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Main Authors: Bolelli, Maria Virginia, Prandi, Dario
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2407.17294
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author Bolelli, Maria Virginia
Prandi, Dario
author_facet Bolelli, Maria Virginia
Prandi, Dario
contents The aim of this work is to present a mathematical framework for the study of flickering inputs in visual processing tasks. When combined with geometric patterns, these inputs influence and induce interesting psychophysical phenomena, such as the MacKay and the Billock-Tsou effects, where the subjects perceive specific afterimages typically modulated by the flickering frequency. Due to the symmetry-breaking structure of the inputs, classical bifurcation theory and multi-scale analysis techniques are not very effective in our context. We thus take an approach based on the input-output framework of control theory for Amari-type neural fields. This allows us to prove that, when driven by periodic inputs, the dynamics converge to a periodic state. Moreover, we study under which assumptions these nonlinear dynamics can be effectively linearised, and in this case we present a precise approximation of the integral kernel for short-range excitatory and long-range inhibitory neuronal interactions. Finally, for inputs concentrated at the center of the visual field with a flickering background, we directly relate the width of the illusory contours appearing in the afterimage with both the flickering frequency and the strength of the inhibition.
format Preprint
id arxiv_https___arxiv_org_abs_2407_17294
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Neural field equations with time-periodic external inputs and some applications to visual processing
Bolelli, Maria Virginia
Prandi, Dario
Neurons and Cognition
Analysis of PDEs
Dynamical Systems
Optimization and Control
92C20, 45K05, 35B36, 93C20, 45A05
The aim of this work is to present a mathematical framework for the study of flickering inputs in visual processing tasks. When combined with geometric patterns, these inputs influence and induce interesting psychophysical phenomena, such as the MacKay and the Billock-Tsou effects, where the subjects perceive specific afterimages typically modulated by the flickering frequency. Due to the symmetry-breaking structure of the inputs, classical bifurcation theory and multi-scale analysis techniques are not very effective in our context. We thus take an approach based on the input-output framework of control theory for Amari-type neural fields. This allows us to prove that, when driven by periodic inputs, the dynamics converge to a periodic state. Moreover, we study under which assumptions these nonlinear dynamics can be effectively linearised, and in this case we present a precise approximation of the integral kernel for short-range excitatory and long-range inhibitory neuronal interactions. Finally, for inputs concentrated at the center of the visual field with a flickering background, we directly relate the width of the illusory contours appearing in the afterimage with both the flickering frequency and the strength of the inhibition.
title Neural field equations with time-periodic external inputs and some applications to visual processing
topic Neurons and Cognition
Analysis of PDEs
Dynamical Systems
Optimization and Control
92C20, 45K05, 35B36, 93C20, 45A05
url https://arxiv.org/abs/2407.17294