Weighted cue integration in the rodent head direction system.

How the brain combines information from different sensory modalities and of differing reliability is an important and still-unanswered question. Using the head direction (HD) system as a model, we explored the resolution of conflicts between landmarks and background cues. Sensory cue integration mod...

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Main Authors: Knight, R, Piette, C, Page, H, Walters, D, Marozzi, E, Nardini, M, Stringer, S, Jeffery, K
Format: Journal article
Language:English
Published: 2014
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author Knight, R
Piette, C
Page, H
Walters, D
Marozzi, E
Nardini, M
Stringer, S
Jeffery, K
author_facet Knight, R
Piette, C
Page, H
Walters, D
Marozzi, E
Nardini, M
Stringer, S
Jeffery, K
author_sort Knight, R
collection OXFORD
description How the brain combines information from different sensory modalities and of differing reliability is an important and still-unanswered question. Using the head direction (HD) system as a model, we explored the resolution of conflicts between landmarks and background cues. Sensory cue integration models predict averaging of the two cues, whereas attractor models predict capture of the signal by the dominant cue. We found that a visual landmark mostly captured the HD signal at low conflicts: however, there was an increasing propensity for the cells to integrate the cues thereafter. A large conflict presented to naive rats resulted in greater visual cue capture (less integration) than in experienced rats, revealing an effect of experience. We propose that weighted cue integration in HD cells arises from dynamic plasticity of the feed-forward inputs to the network, causing within-trial spatial redistribution of the visual inputs onto the ring. This suggests that an attractor network can implement decision processes about cue reliability using simple architecture and learning rules, thus providing a potential neural substrate for weighted cue integration.
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spelling oxford-uuid:3f710886-ebab-4bee-9255-fc9e63dc07d32022-03-26T14:32:01ZWeighted cue integration in the rodent head direction system.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:3f710886-ebab-4bee-9255-fc9e63dc07d3EnglishSymplectic Elements at Oxford2014Knight, RPiette, CPage, HWalters, DMarozzi, ENardini, MStringer, SJeffery, KHow the brain combines information from different sensory modalities and of differing reliability is an important and still-unanswered question. Using the head direction (HD) system as a model, we explored the resolution of conflicts between landmarks and background cues. Sensory cue integration models predict averaging of the two cues, whereas attractor models predict capture of the signal by the dominant cue. We found that a visual landmark mostly captured the HD signal at low conflicts: however, there was an increasing propensity for the cells to integrate the cues thereafter. A large conflict presented to naive rats resulted in greater visual cue capture (less integration) than in experienced rats, revealing an effect of experience. We propose that weighted cue integration in HD cells arises from dynamic plasticity of the feed-forward inputs to the network, causing within-trial spatial redistribution of the visual inputs onto the ring. This suggests that an attractor network can implement decision processes about cue reliability using simple architecture and learning rules, thus providing a potential neural substrate for weighted cue integration.
spellingShingle Knight, R
Piette, C
Page, H
Walters, D
Marozzi, E
Nardini, M
Stringer, S
Jeffery, K
Weighted cue integration in the rodent head direction system.
title Weighted cue integration in the rodent head direction system.
title_full Weighted cue integration in the rodent head direction system.
title_fullStr Weighted cue integration in the rodent head direction system.
title_full_unstemmed Weighted cue integration in the rodent head direction system.
title_short Weighted cue integration in the rodent head direction system.
title_sort weighted cue integration in the rodent head direction system
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