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.
(11) and take the real part: Re[λ± k ] = 2v0+ q B+Acos(θ) + p A2 + 2ABcos(θ) +B 2 (B2) 12 where v0 =− ∆ 2πτ r0 , A= √ κ−1(1−µ)τ r 0J, B=τ r 0J µ−2(πτ r 0)2
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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.