Brain circuits underlying visual stability across eye movements-converging evidence for a neuro-computational model of area LIP

The understanding of the subjective experience of a visually stable world despite the occurrence of an observer's eye movements has been the focus of extensive research for over 20 years. These studies have revealed fundamental mechanisms such as anticipatory receptive field (RF) shifts and the...

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Published inFrontiers in computational neuroscience Vol. 8; p. 25
Main Authors Ziesche, Arnold, Hamker, Fred H
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Research Foundation 11.03.2014
Frontiers Media S.A
Subjects
computational model
Computational neuroscience
corollary discharge
Eye movements
Eye Position Signal
Neurons
Neuroscience
Neurosciences
predictive remapping
Receptive field
Saccadic eye movements
Saccadic Suppression of Displacement
Space Perception
Visual pathways
Visual system
Germany
computational model
eye position signal
predictive remapping
corollary discharge
saccadic suppression of displacement
space perception
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Summary:The understanding of the subjective experience of a visually stable world despite the occurrence of an observer's eye movements has been the focus of extensive research for over 20 years. These studies have revealed fundamental mechanisms such as anticipatory receptive field (RF) shifts and the saccadic suppression of stimulus displacements, yet there currently exists no single explanatory framework for these observations. We show that a previously presented neuro-computational model of peri-saccadic mislocalization accounts for the phenomenon of predictive remapping and for the observation of saccadic suppression of displacement (SSD). This converging evidence allows us to identify the potential ingredients of perceptual stability that generalize beyond different data sets in a formal physiology-based model. In particular we propose that predictive remapping stabilizes the visual world across saccades by introducing a feedback loop and, as an emergent result, small displacements of stimuli are not noticed by the visual system. The model provides a link from neural dynamics, to neural mechanism and finally to behavior, and thus offers a testable comprehensive framework of visual stability.
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Edited by: Tomoki Fukai, RIKEN Brain Science Institute, Japan
This article was submitted to the journal Frontiers in Computational Neuroscience.
Reviewed by: Katsunori Kitano, Ritsumeikan University, Japan; Ko Sakai, University of Tsukuba, Japan
ISSN:1662-5188
1662-5188
DOI:10.3389/fncom.2014.00025