Ensembles of gustatory cortical neurons anticipate and discriminate between tastants in a single lick

Front Neurosci. 2007 Oct 15;1(1):161-74. doi: 10.3389/neuro.01.1.1.012.2007. eCollection 2007 Nov.

Abstract

The gustatory cortex (GC) processes chemosensory and somatosensory information and is involved in learning and anticipation. Previously we found that a subpopulation of GC neurons responded to tastants in a single lick (Stapleton et al., 2006). Here we extend this investigation to determine if small ensembles of GC neurons, obtained while rats received blocks of tastants on a fixed ratio schedule (FR5), can discriminate between tastants and their concentrations after a single 50 muL delivery. In the FR5 schedule subjects received tastants every fifth (reinforced) lick and the intervening licks were unreinforced. The ensemble firing patterns were analyzed with a Bayesian generalized linear model whose parameters included the firing rates and temporal patterns of the spike trains. We found that when both the temporal and rate parameters were included, 12 of 13 ensembles correctly identified single tastant deliveries. We also found that the activity during the unreinforced licks contained signals regarding the identity of the upcoming tastant, which suggests that GC neurons contain anticipatory information about the next tastant delivery. To support this finding we performed experiments in which tastant delivery was randomized within each block and found that the neural activity following the unreinforced licks did not predict the upcoming tastant. Collectively, these results suggest that after a single lick ensembles of GC neurons can discriminate between tastants, that they may utilize both temporal and rate information, and when the tastant delivery is repetitive ensembles contain information about the identity of the upcoming tastant delivery.

Keywords: Bayesian generalized linear model; fixed ratio schedule; gustation, licking; gustatory cortex; multi-electrode neurophysiology; neural ensembles; rate and temporal coding.