ACHEMS 2019
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SPLTRAK Abstract Submission
Spatio-temporal patterns of activity in the gustatory cortex of mice engaged in a cue-taste paradigm
Ke Chen, Joshua F. Kogan, Alfredo Fontanini
State University of New York at Stony Brook, Stony Brook, NY, United States

Despite decades of research, the basic logic underlying taste coding in the gustatory cortex (GC) remains intensively debated. The development of 2-photon calcium imaging has greatly expanded our perspective on taste coding in GC. What we know about the topographic organization of GC comes from imaging studies in anesthetized rodents. However, work on various sensory systems suggests that coding in alert animals is radically different from coding under anesthesia. Here, we apply 2-photon calcium imaging to study the representation of taste information and task-related signals in GC of awake mice.  AAV1 virus carrying GCaMP6f was injected into GC and chronic windows made of micro-prisms were implanted above GC. After recovery, mice were water restricted and trained to perform a cued-taste task. For each trial, mice were trained to perform 5 dry licks after an auditory tone (2s, 2k Hz) to receive one of five stimuli (sucrose, NaCl, citric acid, quinine and water) while we monitored neural activity in GC with 2-photon microscopy. We analyzed activity in 872 active neurons from layer 2/3 of 6 mice that had been habituated to tastants. We found that 20.5% (179/872) of the neurons encoded taste identity, 15.8% (138/872) of the neurons were activated by the auditory cue and 8.7% (76/872) neurons were active during licking. For taste coding neurons, half responded exclusively to a single quality, while the other half was tuned to multiple qualities. Taste coding neurons were spatially distributed, with no evidence of spatial clustering. In addition, we also imaged the same portion of GC during Day 1, Day 3 and Day 7 of taste exposure. Altogether, our data suggest that GC encodes taste with spatially distributed patterns of activity and with a mix of narrowly and broadly tuned neurons.