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001020019 1001_ $$0P:(DE-Juel1)164577$$aManos, Thanos$$b0$$eCorresponding author
001020019 245__ $$aEnhanced simulations of whole-brain dynamics using hybrid resting-state structural connectomes
001020019 260__ $$aLausanne$$bFrontiers Research Foundation$$c2023
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001020019 520__ $$aThe human brain, composed of billions of neurons and synaptic connections, is an intricate network coordinating a sophisticated balance of excitatory and inhibitory activities between brain regions. The dynamical balance between excitation and inhibition is vital for adjusting neural input/output relationships in cortical networks and regulating the dynamic range of their responses to stimuli. To infer this balance using connectomics, we recently introduced a computational framework based on the Ising model, which was first developed to explain phase transitions in ferromagnets, and proposed a novel hybrid resting-state structural connectome (rsSC). Here, we show that a generative model based on the Kuramoto phase oscillator can be used to simulate static and dynamic functional connectomes (FC) with rsSC as the coupling weight coefficients, such that the simulated FC aligns well with the observed FC when compared with that simulated traditional structural connectome.
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001020019 7001_ $$0P:(DE-Juel1)165859$$aDiaz, Sandra$$b1$$ufzj
001020019 7001_ $$0P:(DE-HGF)0$$aFortel, Igor$$b2
001020019 7001_ $$0P:(DE-HGF)0$$aDriscoll, Ira$$b3
001020019 7001_ $$0P:(DE-HGF)0$$aZhan, Liang$$b4
001020019 7001_ $$0P:(DE-HGF)0$$aLeow, Alex$$b5
001020019 773__ $$0PERI:(DE-600)2452964-3$$a10.3389/fncom.2023.1295395$$gVol. 17, p. 1295395$$p1295395$$tFrontiers in computational neuroscience$$v17$$x1662-5188$$y2023
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