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| Poster #259 Investigating Intra-State Dynamics in Taste-Evoked Gustatory Cortex Responses in Rats |
| Vincent Calia-Bogan1, Abuzar Mahmood1, Donald Katz1,2 1Department of Psychology, Brandeis University, Waltham, MA, United States 2Volen National Center for Complex Systems, Brandeis University, Waltham, MA, United States |
Cortical taste-processing is comprised of a sequence of discrete states of neural activity (Mahmood et al., 2023). State changes, detected using Hidden Markov Modelling (HMM), have been observed in stimulus-evoked neural population activity in both the Gustatory Cortex and Basolateral Amygdala. While previous work has shown that constant-emission HMMs (i.e., models that treat activity within a single state as a fixed pattern plus noise) describe neural population activity better than either trial-averaged PSTHs or Drift-Diffusion models, the assumption of perfectly stationary activity is simplistic (Sadacca et al., 2016; Mahmood et al., 2023). Indeed, previous analyses show that both onset-time and duration of states vary from trial-to-trial. We hypothesize that this variability is governed by hitherto overlooked intra-state dynamics—that differences in the speed with which within-state dynamics reach “completion” may determine differences in state duration. To interrogate this question directly, I have employed a variety of computational methods for quantifying ensemble behavior to better investigate intra-state dynamics in taste-evoked population activity. Our analyses show that intra-state dynamics within cortical activity across a battery of taste stimuli are aligned to state-transitions inferred using constant-emission HMMs, and are demonstrably different from noise (as expected by a constant-emission model). Ongoing work is investigating an explicit link between these intra-state dynamics and duration of taste-processing states. The characterization of these intra-state dynamics will allow for greater insight into the mechanistic models underlying these highly non-linear dynamics and provide additional constrains for theoretical models generating such dynamics. |