iScienceNeurosciencePeer-reviewed journal article
Sequential and dynamic coding of water-sucrose categorization in rat gustatory cortices
Germán MendozaiD, Esmeralda FonsecaiD, Hugo MerchantiD, Ranier GutiérreziD
Abstract
The gustatory system enables our conscious perception of sweetness, allowing us to distinguish sweet solutions from water. However, the neural mechanisms underlying this categorization process in rats remain poorly understood. We addressed this question by designing a novel sucrose categorization task in which rats classified varying sucrose concentrations against water. We found that in the anterior insular cortex (aIC) and orbitofrontal cortex (OFC), neural activity primarily encoded the categorical distinction between sucrose and water, rather than specific sucrose concentrations. Notably, aIC neurons encoded this distinction faster than OFC neurons. Conversely, the OFC slightly preceded the aIC in encoding choice information, although both cortices maintained parallel encoding of the rats choices. The encoding of sensory and categorical decisions was dynamic and sequential, forming a sequence of encoding neurons throughout the trial. These findings reveal that sucrose categorization relies on dynamic coding sequences in the neuronal activity of the aIC and OFC rather than static, long-lasting (sustained) neural representations. This dynamic coding, supported by single-cell population decoding and principal component analyses, suggests that the brain continuously updates its representation of sucrose categorization as new information emerges. Additionally, both the aIC and OFC rapidly encoded reward outcomes. Our data supports the notion that gustatory cortices employ sequential and dynamic coding to compute sensorimotor transformations, from taste detection to categorical taste decisions and reward processing. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=171 SRC="FIGDIR/small/590344v2_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@20b8f0org.highwire.dtl.DTLVardef@4da81eorg.highwire.dtl.DTLVardef@586151org.highwire.dtl.DTLVardef@5d4469_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: rat
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 3
- FWCI
- 0.73
- Field percentile
- top 32%
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