A framework for macroscopic phase-resetting curves for generalised spiking neural networks.

ABSTRACT: Brain rhythms emerge from synchronization among interconnected spiking neurons. Key properties of such rhythms can be gleaned from the phase-resetting curve (PRC). Inferring the PRC and developing a systematic phase reduction theory for large-scale brain rhythms remains an outstanding challenge. Here we present a theoretical framework and methodology to compute the PRC of generic spiking networks with emergent collective oscillations. We adopt a renewal approach where neurons are described by the time since their last action potential, a description that can reproduce the dynamical feature of many cell types. For a sufficiently large number of neurons, the network dynamics are well captured by a continuity equation known as the refractory density equation. We develop an adjoint method for

SUBMITTER: Dumont G 

PROVIDER: S-EPMC9371324 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature