bioRxivNeurosciencePreprint
The Ingestive Response Reflects Neural Dynamics in Gustatory Cortex
Natasha Baas-ThomasiD, Abuzar MahmoodiD, Narendra MukherjeeiD, Kathleen C. MaigleriD, Yixi Wang, Donald B. KatziD
Abstract
Upon delivery of a taste onto the tongue, gustatory neural activity determines whether the stimulus is ingested or rejected. While some work in rodents has been devoted to investigating the neural activity leading to the rejection decision and its associated orofacial movements, little is known about what behaviors lead to ingestion of palatable tastes (and what neural activity is associated with that decision), largely because identifying ingestion-related behaviors is a difficult challenge--and probably undoable with video analysis given that the behaviors are largely intraoral. To address this gap in our understanding, we analyzed simultaneously-collected electromyographic (EMG) activity of the jaw opener muscle and the firing of gustatory cortical (GC) ensembles. We developed a machine-learning classifier to identify individual orofacial movements from EMG signals, demonstrating that it outperforms previously developed methods and using the technique to reveal three novel subtypes of ingestion-related tongue/mouth movements. Investigating the dynamics of these behaviors, we found that the frequency of occurrence of each type subtype shifts significantly at the time of the consumption decision, and is both tightly coupled with and reliably follows the transition in GC population activity into the state reflecting the tastants emotional/hedonic value. However, rather than the onset of single "ingestion" movement (as occurs for rejection decisions in the form of gapes), we show that the transition to ingestion is instead characterized by a collective change in the frequencies all ingestion-related behaviors. These findings demonstrate a direct link between neural dynamics in GC and the orchestration of the physical movements that define ingestive behavior, highlighting GCs general role in taste perception, decision making, and the control of motor actions.
- organism: mouse
- assay: electronic health records
- research focus: cell type annotation
- approach: machine learning (classical)
- Citations
- 5
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