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pmid: 33296032
pmc: PMC7726065
AbstractA neural field models the large scale behaviour of large groups of neurons. We extend previous results for these models by including a diffusion term into the neural field, which models direct, electrical connections. We extend known and prove new sun-star calculus results for delay equations to be able to include diffusion and explicitly characterise the essential spectrum. For a certain class of connectivity functions in the neural field model, we are able to compute its spectral properties and the first Lyapunov coefficient of a Hopf bifurcation. By examining a numerical example, we find that the addition of diffusion suppresses non-synchronised steady-states while favouring synchronised oscillatory modes.
Mathematics - Functional Analysis, Delay equation, Normal form, Sun-star calculus, Research, Neural field, FOS: Mathematics, Numerical bifurcation analysis, Hopf bifurcation, Dynamical Systems (math.DS), Mathematics - Dynamical Systems, Functional Analysis (math.FA)
Mathematics - Functional Analysis, Delay equation, Normal form, Sun-star calculus, Research, Neural field, FOS: Mathematics, Numerical bifurcation analysis, Hopf bifurcation, Dynamical Systems (math.DS), Mathematics - Dynamical Systems, Functional Analysis (math.FA)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 11 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |