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Learning Peri-saccadic Remapping of Receptive Field from Experience in Lateral Intraparietal Area.

Authors :
Xiao Wang
Yan Wu
Mingsha Zhang
Si Wu
Source :
Frontiers in Computational Neuroscience; 11/28/2017, p1-12, 12p
Publication Year :
2017

Abstract

Our eyes move constantly at a frequency of 3-5 times per second. These movements, called saccades, induce the sweeping of visual images on the retina, yet we perceive the world as stable. It has been suggested that the brain achieves this visual stability via predictive remapping of neuronal receptive field (RF). A recent experimental study disclosed details of this remapping process in the lateral intraparietal area (LIP), that is, about the time of the saccade, the neuronal RF expands along the saccadic trajectory temporally, covering the current RF (CRF), the future RF (FRF) and the region the eye will sweep through during the saccade. A cortical wave (CW) model was also proposed, which attributes the RF remapping as a consequence of neural activity propagating in the cortex, triggered jointly by a visual stimulus and the corollary discharge (CD) signal responsible for the saccade. In this study, we investigate how this CW model is learned naturally from visual experiences at the development of the brain. We build a two-layer network, with one layer consisting of LIP neurons and the other superior colliculus (SC) neurons. Initially, neuronal connections are random and non-selective. A saccade will cause a static visual image to sweep through the retina passively, creating the effect of the visual stimulus moving in the opposite direction of the saccade. According to the spiking-time-dependent-plasticity rule, the connection path in the opposite direction of the saccade between LIP neurons and the connection path fromSC to LIP are enhanced. Over many such visual experiences, the CW model is developed, which generates the peri-saccadic RF remapping in LIP as observed in the experiment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16625188
Database :
Complementary Index
Journal :
Frontiers in Computational Neuroscience
Publication Type :
Academic Journal
Accession number :
126474427
Full Text :
https://doi.org/10.3389/fncom.2017.00110