Statistical Field Theory and Networks of Spiking Neurons

Pierre Gosselin; Aïleen Lotz; Marc Wambst

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arXiv · 2009.14744

Statistical Field Theory and Networks of Spiking Neurons

Pierre Gosselin·Aïleen Lotz·Marc Wambst

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Abstract

This paper models the dynamics of a large set of interacting neurons within the framework of statistical field theory. We use a method initially developed in the context of statistical field theory [44] and later adapted to complex systems in interaction [45][46]. Our model keeps track of individual interacting neurons dynamics but also preserves some of the features and goals of neural field dynamics, such as indexing a large number of neurons by a space variable. Thus, this paper bridges the scale of individual interacting neurons and the macro-scale modelling of neural field theory.

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Pierre Gosselin, Aïleen Lotz, Marc Wambst. 2020-09-30. Statistical Field Theory and Networks of Spiking Neurons. https://arxiv.org/abs/2009.14744

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