Stability of bumps in piecewise smooth neural fields with nonlinear adaptation.
Stability of bumps in piecewise smooth neural fields with nonlinear adaptation.
Zachary P Kilpatrick and Paul C Bressloff
Physica D 239 (2010), pp. 1048-1060.
Abstract:We study the linear stability of stationary bumps in piecewise smooth neural fields with local negative
feedback in the form of synaptic depression or spike frequency
adaptation. The continuum dynamics is described in terms of a nonlocal
integrodifferential equation, in which the integral kernel represents
the spatial distribution of synaptic weights between populations of
neurons whose mean firing rate is taken to be a Heaviside function of
local activity. Discontinuities in the adaptation variable associated
with a bump solution means that bump stability cannot be analyzed by
constructing the Evans function for a network with a sigmoidal gain
function and then taking the high-gain limit. In the case of synaptic
depression, we show that linear stability can be formulated in terms
of solutions to a system of pseudo-linear equations. We thus establish
that sufficiently strong synaptic depression can destabilize a bump
that is stable in the absence of depression. These instabilities are
dominated by shift perturbations that evolve into traveling pulses. In
the case of spike frequency adaptation,weshow that for a wide class of
perturbations the activity and adaptation variables decouple in the
linear regime, thus allowing us to explicitly determine stability in
terms of the spectrum of a smooth linear operator. We find that bumps
are always unstable with respect to this class of perturbations, and
destabilization of a bump can result in either a traveling pulse or a spatially localized breather.
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