Linear stability analysis of homogeneous states in sparse random networks of next-generation neural mass models links instabilities to connectivity spectra, revealing winner-takes-all patterns in undirected inhibitory systems and high-dimensional chaos in directed networks.
Otherwise, increasingNwith fixedκ, would surpass the percolation threshold, leading to the emergence of several connected components
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Symmetry breaking and high-dimensional chaos in sparse random networks of exact firing rate models
Linear stability analysis of homogeneous states in sparse random networks of next-generation neural mass models links instabilities to connectivity spectra, revealing winner-takes-all patterns in undirected inhibitory systems and high-dimensional chaos in directed networks.