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.
Relations between large-scale brain connectivity and effects of regional stimulation depend on collective dynamical state
Evaluation of Resting Spatio-Temporal Dynamics of a Neural Mass Model Using Resting fMRI Connectivity and EEG Microstates
Coincident pre- and postsynaptic activity modifies GABAergic synapses by postsynaptic changes in Cl- transporter activity
Plasticity and stability in neuronal output via changes in intrinsic excitability: it's what's inside that counts
Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources
FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data
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Measuring functional connectivity in MEG: a multivariate approach insensitive to linear source leakage
Anatomically-constrained tractography: improved diffusion MRI streamlines tractography through effective use of anatomical information
Resting-state functional connectivity emerges from structurally and dynamically shaped slow linear fluctuations
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