title: Influence of response variability on the coding performance of central gustatory neurons.
abstract: We explored how variability in responding to taste stimuli could impact the signaling of taste quality information by neuron types and individual cells in the nucleus of the solitary tract. One hundred sixty-two neurons recorded from anesthetized rats were grouped using multivariate analysis of taste responses to the following (in m): 0.5 sucrose, 0.1 NaCl, 0.01 HCl, and 0.01 quinine-HCl. Neurons fell into one of three groups corresponding to cell types that responded optimally to sucrose, NaCl, or HCl. A statistical model was used to examine whether responses observed among neurons within each group could be correctly attributed to the optimal stimulus or another tastant on the basis of spike count. Results revealed poor classification performance in some cases attributable to wide variations in the sensitivities of neurons that compose a cell type. This outcome leads us to question whether neuron types could faithfully encode a single taste quality. We then theoretically explored whether a hypothetical observer of individual neurons could discriminate between spiking rates to different tastants during the first second of stimulus processing. Spike rate was found to be an unreliable predictor of stimulus quality for each neuron tested. However, additional analyses suggested that taste stimuli could be identified by a reader that attends to the relative spiking activities of different kinds of neurons in parallel. Rather than assigning meaning to individual neurons or categories of them, central gustatory circuits may signal quality information using a strategy that involves the relative activities of neurons with different sensitivities to tastants.
authors.affiliation: Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA. chris@utmem.edu
authors.forename: Christian H
authors.initials: CH
authors.lastname: Lemon
authors.forename: David V
authors.initials: DV
authors.lastname: Smith
mesh_terms: D000200:Action Potentials; D000818:Animals; D008959:Models, Neurological; D015233:Models, Statistical; D009474:Neurons / Q000502:physiology*; D012372:ROC Curve; D051381:Rats; D017552:Solitary Nucleus / Q000166:cytology / Q000502:physiology*; D013649:Taste