ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2022
Active Licking Shapes Cortical Taste Coding.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Sex differences in taste neophobia and conditioned aversion across fluid administration methods.Frontiers in behavioral neuroscience · 2026Article
- Neural Processing of Taste-Related Signals in the Mediodorsal Thalamus of Mice.bioRxiv : the preprint server for biology · 2025Article
- Cortical coding of gustatory and thermal signals in active licking mice.The Journal of physiology · 2025Article
- Cortical Coding of Gustatory and Thermal Signals in Active Licking Mice.bioRxiv : the preprint server for biology · 2024Article
- Neural Activity in the Anterior Insula at Drinking Onset and Licking Relates to Compulsion-Like Alcohol Consumption.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Oral thermal processing in the gustatory cortex of awake mice.Chemical senses · 2023Article
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Authors and funding
6 authors.
Funding
Abstract
Neurons in the gustatory cortex (GC) represent taste through time-varying changes in their spiking activity. The predominant view is that the neural firing rate represents the sole unit of taste information. It is currently not known whether the phase of spikes relative to lick timing is used by GC neurons for taste encoding. To address this question, we recorded spiking activity from >500 single GC neurons in male and female mice permitted to freely lick to receive four liquid gustatory stimuli and water. We developed a set of data analysis tools to determine the ability of GC neurons to discriminate gustatory information and then to quantify the degree to which this information exists in the spike rate versus the spike timing or phase relative to licks. These tools include machine learning algorithms for classification of spike trains and methods from geometric shape and functional data analysis. Our results show that while GC neurons primarily encode taste information using a rate code, the timing of spikes is also an important factor in taste discrimination. A further finding is that taste discrimination using spike timing is improved when the timing of licks is considered in the analysis. That is, the interlick phase of spiking provides more information than the absolute spike timing itself. Overall, our analysis demonstrates that the ability of GC neurons to distinguish among tastes is best when spike rate and timing is interpreted relative to the timing of licks.
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