Associative learning changes cross-modal representations in the gustatory cortex
Abstract
A growing body of literature has demonstrated that primary sensory cortices are not exclusively unimodal, but can respond to stimuli of different sensory modalities. However, several questions concerning the neural representation of cross-modal stimuli remain open. Indeed, it is poorly understood if cross-modal stimuli evoke unique or overlapping representations in a primary sensory cortex and whether learning can modulate these representations. Here we recorded single unit responses to auditory, visual, somatosensory, and olfactory stimuli in the gustatory cortex (GC) of alert rats before and after associative learning. We found that, in untrained rats, the majority of GC neurons were modulated by a single modality. Upon learning, both prevalence of cross-modal responsive neurons and their breadth of tuning increased, leading to a greater overlap of representations. Altogether, our results show that gustatory cortex represents cross-modal stimuli according to their sensory identity, and that learning changes the overlap of cross-modal representations.
Article and author information
Author details
Funding
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (P2GEP3_151816)
- Roberto Vincis
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (P300PA_161021)
- Roberto Vincis
National Institute on Deafness and Other Communication Disorders (R01-DC010389)
- Alfredo Fontanini
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All experimental procedures were performed according to approved Institutional Animal Care and Use Committee protocols (#244930-1) at Stony Brook University, and complied with university, state, and federal regulation on the care and use of laboratory animals.
Copyright
© 2016, Vincis & Fontanini
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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