significantly stretched compared to their shortest counterparts. Stretch distributions are also found to be extremely similar. This phenomenon is empirically confirmed on four networks from diverse areas of life. We also identify the high-level path selection rules nature seems to use when picking its paths.
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Affiliation(s)
- Attila Csoma
- Budapest University of Technology and Economics, Dept. of Telecommunications and Media Informatics, MTA-BME Information Systems Research Group, H-1117, Budapest, Magyar tudósok krt. 2, Hungary
| | - Attila Kőrösi
- Budapest University of Technology and Economics, Dept. of Telecommunications and Media Informatics, MTA-BME Information Systems Research Group, H-1117, Budapest, Magyar tudósok krt. 2, Hungary
| | - Gábor Rétvári
- Budapest University of Technology and Economics, Dept. of Telecommunications and Media Informatics, MTA-BME Information Systems Research Group, H-1117, Budapest, Magyar tudósok krt. 2, Hungary
| | - Zalán Heszberger
- Budapest University of Technology and Economics, Dept. of Telecommunications and Media Informatics, MTA-BME Information Systems Research Group, H-1117, Budapest, Magyar tudósok krt. 2, Hungary
| | - József Bíró
- Budapest University of Technology and Economics, Dept. of Telecommunications and Media Informatics, MTA-BME Information Systems Research Group, H-1117, Budapest, Magyar tudósok krt. 2, Hungary
| | - Mariann Slíz
- Eötvös Loránd University, Institute of Hungarian Linguistics and Finno-Ugric Studies, H-1088, Budapest, Múzeum krt. 4/A, Hungary
| | | | - Alessandra Griffa
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, Netherlands.,Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - András Gulyás
- Budapest University of Technology and Economics, Dept. of Telecommunications and Media Informatics, MTA-BME Information Systems Research Group, H-1117, Budapest, Magyar tudósok krt. 2, Hungary.
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44
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Friedrichs-Maeder CL, Griffa A, Schneider J, Hüppi PS, Truttmann A, Hagmann P. Exploring the role of white matter connectivity in cortex maturation. PLoS One 2017; 12:e0177466. [PMID: 28545040 PMCID: PMC5435226 DOI: 10.1371/journal.pone.0177466] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 04/27/2017] [Indexed: 12/18/2022] Open
Abstract
The maturation of the cortical gray matter (GM) and white matter (WM) are described as sequential processes following multiple, but distinct rules. However, neither the mechanisms driving brain maturation processes, nor the relationship between GM and WM maturation are well understood. Here we use connectomics and two MRI measures reflecting maturation related changes in cerebral microstructure, namely the Apparent Diffusion Coefficient (ADC) and the T1 relaxation time (T1), to study brain development. We report that the advancement of GM and WM maturation are inter-related and depend on the underlying brain connectivity architecture. Particularly, GM regions and their incident WM connections show corresponding maturation levels, which is also observed for GM regions connected through a WM tract. Based on these observations, we propose a simple computational model supporting a key role for the connectome in propagating maturation signals sequentially from external stimuli, through primary sensory structures to higher order functional cortices.
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Affiliation(s)
| | - Alessandra Griffa
- Department of Radiology, Centre Hospitalier Universitaire Vaudoise (CHUV), Lausanne, Switzerland
- Signal Processing Laboratory (LTSS), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Juliane Schneider
- Clinic of Neonatology and Follow-up, Department of Pediatrics, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
- Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, Canada
| | - Petra Susan Hüppi
- Division of Development and Growth, Department of Pediatrics, University of Geneva, Geneva, Switzerland
| | - Anita Truttmann
- Clinic of Neonatology and Follow-up, Department of Pediatrics, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudoise (CHUV), Lausanne, Switzerland
- Signal Processing Laboratory (LTSS), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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45
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Adhikari MH, Hacker CD, Siegel JS, Griffa A, Hagmann P, Deco G, Corbetta M. Decreased integration and information capacity in stroke measured by whole brain models of resting state activity. Brain 2017; 140:1068-1085. [PMID: 28334882 DOI: 10.1093/brain/awx021] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Accepted: 12/21/2016] [Indexed: 11/14/2022] Open
Abstract
While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to represent stimuli and task states, and that information capacity measured through whole brain models is a theory-driven measure of processing capacity that could be used as a biomarker of injury for outcome prediction or target for rehabilitation intervention.
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Affiliation(s)
- Mohit H Adhikari
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Ramon Trias Fargas, 25-27, Barcelona, 08005, Spain
| | - Carl D Hacker
- Department of Bioengineering, Washington University Saint Louis, USA
| | - Josh S Siegel
- Department of Neurology, Washington University School of Medicine Saint Louis, USA
| | - Alessandra Griffa
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), 1011 Lausanne, Switzerland.,Signal Processing Lab 5, Ecole Polytechnique Federale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), 1011 Lausanne, Switzerland.,Signal Processing Lab 5, Ecole Polytechnique Federale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Ramon Trias Fargas, 25-27, Barcelona, 08005, Spain.,Institucio Catalana de la Recerca I Estudis Avancats (ICREA), University of Pompeu Fabra, Passeig Lluis Companys 23, Barcelona, 08010, Spain
| | - Maurizio Corbetta
- Department of Bioengineering, Washington University Saint Louis, USA.,Department of Neurology, Washington University School of Medicine Saint Louis, USA.,Departments of Radiology and Neuroscience, Washington University School of Medicine Saint Louis, USA.,Department of Neuroscience, University of Padua, Italy
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46
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Griffa A, Ricaud B, Benzi K, Bresson X, Daducci A, Vandergheynst P, Thiran JP, Hagmann P. Transient networks of spatio-temporal connectivity map communication pathways in brain functional systems. Neuroimage 2017; 155:490-502. [PMID: 28412440 DOI: 10.1016/j.neuroimage.2017.04.015] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 04/06/2017] [Indexed: 12/20/2022] Open
Abstract
The study of brain dynamics enables us to characterize the time-varying functional connectivity among distinct neural groups. However, current methods suffer from the absence of structural connectivity information. We propose to integrate infra-slow neural oscillations and anatomical-connectivity maps, as derived from functional and diffusion MRI, in a multilayer-graph framework that captures transient networks of spatio-temporal connectivity. These networks group anatomically wired and temporary synchronized brain regions and encode the propagation of functional activity on the structural connectome. In a group of 71 healthy subjects, we find that these transient networks demonstrate power-law spatial and temporal size, globally organize into well-known functional systems and describe wave-like trajectories of activation across anatomically connected regions. Within the transient networks, activity propagates through polysynaptic paths that include selective ensembles of structural connections and differ from the structural shortest paths. In the light of the communication-through-coherence principle, the identified spatio-temporal networks could encode communication channels' selection and neural assemblies, which deserves further attention. This work contributes to the understanding of brain structure-function relationships by considering the time-varying nature of resting-state interactions on the axonal scaffold, and it offers a convenient framework to study large-scale communication mechanisms and functional dynamics.
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Affiliation(s)
- Alessandra Griffa
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne 1011, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland.
| | - Benjamin Ricaud
- Signal Processing Laboratory 2 (LTS2), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Kirell Benzi
- Signal Processing Laboratory 2 (LTS2), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Xavier Bresson
- Signal Processing Laboratory 2 (LTS2), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Alessandro Daducci
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Pierre Vandergheynst
- Signal Processing Laboratory 2 (LTS2), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne 1011, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne 1011, Switzerland; Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
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47
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Baumann PS, Griffa A, Fournier M, Golay P, Ferrari C, Alameda L, Cuenod M, Thiran JP, Hagmann P, Do KQ, Conus P. Impaired fornix-hippocampus integrity is linked to peripheral glutathione peroxidase in early psychosis. Transl Psychiatry 2016; 6:e859. [PMID: 27459724 PMCID: PMC5545707 DOI: 10.1038/tp.2016.117] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2015] [Revised: 03/17/2016] [Accepted: 04/15/2016] [Indexed: 12/19/2022] Open
Abstract
Several lines of evidence implicate the fornix-hippocampus circuit in schizophrenia. In early-phase psychosis, this circuit has not been extensively investigated and the underlying mechanisms affecting the circuit are unknown. The hippocampus and fornix are vulnerable to oxidative stress at peripuberty in a glutathione (GSH)-deficient animal model. The purposes of the current study were to assess the integrity of the fornix-hippocampus circuit in early-psychosis patients (EP), and to study its relationship with peripheral redox markers. Diffusion spectrum imaging and T1-weighted magnetic resonance imaging (MRI) were used to assess the fornix and hippocampus in 42 EP patients compared with 42 gender- and age-matched healthy controls. Generalized fractional anisotropy (gFA) and volumetric properties were used to measure fornix and hippocampal integrity, respectively. Correlation analysis was used to quantify the relationship of gFA in the fornix and hippocampal volume, with blood GSH levels and glutathione peroxidase (GPx) activity. Patients compared with controls exhibited lower gFA in the fornix as well as smaller volume in the hippocampus. In EP, but not in controls, smaller hippocampal volume was associated with high GPx activity. Disruption of the fornix-hippocampus circuit is already present in the early stages of psychosis. Higher blood GPx activity is associated with smaller hippocampal volume, which may support a role of oxidative stress in disease mechanisms.
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Affiliation(s)
- P S Baumann
- Department of Psychiatry, Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
- Department of Psychiatry, Service of General Psychiatry, Centre Hospitalier Universitaire Vaudois, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - A Griffa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - M Fournier
- Department of Psychiatry, Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - P Golay
- Department of Psychiatry, Service of General Psychiatry, Centre Hospitalier Universitaire Vaudois, Lausanne University Hospital (CHUV), Lausanne, Switzerland
- Service of Community Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - C Ferrari
- Department of Psychiatry, Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - L Alameda
- Department of Psychiatry, Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
- Department of Psychiatry, Service of General Psychiatry, Centre Hospitalier Universitaire Vaudois, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - M Cuenod
- Department of Psychiatry, Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - J-P Thiran
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - P Hagmann
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - K Q Do
- Department of Psychiatry, Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - P Conus
- Department of Psychiatry, Service of General Psychiatry, Centre Hospitalier Universitaire Vaudois, Lausanne University Hospital (CHUV), Lausanne, Switzerland
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48
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Fischi-Gomez E, Muñoz-Moreno E, Vasung L, Griffa A, Borradori-Tolsa C, Monnier M, Lazeyras F, Thiran JP, Hüppi PS. Brain network characterization of high-risk preterm-born school-age children. Neuroimage Clin 2016; 11:195-209. [PMID: 26955515 PMCID: PMC4761723 DOI: 10.1016/j.nicl.2016.02.001] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2015] [Revised: 01/20/2016] [Accepted: 02/04/2016] [Indexed: 01/14/2023]
Abstract
Higher risk for long-term cognitive and behavioral impairments is one of the hallmarks of extreme prematurity (EP) and pregnancy-associated fetal adverse conditions such as intrauterine growth restriction (IUGR). While neurodevelopmental delay and abnormal brain function occur in the absence of overt brain lesions, these conditions have been recently associated with changes in microstructural brain development. Recent imaging studies indicate changes in brain connectivity, in particular involving the white matter fibers belonging to the cortico-basal ganglia-thalamic loop. Furthermore, EP and IUGR have been related to altered brain network architecture in childhood, with reduced network global capacity, global efficiency and average nodal strength. In this study, we used a connectome analysis to characterize the structural brain networks of these children, with a special focus on their topological organization. On one hand, we confirm the reduced averaged network node degree and strength due to EP and IUGR. On the other, the decomposition of the brain networks in an optimal set of clusters remained substantially different among groups, talking in favor of a different network community structure. However, and despite the different community structure, the brain networks of these high-risk school-age children maintained the typical small-world, rich-club and modularity characteristics in all cases. Thus, our results suggest that brain reorganizes after EP and IUGR, prioritizing a tight modular structure, to maintain the small-world, rich-club and modularity characteristics. By themselves, both extreme prematurity and IUGR bear a similar risk for neurocognitive and behavioral impairment, and the here defined modular network alterations confirm similar structural changes both by IUGR and EP at school age compared to control. Interestingly, the combination of both conditions (IUGR + EP) does not result in a worse outcome. In such cases, the alteration in network topology appears mainly driven by the effect of extreme prematurity, suggesting that these brain network alterations present at school age have their origin in a common critical period, both for intrauterine and extrauterine adverse conditions.
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Affiliation(s)
- Elda Fischi-Gomez
- Signal Processing Laboratory 5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Division of Development and Growth, Department of Pediatrics, University Hospital of Geneva, Geneva, Switzerland.
| | - Emma Muñoz-Moreno
- Fetal i+D Fetal Medicine Research Center, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona, Barcelona, Spain
| | - Lana Vasung
- Division of Development and Growth, Department of Pediatrics, University Hospital of Geneva, Geneva, Switzerland
| | - Alessandra Griffa
- Signal Processing Laboratory 5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology, University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Cristina Borradori-Tolsa
- Division of Development and Growth, Department of Pediatrics, University Hospital of Geneva, Geneva, Switzerland
| | - Maryline Monnier
- Follow-up Unit, Neonatology Service, Department of Pediatrics University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - François Lazeyras
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory 5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology, University Hospital Center (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Petra S Hüppi
- Division of Development and Growth, Department of Pediatrics, University Hospital of Geneva, Geneva, Switzerland
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49
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Betzel RF, Avena-Koenigsberger A, Goñi J, He Y, de Reus MA, Griffa A, Vértes PE, Mišic B, Thiran JP, Hagmann P, van den Heuvel M, Zuo XN, Bullmore ET, Sporns O. Generative models of the human connectome. Neuroimage 2016; 124:1054-1064. [PMID: 26427642 PMCID: PMC4655950 DOI: 10.1016/j.neuroimage.2015.09.041] [Citation(s) in RCA: 165] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2015] [Revised: 09/17/2015] [Accepted: 09/18/2015] [Indexed: 12/18/2022] Open
Abstract
The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan.
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Affiliation(s)
- Richard F Betzel
- Indiana University, Psychological and Brain Sciences, Bloomington IN, 47405, USA
| | | | - Joaquín Goñi
- Indiana University, Psychological and Brain Sciences, Bloomington IN, 47405, USA; Indiana University, Network Science Institute, Bloomington IN 47405, USA
| | - Ye He
- Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Marcel A de Reus
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Alessandra Griffa
- Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland; Signal Processing Lab 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Petra E Vértes
- Department of Psychiatry, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Bratislav Mišic
- Indiana University, Psychological and Brain Sciences, Bloomington IN, 47405, USA
| | - Jean-Philippe Thiran
- Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland; Signal Processing Lab 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland; Signal Processing Lab 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Martijn van den Heuvel
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Xi-Nian Zuo
- Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Edward T Bullmore
- Department of Psychiatry, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Olaf Sporns
- Indiana University, Psychological and Brain Sciences, Bloomington IN, 47405, USA; Indiana University, Network Science Institute, Bloomington IN 47405, USA.
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50
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Váša F, Griffa A, Scariati E, Schaer M, Urben S, Eliez S, Hagmann P. An affected core drives network integration deficits of the structural connectome in 22q11.2 deletion syndrome. Neuroimage Clin 2015; 10:239-49. [PMID: 26870660 PMCID: PMC4711395 DOI: 10.1016/j.nicl.2015.11.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Revised: 11/06/2015] [Accepted: 11/24/2015] [Indexed: 01/01/2023]
Abstract
Chromosome 22q11.2 deletion syndrome (22q11DS) is a genetic disease known to lead to cerebral structural alterations, which we study using the framework of the macroscopic white-matter connectome. We create weighted connectomes of 44 patients with 22q11DS and 44 healthy controls using diffusion tensor magnetic resonance imaging, and perform a weighted graph theoretical analysis. After confirming global network integration deficits in 22q11DS (previously identified using binary connectomes), we identify the spatial distribution of regions responsible for global deficits. Next, we further characterize the dysconnectivity of the deficient regions in terms of sub-network properties, and investigate their relevance with respect to clinical profiles. We define the subset of regions with decreased nodal integration (evaluated using the closeness centrality measure) as the affected core (A-core) of the 22q11DS structural connectome. A-core regions are broadly bilaterally symmetric and consist of numerous network hubs — chiefly parietal and frontal cortical, as well as subcortical regions. Using a simulated lesion approach, we demonstrate that these core regions and their connections are particularly important to efficient network communication. Moreover, these regions are generally densely connected, but less so in 22q11DS. These specific disturbances are associated to a rerouting of shortest network paths that circumvent the A-core in 22q11DS, “de-centralizing” the network. Finally, the efficiency and mean connectivity strength of an orbito-frontal/cingulate circuit, included in the affected regions, correlate negatively with the extent of negative symptoms in 22q11DS patients, revealing the clinical relevance of present findings. The identified A-core overlaps numerous regions previously identified as affected in 22q11DS as well as in schizophrenia, which approximately 30–40% of 22q11DS patients develop. Graph theory confirms reduced integration in 22q11.2 deletion syndrome (22q11DS). An “affected core” (A-core) of hub regions drives global integration deficits. The A-core is generally densely connected, but less so in 22q11DS. Shortest network paths are rerouted around the A-core in 22q11DS. Connectivity of a subset of A-core regions correlates with negative symptoms.
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Affiliation(s)
- František Váša
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Alessandra Griffa
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Elisa Scariati
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Marie Schaer
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Geneva, Switzerland; Stanford Cognitive and Systems Neuroscience Laboratory, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Sébastien Urben
- Service Universitaire de Psychiatrie de l'Enfant et de l'Adolescent (SUPEA), Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Stephan Eliez
- Office Médico-Pédagogique, Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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