Generalizing a two-population decision model to any Hill coefficient and adding self-inhibition delay can flip the predicted dynamics from stable decisions to oscillations or divergence.
Impact of Hill coefficient and time delay on a perceptual decision-making model
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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.
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Impact of Hill coefficient and time delay on a perceptual decision-making model
Generalizing a two-population decision model to any Hill coefficient and adding self-inhibition delay can flip the predicted dynamics from stable decisions to oscillations or divergence.