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

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

<p>The figure shows a similar impact of excitatory heterogeneity, which is contingent upon the inhibitory heterogeneity present in the network. Node 1 is stimulated with mV.</p>

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Dettagli Bibliografici
Autore principale:	Kalana G. Abeywardena (21799763) (author)
Altri autori:	Jeremie Lefebvre (9899117) (author), Taufik A. Valiante (7853738) (author), Stark C. Draper (21799766) (author)
Pubblicazione:	2025
Soggetti:	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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