Gabriele Casagrande
Derivation of mean-field models from single neuron models subjected to dopamine modulation.
Rel. Alessandro Pelizzola. Politecnico di Torino, Corso di laurea magistrale in Physics Of Complex Systems (Fisica Dei Sistemi Complessi), 2024
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Abstract
One of the main challenge in neuroscience is to model the behavior of the brain at different scales, both in physiological and pathological conditions. However, the inherent complexity of the brain make it really challenging to tackle the problem of studying the underlying brain dynamics directly. In an attempt to ease this challenge several techniques borrowed from physics have been exploited. One of these approach consist into derive the macroscopic dynamics of a population of neurons through mean field approximations. These models are based on the idea that, given the large number of neuron in a single population, we can focus our attention into describing the average activity of the group, instead that of each individual component.
In this work we exploit the mean field derivation framework to achieve a system of closed equations for two slightly different network of adaptive quadratic integrate-and-fire (aQIF) neurons
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