%0 Conference Paper
%A Dick, Michael
%A Alexander, van Meegen
%A Helias, Moritz
%T Linking Network and Neuron Level Correlations via Renormalized Field Theory
%M FZJ-2023-03601
%D 2023
%X It is frequently hypothesized that cortical networks operate close to a critical point. Advantages of criticality include rich dynamics well-suited for computation and critical slowing down, which may offer a mechanism for dynamic memory. However, mean-field approximations, while versatile and popular, inherently neglect the fluctuations responsible for such critical dynamics. Thus, a renormalized theory is necessary. We consider the Sompolinsky-Crisanti-Sommers model which displays a well studied chaotic as well as a magnetic transition. Based on the analogue of a quantum effective action, we derive self-consistency equations for the first two renormalized Greens functions. Their self-consistent solution reveals a coupling between the population level activity and single neuron heterogeneity. The quantitative theory explains the population autocorrelation function, the single-unit autocorrelation function with its multiple temporal scales, and cross correlations.
%B Bernstein Conference 2023
%C 26 Sep 2023 - 30 Sep 2023, Berlin (Germany)
Y2 26 Sep 2023 - 30 Sep 2023
M2 Berlin, Germany
%F PUB:(DE-HGF)24
%9 Poster
%R 10.34734/FZJ-2023-03601
%U https://juser.fz-juelich.de/record/1015246