Impact of Hill coefficient and time delay on a perceptual decision-making model

TL;DR

This paper analyzes how the Hill coefficient and time delay affect a neural mass model of perceptual decision-making, providing generalized insights through analytical and numerical methods.

Contribution

It introduces a generalized analysis of the model by incorporating delay and Hill coefficient effects, comparing multiple model variants.

Findings

Delay influences decision dynamics

Hill coefficient alters stability and bifurcations

Model variants exhibit different decision behaviors

Abstract

In this paper, a neural mass perceptual decision making model introduced by Piska{\l}a et al. is analyzed. The model describes activity of two neuron populations influenced by each other and external inputs. The groups' activities correspond to the process of making a perceptual binary decision. Existing results are generalized by investigating the impact of both a delay in self-inhibition and a generic Hill coefficient on solutions to the system of differential equations. Several versions of the model with various assumptions are compared using analytical and numerical methods.