Transitions between Asynchronous and Synchronous States: A Theory of Correlations in Small Neural Circuits

Abstract

<p>Model of the cross-correlation structure of a finite-size firing-rate network with graded activation function, from:</p> <p>Diego Fasoli, Anna Cattani, Stefano Panzeri, arXiv:1605.07383 [q-bio.NC], 2016, submitted to The Journal of Computational Neuroscience.</p> <p>The file "Python_Script_1.py" calculates the fundamental matrix of a finite-size multi-population neural network composed of an arbitrary number of homogeneous populations, according to the formalism described in the supplemental information of the article.</p> <p>The file "Python_Script_2.py" calculates the cross-correlation structure of a network composed of two neural populations (one excitatory and one inhibitory). In particular, the script compares the analytical cross-correlation structure of the network (see Eqs. (11)-(13) in the main text of the article) with the same quantities calculated numerically through the techniques described in SubSec. (2.3).</p