TY  - JOUR
AU  - Manos, Thanos
AU  - Diaz, Sandra
AU  - Fortel, Igor
AU  - Driscoll, Ira
AU  - Zhan, Liang
AU  - Leow, Alex
TI  - Enhanced simulations of whole-brain dynamics using hybrid resting-state structural connectomes
JO  - Frontiers in computational neuroscience
VL  - 17
SN  - 1662-5188
CY  - Lausanne
PB  - Frontiers Research Foundation
M1  - FZJ-2023-05834
SP  - 1295395
PY  - 2023
AB  - The human brain, composed of billions of neurons and synaptic connections, is an intricate network coordinating a sophisticated balance of excitatory and inhibitory activities between brain regions. The dynamical balance between excitation and inhibition is vital for adjusting neural input/output relationships in cortical networks and regulating the dynamic range of their responses to stimuli. To infer this balance using connectomics, we recently introduced a computational framework based on the Ising model, which was first developed to explain phase transitions in ferromagnets, and proposed a novel hybrid resting-state structural connectome (rsSC). Here, we show that a generative model based on the Kuramoto phase oscillator can be used to simulate static and dynamic functional connectomes (FC) with rsSC as the coupling weight coefficients, such that the simulated FC aligns well with the observed FC when compared with that simulated traditional structural connectome.
LB  - PUB:(DE-HGF)16
C6  - 38188355
UR  - <Go to ISI:>//WOS:001134314300001
DO  - DOI:10.3389/fncom.2023.1295395
UR  - https://juser.fz-juelich.de/record/1020019
ER  -