Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration.

J Rankin,G S Masson,P Kornprobst,O Faugeras,A I Meso

doi:10.1007/s10827-013-0465-5

Abstract

Perceptual multistability is a phenomenon in which alternate interpretations of a fixed stimulus are perceived intermittently. Although correlates between activity in specific cortical areas and perception have been found, the complex patterns of activity and the underlying mechanisms that gate multistable perception are little understood. Here, we present a neural field competition model in which competing states are represented in a continuous feature space. Bifurcation analysis is used to describe the different types of complex spatio-temporal dynamics produced by the model in terms of several parameters and for different inputs. The dynamics of the model was then compared to human perception investigated psychophysically during long presentations of an ambiguous, multistable motion pattern known as the barberpole illusion. In order to do this, the model is operated in a parameter range where known physiological response properties are reproduced whilst also working close to bifurcation. The model accounts for characteristic behaviour from the psychophysical experiments in terms of the type of switching observed and changes in the rate of switching with respect to contrast. In this way, the modelling study sheds light on the underlying mechanisms that drive perceptual switching in different contrast regimes. The general approach presented is applicable to a broad range of perceptual competition problems in which spatial interactions play a role.

Highlights

Perception can evolve dynamically for fixed sensory inputs and so-called multistable stimuli have been the attention of much recent experimental and computational investigation
Bifurcation analysis (Strogatz 1994; Kuznetsov 1998) and numerical continuation (Krauskopf et al 2007) are powerful tools from the study of dynamical systems that have already proved effective in analysing rate models where the competing perceptual states are represented by discrete neural masses (Shpiro et al 2007; Curtu et al 2008; Theodoni et al 2011b)
The neural fields model at the core of this study has a continuous feature space, which allows multistability to be investigated in a motion integration problem where the different percepts are represented on a continuous scale

Summary

Introduction

Perception can evolve dynamically for fixed sensory inputs and so-called multistable stimuli have been the attention of much recent experimental and computational investigation. Bifurcation analysis (Strogatz 1994; Kuznetsov 1998) and numerical continuation (Krauskopf et al 2007) are powerful tools from the study of dynamical systems that have already proved effective in analysing rate models where the competing perceptual states are represented by discrete neural masses (Shpiro et al 2007; Curtu et al 2008; Theodoni et al 2011b). Existing studies using discrete neural masses have shown that switching in rivalry experiments can be described by a relatively simple dynamical system.

Results

Discussion

Conclusion