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REPORT
1Department of Psychology, Binghamton University, Binghamton; and 2Department of Neurology and Neuroscience, Weill Medical College of Cornell University, New York, New York
Submitted 25 August 2006; accepted in final form 13 December 2006
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONGRANTSACKNOWLEDGMENTSREFERENCES |
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1/3), whereas information about taste quality was conveyed by spike timing in about half of the units. Different subsets of units contributed information for discrimination of flow rate and taste quality. |
INTRODUCTION |
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TOPABSTRACTINTRODUCTIONGRANTSACKNOWLEDGMENTSREFERENCES |
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), the portion of the response corresponding to the interval when behavioral decisions based on taste quality (sweet, sour, salty, or bitter) are made (Halpern and Tapper 1971). In the natural setting, variation in flow rate is a reflection of the active process of exploration associated with gustation. For example, when an animal licks a fluid from a sipper tube, the flow rate of the stimulus, i.e., the rate at which the stimulus flows across the tongue, depends on the rate at which the animal swipes its tongue across the opening of the tube as well as the turbulence created by tongue and jaw movements as the animal moves the stimulus around the oropharyngeal cavity. Changes in flow rate resulting from these investigative movements may intensify the taste sensation in preparation for further taste reactivity, e.g., swallowing, gaping, etc., and are known to affect perception of taste intensity in humans (Meiselman et al. 1972). Further, both flow rate and taste stimulus concentration modulate the magnitude of the early transient of the chorda tympani nerve (CT, a branch of the facial nerve innervating taste buds on the rostral 2/3 of the tongue) response, suggesting that both characteristics may share common coding mechanisms.
In the present study, we describe the coding mechanisms for stimulus flow rate in the nucleus of the solitary tract (NTS), the first relay in the central gustatory neuraxis and the target of CT projection. In the context of recent work showing that information about taste quality can be conveyed by the temporal characteristics of the early NTS response (the same portion of the response that would be predicted to reflect flow rate) (Di Lorenzo and Victor 2003), the influence and potential interaction of taste quality and flow rate on temporal coding was a special focus of this study.
Twenty-two male Sprague-Dawley rats (250–350 g) were used in these experiments. Animals were housed individually in stainless steel cages, maintained on a 12-h light-dark cycle with ad libitum food and water. Rats were anesthetized with urethan (1.5 g/kg ip, administered in 2 equal doses spaced 30 min apart) and pentibarbital sodium (Nembutal; 25 mg/kg ip) and prepared surgically for electrophysiological recording in the NTS (see Di Lorenzo and Victor 2003) with core temperature maintained at 37°C via a thermistor-controlled heating pad. Single units in the taste-responsive portion of the NTS were located and recorded with tungsten microelectrodes (18–20 M
@ 1 kHz; FHC) using standard electrophysiological recording techniques described previously (Di Lorenzo and Victor 2003).
Taste stimuli included NaCl (0.1 M), HCl (0.01 M), quinine HCl (0.01 M), and sucrose (0.5 M) presented at room temperature. NaCl was delivered at two flow rates, 3 and 5 ml/s. The other tastants were presented at 5 ml/s. Although these flow rates are relatively high, they were chosen to correspond to those used by Smith and Bealer (1975) to facilitate direct comparisons of NTS responses with those in the CT nerve. Tastants were bathed over the tongue through a specially designed stimulus delivery system described in detail elsewhere (Di Lorenzo and Victor 2003). Flow was regulated by a pinch valve positioned on the tube leading from the reservoir to the mouth. Flow rates were calibrated daily prior to each experiment. For variations in flow rate for NaCl, the output of the NaCl reservoir was directed through two different solenoids and two different pinch valves (each imposing a different flow rate) to the same mouth tube. Calibration tests confirmed that this system produced an even flow rate across the entire 5-s stimulus presentation, including the initial portion, for all taste stimuli including NaCl presented at both high and low flow rates.
Taste stimulation trials consisted of a 10-s baseline, 10-s distilled water (for tactile adaptation), 5-s stimulus, 10-s wait, and 20-s distilled water rinse. Interstimulus intervals were 
2 min. To begin, each of four standard taste stimuli were presented in individual trials, all at the high flow rate. Next, for nine cells, NaCl trials were presented repeatedly in alternate trials at the low and high flow rates for as long as the cell was isolated. For the remaining 13 cells, blocks of tastants consisting of NaCl (high flow rate), NaCl (low flow rate), and sucrose, quinine, and HCl (all at the high flow rate) were presented repeatedly for as long as the unit remained well isolated.
Isolation of single units was accomplished using specialized software (Spike2, CED). Action potentials were stamped with the time of occurrence (resolution = 1 ms) relative to the beginning of each stimulus trial. Response magnitude was measured as the rate of firing in spike/second (sps) in the first 2 s of the response minus the firing rate in the final 5 s of water presentation. A change in the average firing rate over the first 2 s of stimulus presentation that differed from the average firing rate during water presentation (last 5 s) by 2.54 SD was defined as a significant response. To assess the breadth of tuning of taste-responsive NTS cells, an uncertainty measure (Smith and Travers 1979) was calculated for each unit using the response magnitudes across taste stimuli presented at the high flow rate; a value close to 1.0 indicated that the cell responded nearly equally well to all tastants tested (broad tuning), whereas a value close to 0 indicated that the cell responded to a single taste stimulus (narrow tuning).
To characterize the contribution of the temporal structure of a response to coding of flow rate or taste quality, spike trains were analyzed by the metric space method of Victor and Purpura (1996, 1997; recently reviewed in Victor 2005). This analysis is based on a family of metrics that measure "distance" (i.e., dissimilarity) between spike trains. Each of these metrics represents the minimum "cost" of transforming one spike train into another by changing a different aspect of the spike trains to be compared. Here, these included the number of spikes and the precise timing of spikes. The simplest metric, Dcount, compares the number of spikes contained in two spike trains associated with two responses. In this case, adding or deleting a spike incurs a cost of 1 and shifting the time of spikes incurs no cost. That is, Dcount is simply the arithmetic difference between the number of spikes in each response.
To measure the difference between two spike trains in terms of the arrangement of spikes in time, the metric Dspike[q] was used. Dspike[q] is a parametric family of metrics in which the parameter q determines how close in time two spikes need to occur to be considered equivalent. The cost of adding or deleting a spike is set at "1" as in Dcount, and in addition, the cost of moving a spike by an amount of time t is set at qt where q is in units of 1/s. Each metric provides for a classification (clustering) of responses. The extent to which this clustering faithfully reflects the stimulus is quantified by transmitted information, H. The transmitted information was calculated at a range of values of q. The maximum value of H(q) is denoted Hmax, and the value of q at which Hmax is achieved is denoted qmax.
In the present experiment, we analyzed the NaCl responses when NaCl was presented at high and low flow rates separately from the dataset of responses to NaCl, sucrose, quinine, and HCl presented at the high flow rate. Thus the maximum possible value of H for discrimination of flow rate was 1 (log2 2 = 1) and the maximum possible value of H for the discrimination of taste quality was 2 (log2 4 = 2). For both datasets, the relative contribution of spike count and spike timing to the information conveyed by taste responses were quantified using these methods.
Two auxiliary analyses were carried out as detailed by Victor and Purpura (1996). The first analysis ("surrogate shuffled") controlled for well-known upward bias in the estimation of H due to chance correlations in limited data (Treves and Panzeri 1995). Briefly, values of H calculated by classifying the observed responses were compared with values H0 obtained from 10 to 40 surrogate datasets in which the tastants associated with each response were randomly scrambled. Only values of H that exceed the range (mean ± 2 SD) of values of H0 can be considered to represent better-than-chance classification.
The second analysis ("exchange resampling") determined the extent to which the rate envelope, i.e., changes in firing rate during the time course of the response, could account for the observed contribution of temporal firing pattern to H. Here surrogate data sets were created that matched the poststimulus time histograms of the observed responses in terms of the rate envelope and that had the same number of spikes in each response but which differed from the observed response in the precise arrangement of spikes in time. We then compared values of Hmax obtained from the recorded data with values Hmax(exchange) obtained from the same analysis on 10–40 exchange-resampled datasets using Dspike[qmax]. If H was above the range (mean ±2 SD) of values of Hmax(exchange), we concluded that the observed temporal coding is not merely due to the rate envelope of the response to each tastant (with the overall variability in spike count taken into consideration) and that the arrangement of spikes in time in individual trials contributes additional information.
Responses from 22 cells to NaCl presented in repeated trials at both flow rates were recorded from single units in the NTS. In 13 of those units, responses to repeated presentations of the other three tastants were also recorded. The number of stimulus repetitions ranged between 10 and 40. Across all units, the mean spontaneous rate was 2.38 ± 0.62 (SE) sps, and the order of effectiveness for all tastants tested was NaCl>HCl>sucrose>quinine. Sixteen units (73%) responded best to NaCl, 6 (37%) to HCl, and none to sucrose or quinine. In general, taste units were broadly tuned with 8 cells (36%) responding to all 4 taste stimuli, 10 (46%) to 3 stimuli, 3 (14%) to 2 stimuli, and 1 (4%) to a single taste stimulus. Average Uncertainty measure across units was 0.80 ± 0.02 SE. Table 1 shows the spontaneous rates, breadth of tuning and response magnitudes for all units.
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). Results from one unit (FR55; 1 of 13, 8%) suggested that the rate envelope contributed information about taste quality [Hmax was not significantly different from Hmax(exchange)]. Only two units (FR51 and FR54; 2 of 13, 15%) showed evidence that spike timing contributed information about both taste quality and flow rate, albeit at different levels of temporal precision (values of q). Figure 1 shows examples of the analysis of temporal coding of flow rate (FR11) and taste quality (FR50) taken from two different units. In Fig. 1A, left, it can be seen that the average firing rates produced by NaCl presented at a high and low flow rates were approximately equivalent. This suggests that response magnitude is a poor indicator of flow rate in this unit. In Fig. 1A, right, results of the analyses of temporal coding show that spike timing contributes a significant amount of information to the discrimination of flow rate (Hmax – Hcount = 0.439, q = 32). In Fig. 1B, left, it can be seen that the average responses magnitudes evoked by NaCl (at both high and low flow rates), HCl, and quinine were similar across trials, suggesting that spike count alone is not sufficient to encode differences among them. Analyses of the contribution of temporal coding (Fig. 1B, right), however, show that spike timing adds a significant amount of additional information to this discrimination (Hmax – Hcount = 0.627, q = 11.3). In both Fig. 1, A and B, the fact that the information contributed by spike timing of the response was significantly larger than the corresponding amount of information contributed by the "exchange" surrogate data set (i.e., Hmax was significantly larger than Hexchange) shows that spike timing per se, and not just the firing rate envelope, conveys information.
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It is worth noting that neither spike count nor spike timing can perfectly convey differences in the flow rate of a stimulus. This is evident in the fact that the median amount of information about flow rate that was conveyed by either of these coding mechanisms was 0.34 bits (range: 0.003–0.81 bits), far short of the 1.0 bit needed for perfect discrimination. Although it is possible that information about flow rate may be encoded in a structure other than, or perhaps in addition to the NTS, another explanation might be that flow rate may be encoded primarily by tactile cells. Because most taste-responsive cells in the NTS also respond to tactile stimuli (Ogawa et al. 1984) (also, as evidenced by the responses to water), they might also participate in signaling this aspect of a taste stimulus. However, because taste intensity is enhanced by flow rate (Meiselman et al. 1972), it is possible to predict that, like flow rate, changes in taste stimulus concentration will also be signaled by the temporal features of the response.
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TOPABSTRACTINTRODUCTIONGRANTSACKNOWLEDGMENTSREFERENCES |
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONGRANTSACKNOWLEDGMENTSREFERENCES |
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FOOTNOTES |
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Address for reprint requests and other correspondence: P. M. Di Lorenzo, Dept. of Psychology, Box 6000, Binghamton University, Binghamton, NY 13902-6000 (E-mail: diloren{at}binghamton.edu)
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REFERENCES |
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TOPABSTRACTINTRODUCTIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Hallock RM, Di Lorenzo PM. Temporal coding in the gustatory system. Neurosci Biobehav Rev 30: 1145–1160, 2006.[CrossRef][ISI][Medline]
Halpern BP, Tapper DN. Taste stimuli: quality coding time. Science 171: 1256–1258, 1971.
Katz DB, Simon SA, Nicolelis MA. Dynamic and multimodal responses of gustatory cortical neurons in awake rats. J Neurosci 21: 4478–4489, 2001.
Lestienne R. Spike timing, synchronization and information processing on the sensory side of the central nervous system. Progr Neurobiol 65: 545–591, 2001.[CrossRef][ISI][Medline]
Meiselman HL, Bose HE, Nykvist WE. Effect of flow rate on taste intensity responses in humans. Physiol Behav 9: 35–38, 1972.[CrossRef][Medline]
Nagai T, Ueda K. Stochastic properties of gustatory impulse discharges in rat chorda tympani fibers. J Neurophysiol 45: 574–592, 1981.
Ogawa H, Imoto T, Hayama T. Responsiveness of solitario-parabrachial relay neurons to taste and mechanical stimulation applied to the oral cavity in rats. Exp Brain Res 54: 349–358, 1984.[ISI][Medline]
Smith DV, Bealer SL. Sensitivity of the rat gustatory system to the rate of stimulus onset. Physiol Behav 15: 303–314, 1975.[CrossRef][Medline]
Smith DV, Travers JB. A metric for the breadth of tuning of gustatory neurons. Chem Senses 4: 215–229, 1979.
Treves A, Panzeri S. The upward bias in measures of information derived from limited data samples. Neural Comput 7: 399–407, 1995.
Victor JD. Spike train metrics. Curr Opin Neurobiol 15: 585–592, 2005.[CrossRef][ISI][Medline]
Victor JD, Purpura KP. Nature and precision of temporal coding in visual cortex: a metric- space analysis. J Neurophysiol 76: 1310–1326, 1996.
Victor JD, Purpura KP. Metric-space analysis of spike trains: theory, algorithms and application. Network 8: 127–164, 1997.
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