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Computational geometry for modeling neural populations: From visualization to simulation - Fig 10

By Marc de Kamps (6421406), Mikkel Lepperød (6421409) and Yi Ming Lai (6421412)

Abstract

<p>A: compares the response for three cases: no adaptation; only current adaptation; and both current- as well as spike-based adaptation is included. B: The gain for a small sinusoidal input modulated on a background input as function of frequency, for no adaptation and AdExp with current- and spike-based adaptation. Both spectra show the dependency expected of an exponential-integrate-and-fire neuron, as the spike shape, represented by the grid at high <i>V</i> values is independent of <i>w</i>. However, the numerical difference between the cases is vast.</p

Topics: Biophysics, Biotechnology, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Information Systems not elsewhere classified, code, probability density function, 1 D systems, mesoscopic description level, point spiking neuron models, method, state space, 2 D ones, term, 1 D marginals, diffusion, simulation, 2 D systems subject
Year: 2019
DOI identifier: 10.1371/journal.pcbi.1006729.g010
OAI identifier: oai:figshare.com:article/7800383
Provided by: FigShare
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