Simple Cortical and Thalamic Neuron Models for Digital Arithmetic Circuit Implementation.

ABSTRACT: Trade-off between reproducibility of neuronal activities and computational efficiency is one of crucial subjects in computational neuroscience and neuromorphic engineering. A wide variety of neuronal models have been studied from different viewpoints. The digital spiking silicon neuron (DSSN) model is a qualitative model that focuses on efficient implementation by digital arithmetic circuits. We expanded the DSSN model and found appropriate parameter sets with which it reproduces the dynamical behaviors of the ionic-conductance models of four classes of cortical and thalamic neurons. We first developed a four-variable model by reducing the number of variables in the ionic-conductance models and elucidated its mathematical structures using bifurcation analysis. Then, expanded DSSN models we

SUBMITTER: Nanami T 

PROVIDER: S-EPMC4865656 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature