CNS*2020 Online

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https://hkbu.zoom.us/j/8259801008
Meeting ID: 825 980 1008

Shengjun Wang, Junhao Liang, Changsong Zhou

Complex neural network in the brain is remarkably cost-efficient while the basic mechanisms underlying its structure-dynamics economy are not clear. Here we study the intricate interplay between wiring and running cost with modular network topology, self-sustained activity and critical avalanche dynamical mode in biologically plausible excitation-inhibition balanced spatial neuronal network. When rewiring the initially wiring-expensive sparse random network gradually to wiring-economical modular network, its self-sustained dynamics changes from asynchronous spiking to critical avalanches state with strongly reduced firing rate and greatly enhanced response sensitivity to transient stimuli. Thus, the system can counter intuitively achieve much more functional values with much less costs in both wiring and firing. The dynamic mechanism is explained as a proximity to Hopf bifurcation in the macroscopic mean-field in separated modules when increasing the connection density. Our work reveals the generic mechanism underlying the cost-economical structural organization and function-efficient critical dynamics of neural systems, providing insights to brain-inspired efficient computational designs.

This work is supposed to be presented by Changsong Zhou.