The Syncytial Mesh Model proposes that astrocytic syncytial organization supplies a continuous mesoscale control field that shapes scale-dependent neuronal coherence and traveling-wave patterns beyond direct synaptic connectivity.
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A neural-network approximation of heteroclinic dynamics, interpretable as an Amari-type neural-field system, reproduces sequential transitions among cognitive states.
Mean-field theory of soft-threshold integrate-and-fire networks predicts Hopf, Turing, and Turing-Hopf bifurcations producing oscillations, bumps, and spatiotemporal waves, confirmed via stochastic simulations.
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The Syncytial Mesh Model: A Mesoscale Control-Field Framework for Scale-Dependent Coherence in the Brain
The Syncytial Mesh Model proposes that astrocytic syncytial organization supplies a continuous mesoscale control field that shapes scale-dependent neuronal coherence and traveling-wave patterns beyond direct synaptic connectivity.
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Modeling sequential cognitive states via population level cortical dynamics
A neural-network approximation of heteroclinic dynamics, interpretable as an Amari-type neural-field system, reproduces sequential transitions among cognitive states.
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Coherent dynamics in soft-threshold integrate-and-fire networks
Mean-field theory of soft-threshold integrate-and-fire networks predicts Hopf, Turing, and Turing-Hopf bifurcations producing oscillations, bumps, and spatiotemporal waves, confirmed via stochastic simulations.