%0 Journal Article
%A Dick, Michael
%A Meegen, Alexander van
%A Helias, Moritz
%T Linking network- and neuron-level correlations by renormalized field theory
%J Physical review research
%V 6
%N 3
%@ 2643-1564
%C College Park, MD
%I APS
%M FZJ-2024-05234
%P 033264
%D 2024
%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 analog 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.
%F PUB:(DE-HGF)16
%9 Journal Article
%U <Go to ISI:>//WOS:001310522300005
%R 10.1103/PhysRevResearch.6.033264
%U https://juser.fz-juelich.de/record/1030128