Multi-node macro-scale networks show trivialization with excitability heterogeneity similar to that observed in two-node networks.

<p>Each sub-figure, organized in a 34 grid, shows the progression of equilibria with for specific heterogeneity vectors and global coupling strengths . Colors indicate stable states at each equilibrium, as defined in <a href="https://journals.plos.org/complexsystems//article/info:doi/1...

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主要作者:	Kalana G. Abeywardena (21799763) (author)
其他作者:	Jeremie Lefebvre (9899117) (author), Taufik A. Valiante (7853738) (author), Stark C. Draper (21799766) (author)
出版:	2025
主题:	Biophysics Medicine Neuroscience Infectious Diseases Biological Sciences not elsewhere classified Physical Sciences not elsewhere classified xlink "> experimental system &# 8217 numerical results show neural mass model e ., electroencephalography network &# 8217 representing brain activity scale brain networks reducing amplitude variations brain region dynamics scale computational model coarser spatial scale intrinsic excitability heterogeneity scale activity brain affects spatial resolution coarser scales computational models network resilience synaptic heterogeneity synaptic coupling stable states multiple equilibria magnetoencephalography ). level investigations less effective interacting excitatory inhibitory sub individual neurons external stimulations external inputs excitability heterogeneity clinical tools
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Multi-node macro-scale networks show trivialization with excitability heterogeneity similar to that observed in two-node networks.

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