Encoding and perception of sensory information are important functions of the brain, whose neural correlates are a subject of intense study. Recent work on taste processing has shown that the neural activity in gustatory cortex of awake rats is dynamic for a given, constant stimulus (a given taste). Specifically, the neural responses vary across a timescale of one to two seconds as the encoded information shifts from somatosensory (a taste hitting the tongue) to chemosensory (the identity of the tastant) to palatability (whether the substance in the mouth should be ingested or expelled). Moreover, these neural dynamics, which appear to vary smoothly when averaged across trials with time locked to the stimulus onset, are better represented by sequences of discrete states of relatively constant firing rate for any cell, with fast transitions between the states corresponding to a change in firing rates coordinated across all cells. Sequences are reproducible and taste specific, whereas transition times vary from trial to trial, leading to a more smoothly varying trial-averaged rate for any neuron. Our first goal, which we achieved, was to reproduce these features of neural activity in a simulated system of neurons with the stimulus represented by a constant input. To achieve this we adapted a heteroclinic model, in which the system passes from one saddle point to another, making the original model more robust so that it could be implemented with networks of spiking neurons. Second, both prior analyses and our own, have demonstrated a change in neural activity pre-stimulus – the appearance of oscillations in the local field potential (related to spatially averaged neural firing) in the 8-12Hz μ range with a corresponding oscillation apparent in the temporal correlation of neural spike trains – that coincides with a switch to a disengaged or inattentive behavioral state of the awake rat. However, when a taste is administered, the μ oscillations are replaced by a state sequence similar to the one observed when the animal is attentive. Our second successful modeling goal was to find sets of parameters in which the pre-stimulus state could be switched in and out of an oscillatory mode, while the same switch – corresponding to a switch in attentiveness – did not destroy the state sequence during the stimulus. We used a bifurcation analysis of simplified, mean-field (firing-rate) models as well as an extensive parameter search using our spiking network, to achieve this goal. Our third experimental analysis demonstrated, somewhat surprisingly, that the trial-to-trial variability of the state sequence was larger when the animal is attentive. Our fourth analysis of experimental data indicated the difference in neural activity between attentive and inattentive conditions dipped dramatically upon stimulus onset for a period of 100-200ms, approximately the duration of the somatosensory epoch. Our final analyses of the cortical responses during inattentiveness demonstrated the possible pre-play or replay of the slow state sequences across the fast timescale of a μ oscillation. That is, the temporal correlations between spikes of different cells on a timescale of milliseconds during the pre-stimulus oscillations was ordered in the same manner as the temporal correlations on a timescale of a second, symptomatic of the state sequences, during stimulus delivery.
|Commitee:||Hagan, Michael, Katz, Donald B.|
|School Location:||United States -- Massachusetts|
|Source:||DAI-B 73/06, Dissertation Abstracts International|
|Keywords:||Chemosensory, Gustatory cortex, Mouth, Neural activity, Neural correlates, Taste processing|
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