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.

Abstract

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.

Citation

Abeysuriya, R. G., Hadida, J., Sotiropoulos, S. N., Jbabdi, S., Becker, R., Hunt, B. A., Brookes, M. J., & Woolrich, M. W. (in press). A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks. PLoS Computational Biology, 14(2), Article e1006007. https://doi.org/10.1371/journal.pcbi.1006007

• Journal Article Type: Article
• Acceptance Date: Jan 28, 2018
• Online Publication Date: Feb 23, 2018
• Deposit Date: Feb 19, 2018
• Publicly Available Date: Feb 23, 2018
• Journal: PLoS Computational Biology
• Print ISSN: 1553-734X
• Electronic ISSN: 1553-7358
• Publisher: Public Library of Science
• Peer Reviewed: Peer Reviewed
• Volume: 14
• Issue: 2
• Article Number: e1006007
• DOI: https://doi.org/10.1371/journal.pcbi.1006007
• Public URL: https://nottingham-repository.worktribe.com/output/916191
• Publisher URL: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006007
• Contract Date: Feb 19, 2018