A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks
Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are faci...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science
2018
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| Online Access: | https://eprints.nottingham.ac.uk/49852/ |
| _version_ | 1848798093796966400 |
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| author | Abeysuriya, Romesh G. Hadida, Jonathan Sotiropoulos, Stamatios N. Jbabdi, Saad Becker, Robert Hunt, Benjamin A.E. Brookes, Matthew J. Woolrich, Mark W. |
| author_facet | Abeysuriya, Romesh G. Hadida, Jonathan Sotiropoulos, Stamatios N. Jbabdi, Saad Becker, Robert Hunt, Benjamin A.E. Brookes, Matthew J. Woolrich, Mark W. |
| author_sort | Abeysuriya, Romesh G. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP. |
| first_indexed | 2025-11-14T20:14:18Z |
| format | Article |
| id | nottingham-49852 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:14:18Z |
| publishDate | 2018 |
| publisher | Public Library of Science |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-498522018-03-14T10:19:37Z https://eprints.nottingham.ac.uk/49852/ A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks Abeysuriya, Romesh G. Hadida, Jonathan Sotiropoulos, Stamatios N. Jbabdi, Saad Becker, Robert Hunt, Benjamin A.E. Brookes, Matthew J. Woolrich, Mark W. Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP. Public Library of Science 2018-02-23 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/49852/8/file.pdf Abeysuriya, Romesh G., Hadida, Jonathan, Sotiropoulos, Stamatios N., Jbabdi, Saad, Becker, Robert, Hunt, Benjamin A.E., Brookes, Matthew J. and Woolrich, Mark W. (2018) A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks. PLoS Computational Biology, 14 (2). e1006007. ISSN 1553-7358 http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006007 doi:10.1371/journal.pcbi.1006007 doi:10.1371/journal.pcbi.1006007 |
| spellingShingle | Abeysuriya, Romesh G. Hadida, Jonathan Sotiropoulos, Stamatios N. Jbabdi, Saad Becker, Robert Hunt, Benjamin A.E. Brookes, Matthew J. Woolrich, Mark W. A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks |
| title | A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks |
| title_full | A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks |
| title_fullStr | A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks |
| title_full_unstemmed | A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks |
| title_short | A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks |
| title_sort | biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks |
| url | https://eprints.nottingham.ac.uk/49852/ https://eprints.nottingham.ac.uk/49852/ https://eprints.nottingham.ac.uk/49852/ |