Single and population coding of taste in the gustatory cortex of awake mice

Abstract

Electrophysiological analysis has revealed much about the broad coding and neural ensemble dynamics that characterize gustatory cortical (GC) taste processing in awake rats and about how these dynamics relate to behavior. With regard to mice, however, data concerning cortical taste coding have largely been restricted to imaging, a technique that reveals average levels of neural responsiveness but that (currently) lacks the temporal sensitivity necessary for evaluation of fast response dynamics; furthermore, the few extant studies have thus far failed to provide consensus on basic features of coding. We have recorded the spiking activity of ensembles of GC neurons while presenting representatives of the basic taste modalities (sweet, salty, sour, and bitter) to awake mice. Our first central result is the identification of similarities between rat and mouse taste processing: most mouse GC neurons (~66%) responded distinctly to multiple (3–4) tastes; temporal coding analyses further reveal, for the first time, that single mouse GC neurons sequentially code taste identity and palatability, the latter responses emerging ~0.5 s after the former, with whole GC ensembles transitioning suddenly and coherently from coding taste identity to coding taste palatability. The second finding is that spatial location plays very little role in any aspect of taste responses: neither between- (anterior-posterior) nor within-mouse (dorsal-ventral) mapping revealed anatomic regions with narrow or temporally simple taste responses. These data confirm recent results showing that mouse cortical taste responses are not “gustotopic” but also go beyond these imaging results to show that mice process tastes through time. NEW & NOTEWORTHY Here, we analyzed taste-related spiking activity in awake mouse gustatory cortical (GC) neural ensembles, revealing deep similarities between mouse cortical taste processing and that repeatedly demonstrated in rat: mouse GC ensembles code multiple aspects of taste in a coarse-coded, time-varying manner that is essentially invariant across the spatial extent of GC. These data demonstrate that, contrary to some reports, cortical network processing is distributed, rather than being separated out into spatial subregion.

Perturbation of amygdala-cortical projections reduces ensemble coherence of palatability coding in gustatory cortex

“…Note the cell body staining in BLA, and the utter lack of cell body staining in GC, where expression is restricted to axon filaments. ArchT (which in this case co-expresses with GFP) is carried from the injection site in BLA in a purely anterograde direction, and a subset of infected axons terminate in the ventral part of GC—a result consistent with earlier rat and mouse data ( Haley et al, 2016 ; Levitan et al, 2019 ). Rats in which GFP expression was not found in BLA and GC, or in which opto-trodes were misplaced, were excluded from further data analysis.…”

Dynamic Representation of Taste-Related Decisions in the Gustatory Insular Cortex of Mice

“…The third epoch (palatability) begins about 1 s after stimulus delivery and relates to the processing of taste palatability. This coding scheme has been further refined through trial-by-trial ensemble analyses and has been extensively validated by experimental evidence in rats and mice [ 5 , 7 , 16 , 30 , 31 ]. Alas, one of the limitations of this model has been its exclusive reliance on experiments in which rodents consume tastants that are flushed directly into the oral cavity through a surgically implanted intraoral cannula.…”

Loss of Stk11 in basolateral amygdalar projection neurons impairs taste aversion learning by altering the temporal pattern of taste response plasticity in gustatory cortex

“…In GC responses, palatability-correlated firing emerges across the 1.5s after stimulus delivery (Levitan et al, 2019; Levitan et al, 2020). The same pattern was observed here (Figure 3A) for both groups of mice.…”

“…Single neurons were classified as regular spiking or fast-spiking based on inspection of spike waveform shape and ISI histograms (for details see Levitan et al, 2019). Regular spiking cells were taken as putative pyramidal neurons while fast-spiking cells were labelled as interneurons.…”