A Spiking Neuron and Population Model Based on the Growth Transform Dynamical System.

ABSTRACT: In neuromorphic engineering, neural populations are generally modeled in a bottom-up manner, where individual neuron models are connected through synapses to form large-scale spiking networks. Alternatively, a top-down approach treats the process of spike generation and neural representation of excitation in the context of minimizing some measure of network energy. However, these approaches usually define the energy functional in terms of some statistical measure of spiking activity (ex. firing rates), which does not allow independent control and optimization of neurodynamical parameters. In this paper, we introduce a new spiking neuron and population model where the dynamical and spiking responses of neurons can be derived directly from a network objective or energy functional of continuo

SUBMITTER: Gangopadhyay A 

PROVIDER: S-EPMC7235464 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature