Parabrachial Neural Coding of Taste Stimuli in Awake Rats

Hisao Nishijo and Ralph Norgren

Department of Physiology, Faculty of Medicine, Toyama Medical and Pharmaceutical University, Toyama 930-01, Japan; and Department of Behavioral Science, College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania 17033

    ABSTRACT
Abstract
Introduction
Methods
Results
Discussion
References

Nishijo, Hisao and Ralph Norgren. Parabrachial neural coding of taste stimuli in awake rats. J. Neurophysiol. 78: 2254-2268, 1997. In awake, behaving rats, the activity of 74 single neurons in the pontine parabrachial nucleus (PBN) was recorded in response to sapid stimulation by 15 chemicals. Of these, 44 taste cells were tested with all 15 stimuli. Based on their responsiveness to 4 standard stimuli, these neurons were categorized as follows: 23 NaCl-best, 15 sucrose-best, 5 citric acid-best, and 1 quinine HCl-best. Several forms of multivariate analyses indicated that the taste responses matched both the behavioral responses to and, less well, the chemical structure of, the sapid stimuli. A hierarchical cluster analysis of the neurons substantially confirmed the best-stimulus categorization, but separated the NaCl-best cells into those that responded more to Na+-containing salts and those that responded more to Cl--containing salts. The cells that responded best to the Na+ moiety actually were somewhat more correlated with the sucrose-best cells than with those that responded to the Cl--containing stimuli. Citric acid-best neurons and the lone quinine-best unit formed a single cluster of neurons that responded well to acids, as well as to NH4Cl and, to a lesser extent, NaNO3. A factor analysis of the neuronal response profiles revealed that three factors accounted for 78.8% of the variance in the sample. Similar analyses of the stimuli suggested that PBN neurons respond to four or five sets of stimuli related by their chemical makeup or by human psychophysical reports. The capacity of rats to make these discriminations has been documented by other behavioral studies in which rodents generalize across sapid chemicals within each of 5 stimulus categories. Furthermore, a simulation analysis of the neural data replicated behavioral results that used amiloride, a Na+ channel blocker, in which rats generalized NaCl to non-Na+, Cl- salts. Thus, using a variety of analyses, in awake rats, the activity of PBN taste neurons tracks their behavioral responses to a variety of chemical stimuli.

    INTRODUCTION
Abstract
Introduction
Methods
Results
Discussion
References

Behavioral studies using response generalization paradigms indicate that rodents discriminate easily between sucrose, NaCl, HCl, and quinine HCl, the chemicals often used to exemplify the four taste qualities commonly recognized by humans: sweet, sour, salty, and bitter (Frank and Nowlis 1989; Morrison 1967; Nachman 1963; Nowlis et al. 1980; Yamamoto et al. 1985). In a conditioned taste aversion test, a variety of other chemicals also generalize to one or another of these exemplars. For instance, fructose and glycine generalized to sucrose, monosodium glutamate (MSG) and NaNO3 generalized to NaCl, and citric acid generalized to HCl. Nevertheless, animals fail to associate other chemicals commonly used as sapid stimuli with any of the four standards. Maltose and Polycose are highly preferred by rats, but apparently taste different from sucrose (Nissenbaum and Sclafani 1987; Nowlis and Frank 1981; Spector and Grill 1988). Polycose contains contaminants such as Na+, K+, and Ca2+, as well as small amounts of glucose and maltose, but its attractiveness appears to derive from glucose polymers (Rehnberg et al. 1996). Although structurally unrelated to sugars, glycine and proline are both highly preferred by rats and apparently taste similar to sucrose (Pritchard and Scott 1982). Although hamsters or rats generalize MgSO4, MgCl2, NH4Cl, and KCl to quinine HCl (Frank and Nowlis 1989; Nowlis et al. 1980; Yamamoto et al. 1985), multivariate anayses of neuronal data suggested that their taste quality might be different from that of quinine HCl (Andersen and Hartmann 1971; Schiffman and Erickson 1971). In human, these chemicals were bitter-salty rather than bitter (Schiffman and Erickson 1971). Based on this limited stimulus array, these results suggest that rodents can discriminate at least five, and perhaps six, taste categories: sweet (sucrose), sour (HCl), salty (NaCl), bitter (quinine HCl), and non-NaCl salts (e.g., MgCl2, NH4Cl, and KCl). The sixth might be elicited by di- and polysaccharides of glucose. Other categories are possible, but, with the exception of umami, which we have treated elsewhere (Nishijo et al. 1991), the evidence for the involvement of the gustatory system is less compelling.

In anesthetized rodents, most single-unit studies found that neurons in the brain stem responded more broadly to taste stimuli than those on the periphery (Ganchrow and Erickson 1970; Smith et al. 1979; Travers and Smith 1979; Travers et al. 1987; Van Buskirk and Smith 1981). This might be taken as evidence for central convergence. In most cases, however, only a single receptor subpopulation was stimulated, so that any central convergence must derive from only one gustatory nerve. Anatomic and electrophysiological evidence does exist for convergence of peripheral taste nerves within the first central relay in the nucleus of the solitary tract (NST) (Hamilton and Norgren 1984; Sweazey and Smith 1987; Travers and Norgren 1991, 1995; Travers et al. 1986). In fact, in awake, behaving rats, gustatory responses in both the NST and parabrachial nuclei (PBN) are more narrowly tuned than those reported from either peripheral or central neurons in anesthetized preparations (Nakamura and Norgren 1991; Nishijo and Norgren 1990b; 1991). Although this difference may be due to the direct effects of general anesthesia, it also may be a consequence of the mutual inhibition that apparently exists between receptor subpopulations (Bartoshuk et al. 1994).

Previous behavioral studies indicated that decerebrate rats, which can use only the NST and the PBN to process the taste information, discriminated at least four stimulus categories (Grill and Norgren 1978a,b). Direct comparisons between neural and behavioral data are difficult to obtain, however, because in most anesthetized animals only a fraction of the receptors are stimulated and because in awake, behaving rats only four stimuli have been tested (Nakamura and Norgren 1991; Nishijo and Norgren 1990b, 1991). To investigate neural coding of taste quality in the PBN of behaving rats, we expanded this basic stimulus series to a battery of 15 chemicals that spanned at least the 6 taste categories suggested by behavioral experiments. Preliminary reports of these data have appeared in abstract or summary form (Nishijo and Norgren 1990a; Norgren et al. 1994). The neural responses to MSG, several nucleotides, and a subset of the stimulus array were analyzed separately in a different context (Nishijo et al. 1991).

    METHODS
Abstract
Introduction
Methods
Results
Discussion
References

The expanded array of stimuli is identical to that used for the NST experiment (Nakamura and Norgren 1993) and the experimental methods, identical to those used previously for recording from the PBN (Nishijo and Norgren 1990b). Because gustatory responses elicited by either intraoral infusions or licking differ little from one another (Nishijo and Norgren 1991) and infusions result in more stable recording, we used intraoral cannulas to deliver the fluids in this experiment.

Animals and surgery

Five male, Sprague-Dawley rats were used (370-440 g, Charles River). Before surgery, the rats were acclimated by handling and accustomed to being placed into a small, plastic restraining cage for brief periods. Surgical procedures were performed under aseptic conditions in two stages. The rats were food deprived overnight, given atropine the next morning (0.1 mg/rat ip), then anesthetized [pentobarbital sodium (Nembutal), 50 mg/kg ip] and mounted in a stereotaxic apparatus with the skull leveled between the beta  and lambda  suture points. The cranium was exposed and six to eight sterile, stainless steel screws (1-72 × 1/8 in.) were threaded into holes in the skull to serve as anchors for dental acrylic. Stainless steel wire, soldered to one or two screws, served as a ground. The acrylic was molded around the conical ends of two sets of stainless steel rods that were attached rigidly to the earbars. During subsequent chronic recording sessions, these rods were attached more medially on the earbars and fitted back into the acrylic impressions, thus painlessly fixing the rat's head in the stereotaxic plane. Twonichrome wires (60 µm diam, Formvar insulated) were inserted into the genioglossus muscle (Travers and Norgren 1986), and an intraoral cannula (PE-100, Clay Adams) was implanted on either side, just anterior to the first maxillary molar (Phillips and Norgren 1970). The electromyograph (EMG) wires and intraoral cannulas were routed subcutaneously to the skull and attached to the acrylic cap. An antibiotic was administered after the surgery (Di-Trim, Syntex Animal Health, 0.05 ml sc).

Training

After recovery (10-14 days), the rats were reacclimated to the plastic restraining cage (Clear Acrylic, Fisher Scientific) (see Norgren et al. 1989 for an illustration), placed on a 23-h water-deprivation regimen, and trained to take 0.3 M sucrose from a spout while in the restrainer (1-2 h daily). With their heads fixed in the stereotaxic instrument, the sucrose was replaced gradually with distilled water, first via the spout and then the intraoral cannulas (Nishijo and Norgren 1990b, 1991). Throughout training and recording, if the rats failed to ingest at least 15.0 ml of water while in the restrainer, they received the remainder in their home cages. In their home cages, they were fed ground rat pellets that contained 30-50% water by weight. They were weighed weekly to ensure that they did not lose weight.

Localization

After training for ~1 mo, rats were reanesthetized (Nembutal, 50 mg/kg ip) and mounted in the stereotaxic instrument. Just caudal to the interparietal suture, a 2- to 3-mm diam area of the acrylic and underlying bone was drilled away, the exposed dura excised, and the PBN gustatory area located electrophysiologically using an electrode oriented 20° toward the anterior to avoid puncturing the transverse sinus. Subsequently, a 1.0- to 1.5-mm diam hole was drilled through the interparietal bone on the midline, and a 178-µm diam stainless steel wire, insulated except at the cross-section of the tip, was implanted in the dorsal pons to serve as an indifferent electrode. The recording exposure was treated with hydrocortisone ointment (Neo-Cortef, Upjohn) or a few drops of chloramphenicol solution (0.1 g/ml), covered with a sterile Teflon sheet, and sealed with an epoxy glue. All animals received water ad libitum during a 5- to 7-day recovery period and then were placed back on the water-deprivation regimen.

Electrophysiological recording and sapid stimuli

After the animal was placed in the stereotaxic apparatus, the Teflon sheet and ointment were removed, and a glass-insulated tungsten microelectrode (Z = 1.5-3.5 MOmega at 1.0 kHz) was advanced through the cerebellum into the PBN using the coordinates derived during the acute recording session. Extracellular neural activity and EMG responses were monitored on an oscilloscope and recorded on magnetic tape (2340, TEAC). After isolating a single unit, a trial began with 0.05 ml of distilled water applied via the ipsilateral intraoral cannula, then a similar amount of a sapid stimulus, followed by at least one water rinse of the same volume, all at room temperature (23-24°C). During long intertrial intervals, such as when searching for a single neuron, small amounts of water were delivered via the contralateral cannula. The minimum interval between water and stimulus application was 15 s, and between one taste stimulus and the next, 45 s. After the initial screening with the 4 standard stimuli (NaCl, sucrose, citric acid, and quinine HCl), up to 11 other sapid solutions also were tested. The 15 sapid stimuli and their concentrations (Table 1) were identical to those used in a similar experiment that involved recording from the NST (Nakamura and Norgren 1993). Given the number of stimuli in the array, only a single concentration of each was used. The four standard chemicals have been tested across a concentration range (Nishijo and Norgren 1990b). The concentrations of those stimuli used here were in the mid- to upper range of effectiveness in terms of driving parabrachial neurons, and all were capable of eliciting behavioral effects. The concentrations for the other stimuli either matched that of the chemically related moiety from the four standards or, in the case of glycine and Polycose, elicited preferences as great or greater than the concentration chosen for the sugars. Some neurons were tested further with 0.5 mM disodium 5'-guanylate (GMP) and a mixture of 0.1 M monosodium L-glutamate (MSG) and 0.5 mM GMP. The results from these two complex stimuli were analyzed separately and have been published elsewhere (Nishijo et al. 1991).

 
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TABLE 1. Chemicals and their molar concentrations

Data analysis

Neural activity was detected using a two-level voltage discriminator that was monitored continuously on a storage oscilloscope during analysis. The discriminator pulses were accumulated in peristimulus histograms with 250-ms bins, but all subsequent data analysis was based on total activity in 5.0-s samples. When more than one trial of a particular stimulus occurred, the mean was used. Spontaneous activity and responses to prestimulus water were calculated from multiple, 5.0-s samples. A water response was considered significant when neural activity during the prestimulus water trials differed from the mean spontaneous rate by ±2.5 SD. Similarly, when activity during taste trials differed by ±2.5 SD from the mean of the prestimulus water trials, this was considered a significant gustatory response. This relatively stringent criterion was adopted because, in most cases, a neuron was tested only once with each chemical stimulus. This rationale is spelled out in greater detail in prior publications (Nakamura and Norgren 1991; Nishijo and Norgren 1990b). All statistical analyses used corrected data in which the spontaneous activity was subtracted from the water response and the water response from the gustatory response.

To compare these data with earlier samples, two forms of analysis used only responses to the four standard stimuli that were common to all four studies (Nakamura and Norgren 1991, 1993; Nishijo and Norgren 1990b). First, each neuron was categorized on the basis of its best stimulus (i.e., the chemical that produced the greatest number of spikes in 5.0 s), its second best stimulus, and any effective stimuli (i.e., the chemical that produced a significant response using our criterion). Second, for each neuron, the breadth of responsiveness was calculated from the formula for entropy based on the excitatory component of the activity generated by each of the four standard chemicals (i.e., NaCl, sucrose, citric acid, and quinine HCl) (Smith and Travers 1979). The entropy measure (H) of each neuron was given by the following formula
<IT>H</IT> = −1.661 <LIM><OP>∑</OP><LL><SUB><IT>i</IT>=1</SUB></LL><UL>4</UL></LIM><IT>p<SUB>i</SUB></IT>(log <IT>p<SUB>i</SUB></IT>)
The neural data also were treated with several multivariate analyses that used the responses to all 15 stimuli in the array. The cluster analysis utilized Pearson's product-moment correlation coefficients and the average linkage method (Biomedical Computer Program, BMDP1M). The multidimensional scaling (MDS) employed the metric ratio and Euclidean model (SYSTAT statistical package, Guttman scaling method). To avoid a degenerate MDS, the data were normalized so that the maximum response of each neuron to the stimuli was the same (Erickson et al. 1993). The dissimilarity (Euclidean distance) between each possible pair of chemicals or neurons was calculated and analyzed using the MDS program. The statistical criteria, categories, and numerical analyses were identical to those used in a previous study (Nishijo and Norgren 1990b) except that Euclidean distance was used instead of correlation coefficients in the MDS. Factor analysis was accomplished using the principal component procedure and Varimax orthogonal rotations (Biomedical Computer Program, BMDP4M; SYSTAT statistical package) using the original, nonnormalized data. The number of factors was determined according to the Kaiser criterion and scree method (Bieber and Smith 1986).

Histological analysis

After the recording sessions, the animals were reanesthetized (Nembutal, 50 mg/kg ip), and small electrolytic lesions (20 µA for 10 s) were made at the rostral, caudal, lateral, and medial margins of the gustatory responsive area in the pons. Then the rats were given a further, lethal dose of Nembutal (100 mg/kg ip) and perfused intracardially with 0.9% saline and 10% Formalin. Relevant blocks of neural tissue were sectioned on a freezing microtome at 40 or 50 µm and stained with cresyl violet.

    RESULTS
Abstract
Introduction
Methods
Results
Discussion
References

Histology

We explored the PBN in five rats: two bilaterally and three unilaterally. Single or multiunit gustatory activity was recorded from 275 of the 396 electrode penetrations. Based on the stereotaxic coordinates and the marking lesions, the neurons were isolated from the caudomedial quadrant of the PBN above, below, and probably within the brachium conjunctivum. This location is consistent with our previous samples (Nishijo and Norgren 1990b, 1991) and with acute experiments in which localization was an objective (Norgren and Pfaffmann 1975).

General characteristics of taste neurons

A total of 74 single neurons was tested with the 4 standard chemicals, and in 70 at least 1 of these stimuli elicited a significant response. Of these 70 neurons, 41 also gave significant responses to water. The remaining 4 cells responded significantly only to water. Most taste responses, and all of those in a best-stimulus category, were excitatory. In four taste neurons, one or two sapid chemicals elicited significant inhibitory responses. The mean spontaneous rate of the 70 taste neurons was 11.2 ± 0.8 (SE) spikes/s. Figure 1 depicts raw records of a PBN taste neuron responding to 10 of the 15 stimuli in the array. Based on our ±2.5 SD criterion, this unit responded briskly to 0.1 M NaCl (Fig. 1C) and to other Cl--containing chemicals such as 0.1 M KCl, NH4Cl, and MgCl2 (Fig. 1, H-J). Its response to water also was significant (Fig. 1B) but those to sucrose (D), citric acid (E), quinine HCl (F), MSG (G), fructose (K), and HCl (L) were not.


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FIG. 1. Raw records of a parabrachial taste neuron (unit 39) during control (A), intraoral infusion of water (B), and sapid solutions (C-L). Arrows indicate infusion onset. Note the slight, but significant response to water. MSG, monosodium glutamate.

The complete array of stimuli was tested on 44 neurons. For this sample, the order of effectiveness of the standard chemicals (at the standard concentrations) was NaCl > sucrose > citric acid > quinine HCl (Fig. 2). The PBN taste neurons also responded well to the other Na+ salts (MSG and NaNO3) and glycine, moderately to the non-Na+, Cl- salts and sweet chemicals (fructose and maltose), and less to Polycose, HCl, and malic acid (Fig. 2). Among the salts, those that contain Na+ (NaCl, MSG, NaNO3) elicited significantly stronger average responses than those that contain Cl- but not Na+ [Fisher's LSD test after 1-way analysis of variance (ANOVA), P < 0.05]. Of the normally preferred chemicals, sucrose and glycine were equally effective, but sucrose elicited significantly stronger responses than fructose, maltose, or Polycose (Fisher's LSD test after 1-way ANOVA, P < 0.05). No significant differences in response magnitude existed among acids and quinine HCl (Fisher's LSD test after a 1-way ANOVA, P > 0.05).


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FIG. 2. Mean response profiles of 44 parabrachial taste neurons to 15 taste stimuli. Error bars indicate SE. NACL, sodium chloride; SUC, sucrose; CA, citric acid; QHCL, quinine hydrochloride; NANO, sodium nitrate; KCL, potassium chloride; NHCL, ammonium chloride; MGCL, magnesium chloride; FRU, fructose; MAL, maltose; GLY, glycine; POLY, Polycose; HCL, hydrochloride; MA, malic acid.

Based on their largest response to the 4 standard sapid stimuli, the 44 taste neurons were classified as follows: 23 NaCl-best, 15 sucrose-best, 5 acid-best, and 1 quinine-best. Figure 3 depicts the response profiles of these neurons to four standard taste stimuli, two Na+ salts (MSG and NaNO3), and water (A), and those to the other nine sapid solutions (B). In Fig. 3A, taste neurons are grouped into best-stimulus categories and, within those categories, they are arranged in descending order of response magnitude to the best stimulus, beginning with the NaCl-best neurons on the left, followed by the sucrose-best, citric acid-best, and quinine-best cells. The same ordering is maintained in Fig. 3B. In this sample of 44 taste neurons, 17 (38.6%) responded significantly to only a single one of the four standard chemicals [Ns (NaCl specific) = 12; Ss = 4; Cs = 1]. Because it is based only on the responses to the 4 standard sapid solutions, the terminology does not imply anything about the responses to the 11 other chemicals in the expanded array.


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FIG. 3. Response profiles of 44 parabrachial taste neurons to 4 standard taste stimuli, 2 Na+ salts, and water (A), and those to the other 9 sapid solutions (B). Taste neurons are grouped into best-stimulus categories and arranged within those categories in descending order of response magnitude to the best stimulus. Vertical dashed lines indicate boundaries between best-stimulus categories. Taste responses are adjusted for water responses, and responses to water for spontaneous discharge rates. Bottom: spontaneous discharge rates with unit numbers. Filled bars indicate significant responses, i.e., ±2.5 SD from spontaneous rate (water) or from water responses (tastes). Up bars indicate excitatory responses; down bars, inhibitory ones.

Typical response profiles of individual neurons appear in Fig. 4. The first three units are NaCl-specific (Ns), but nevertheless reveal two distinct profiles (A). Unit 19 responded only to the chemicals that contain Na+ cations (NaCl, MSG, and NaNO3). Units 39 and 35, on the other hand, responded exclusively to the salts that contain Cl- anions. Of the 12 NaCl-specific cells, 4 had profiles similar to unit 19, and 8 had profiles similar to unit 39. Of the 11 NaCl-best cells (as distinct from the NaCl-specific cells), most maintained the pattern evident in unit 36 in that they responded to Na+ salts, sucrose, fructose, and glycine, but seldom to other stimuli in the array. Units 16 and 28 are two of the four sucrose-specific (Ss; Fig. 4B). Of the 11 sucrose-best (Sb) cells, 6 responded 2nd best to NaCl and 5 to citric acid (Fig. 4B, unit 44). Although the responses often were relatively small, the citric acid-best cells (unit 15) and the quinine-best unit (unit 27) responded to more of the stimuli in the expanded array than did either the Na+-best or sucrose-best neurons (58% vs. 38 and 45%, respectively).


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FIG. 4. Nine typical response profiles of parabrachial neurons. Filled bars indicate significant taste response, i.e., 2.5 SD above or below water responses. Ns, neurons that respond only to NaCl among the 4 standard sapid chemicals; Nb+S, NaCl-best neuron with 2nd-best response to sucrose; Ss, sucrose-specific; Sb, sucrose-best; Cb, citric acid-best; Qb, quinine-best; +N, 2nd best response to NaCl; +CN, 2nd best response to citric acid, 3rd best response to NaCl. Other abbreviations as in Fig. 1.

The relationship of response category to breadth of response can be numerically expressed in terms of the entropy measure of Smith and Travers (1979), which usually is calculated from the response of each neuron to four standard stimuli. Although not linear, this value provides a criterion-free index of response specificity. A value of zero indicates that a neuron responded to only one of the four standard stimuli; a value of 1 indicates equal responsiveness to all four stimuli. For the 44 neurons tested with all 15 sapid chemicals, the mean entropy calculated from the excitatory component of the responses to the standard stimuli was 0.60. For the specific neurons, it was 0.39. When the absolute values of the responses were used, however, the entropy values were 0.68 and 0.55, respectively. This relatively greater increase in the value for the specific neurons compared with the entire sample could result from these neurons having a disproportionate amount of inhibitory activity, i.e., less excitation by sapid chemicals than by water alone. In fact, 76.5% (13/17) of the specific neurons had inhibitory responses to at least one of four basic stimuli, whereas only 33.3% (9/27) of the nonspecific cells exhibited such activity (Fisher's exact test, P < 0.01). This difference may reflect a mechanism by which these neurons achieve their relatively narrow response.

Neuronal relationships

HIERARCHICAL CLUSTER ANALYSIS. The dendrogram derived from a hierarchical cluster analysis of the 44 fully tested parabrachial taste neurons illustrates graphically the response relationships referred to above (Fig. 5). The unit numbers and their response categories are listed on the right of the dendrogram. The scale below it indicates the average correlation coefficient of neurons joined by a vertical line, i.e., the mean of the correlations of all possible pairs of neurons included in the cluster. At the level of the second division, labeled N1, C, N2, and S, the cluster analysis separates the neuronal sample almost perfectly into best-stimulus categories. The only exception is the lone quinine-best cell, which is situated in the cluster labeled "C" with the five acid-best neurons. The response profiles of these 6 units have an average correlation of just about 0.3. The neurons in the two "N" clusters, which responded best to NaCl, and all but 3 of those in the "S" cluster, which responded best to sucrose, have average correlations above 0.7. 


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FIG. 5. Dendrogram of 44 parabrachial neurons resulting from a hierarchical cluster analysis using Pearson's product-moment correlation coefficients and the average linkage method. Right: each neuron's number and stimulus response category (Nishijo and Norgren 1990b). Abscissa: cluster similarity between neurons or clusters. Cs, citric acid-specific; C, N, Q, or S stand for a significant response to citric acid, NaCl, quinine HCl, or sucrose, respectively. The order of the abbreviations reflects the relative magnitude of the responses. Other abbreviations as in Fig. 4.

This within-group similarity produced distinctive mean response profiles (Fig. 6). The cells in the N1 group were mostly NaCl-specific with respect to the four standard stimuli, but actually responded better to chemicals that contained Cl- rather than Na+. In fact they responded to very little else in the expanded array (1-way ANOVA, F = 48.8, P < 0.0001). As a group, these cells apparently discriminate Cl--containing salts from the other stimuli, but not from one other. All of the post hoc comparisons between a Cl--containing salts and the other stimuli were significant, but all comparisons among Cl- salts were not (Fisher's LSD, P < 0.01 and P > 0.05, respectively). Similarly, in the N2 group, in which more cells responded to NaCl and sucrose than to NaCl alone, mean responses to the 3 Na+-containing salts were indistinguishable, but reliable differences did exist between each of the Na+ salts and the other 12 sapid chemicals (1-way ANOVA, F = 31.91, P < 0.0001 with post hoc Fisher's LSD).


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FIG. 6. Mean response profiles of 44 parabrachial taste neurons by the category dependent on cluster analysis. Each group corresponds to that in Fig. 5. N indicates number of neurons. Other descriptions as for Fig. 2.

In the S cluster, the differences in average response magnitude were not as great as in the N groups. Nevertheless, these neurons responded differentially to the sugars, glycine, and MSG compared with the other sapid chemicals. The response to Polycose was anomalous because it was larger than those to some other stimuli, but statistically indistinguishable from NaCl, citric acid, and NaNO3 (1-way ANOVA, Fisher's LSD tests). Of the normally preferred stimuli, the order of effectiveness was sucrose = glycine > fructose, MSG, maltose > Polycose (Fisher's LSD test,P < 0.05). In the C-cluster, the acids, NH4Cl, and NaNO3 elicited similar responses (Fisher's LSD tests, P > 0.05), but other chemicals (NaCl, glycine, and MgCl2) also activated some of these neurons. This broad, variable responsiveness to the extended array accounts for the relatively low correlations within this group (Fig. 5).

Multidimensional scaling

Euclidean distances for dissimilarity between each possible pair of taste neurons were used for multidimensional scaling. Guttman's coefficients of alienation (0.289, 0.141, 0.082, and 0.038) represent the goodness of fit for dimensions 1-4, respectively. The three-dimensional solution depicted in Fig. 7 makes two points that cannot be drawn from the cluster analysis (Fig. 5) (Bieber and Smith 1986; Smith et al. 1983a,b). The sucrose-specific neurons (bullet ) and what might be called the Na+-specific neurons (black-triangle) are connected by a continuum of less specific cells of the same ilk. This distribution varies only slightly along dimension 3 and modestly in 2, but is separated distinctly from the NaCl-best cells that also responded to non-Na+, Cl- salts, primarily along dimension 3. In fact, only the lone citric acid-specific cell and the one quinine-best neuron show greater separation on dimension 3. 


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FIG. 7. Distribution of 44 parabrachial taste neurons in a 3-dimensional space resulting from multidimensional scaling. Neuron categories are as follows. NaCl-specific (Na): neurons responding only to Na+ salts; NaCl-best (Na): neurons responding best to Na+ salts but also to other chemicals; NaCl-specific (Cl): neurons responding to only Cl- salts; NaCl-best (Cl): neurons responding not only to Cl- salts but also to other standard solutions; sucrose-specific: neurons responding only to sucrose among the 4 standard sapid solutions; sucrose-best: neurons responding best to sucrose but also to one or more of the other standard chemicals; citric acid-specific: neurons responding only to citric acid among the 4 standard sapid solutions; citric acid-best: neurons responding best to acid but also to one or more of the other standard chemidals; quinine HCl-best: neurons responding best to quinine but also to one or more of the other standard chemicals.

Factor analysis

Hierarchical cluster analysis is useful because it provides an index of shared correlation among the response profiles of neurons. Multidimensional scaling organizes the same set of relationships but provides more detail because the relationship among any possible pair of neurons can be assessed and plotted in two or three dimensions. The multidimensional scaling analysis indicated that the Na+-sensitive and sucrose-sensitive neurons formed a continuum on at least one dimension. This suggests that each neuron in the continuum may share responsiveness to the same specific chemicals (i.e., NaCl and sucrose), but in different degrees. Factor analysis can expose these relationships but usually is presented without a visual analogue. When such an analysis is subjected to an orthogonal rotation, the terms generated, usually termed "loadings," are correlation coefficients. A factor analysis was performed on the responses of all 44 PBN taste neurons to all 15 stimuli using an orthogonal rotation (BMD program 4 M, SYSTAT). Application of the Kaiser criterion to the principal solution indicated that five factors accounted for 80.2% of the variance in the data (Table 2).

 
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TABLE 2. Factor loading matrix for 44 neurons resulted from orthogonal rotation (Varimax)

The highest correlations on factor 1 were with the 12 neurons that responded preferentially to the Na+ salts (range, 0.711-0.985). Thus, for these 12 neurons, factor 1 accounts for 50-97% of the variance in the neural activity generated by these 15 chemicals. Five of the sucrose-best cells had modest correlations with this factor (0.344-0.599), but only one of the NaCl-best units that responded to Cl- salts came even close to that range (0.294). Just the reverse is true for factor 3; the neurons that responded preferentially to Cl- salts correlated strongly with this dimension (0.873-0.958), but the truly Na+-sensitive units did not (-0.140 to +0.255). All except two of the sucrose-best cells had negative correlations with this factor (-0.396 to +0.218). The majority of sucrose-best neurons (12/15) had high, positive correlations with factor 2 (0.690-0.931); the remaining three had more modest relationships (0.332-0.517) that overlapped with the correlations for six of the Na+-sensitive cells (0.232-0.542). Aside from the single sucrose-best cell, factor 4 correlated most with the acid-best neurons (0.406-0.837); 33 of the remaining 38 cells had correlations between -0.31 and +0.1. The fifth factor was even more exclusive. Only 3 cells correlated with this dimension at more than -0.4, i.e., 0.16% of the variance. The two sucrose-best units were mentioned above; the 3rd was the lone quinine-best neuron, and its correlation was -0.693.

Stimulus relationships

HIERARCHICAL CLUSTER ANALYSIS. The relationships among the stimulus chemicals were analyzed via the matrix of correlation coefficients generated from the responses of these 44 PBN neurons (Table 3). The dendrogram of a hierarchical cluster analysis derived with the average linkage method appears in Fig. 8. In several respects, the stimulus dendrogram resembles the one for neurons (Fig. 5). The non-Na+, Cl- salts are connected first to the acids and quinine, whereas the Na+ salts first join to the normally preferred stimuli. The correlations within these first five clusters are greater (r > 0.6) than those between categories (r < 0.4). For the neurons, particularly those that respond best to acid or sucrose, the difference in average correlation within and between clusters is not as great as for the stimuli. Nevertheless, the overall similarity in the two dendrograms reinforces the impression that the activity in relatively small subsamples of neurons dominates the quality code for particular classes of chemicals.

 
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TABLE 3. Pearson's correlation coefficients among sapid stimuli


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FIG. 8. Dendrogram of 15 chemicals resulting from a hierarchical cluster analysis based on Pearson's correlation coefficients using 44 parabrachial taste neurons. See Fig. 2 for stimulus abbreviations.

Multidimensional scaling

The interstimulus relationships also were examined by multidimensional scaling and factor analysis. The Guttman's coefficients of alienation (goodness of fit) for the 1st 4 dimensions were 0.240, 0.073, 0.030, and 0.010, respectively. The 3-dimensional solution of the Guttman scaling model (SYSTAT; Fig. 9) revealed a somewhat different picture of these 15 sapid chemicals than apparent in the cluster analysis. The acids and the non-Na+, Cl- salts form relatively compact groups. Quinine HCl is about equidistant from the acids and Polycose. The four stimuli that are reported to be sweet by humans (3 sugars and glycine) are closer to one another than to the other stimuli, but not by much, particularly for MSG and Polycose. The Na+ salts appear to be well removed from the other stimuli, but in fact they are not. If considered in all three dimensions, MSG and NaNO3 are about equidistant from NaCl and the sweet stimuli. Sodium chloride, in turn, is situated by itself, separated about as much from the two other Na+ salts as from the non-Na+, Cl- salts. As with the neurons, this type of display emphasizes the continuousness of the interstimulus relationships, whereas the cluster analysis gives the impression of groups. Nevertheless, comparison of these two analyses reveals that, with the exception of the Na+ salts, chemically related stimuli that are joined in the cluster analysis also are generally closer to one another in the three-dimensional space.


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FIG. 9. Distributions of 15 sapid chemicals in a 3-dimensional space resulting from multidimensional scaling using Euclidean distances of 44 parabrachial taste neurons. See Fig. 2 for abbreviations.

Factor analysis

A factor analysis based on the responses of these 44 PBN neurons clearly identifies the chemical and psychophysical similarities between these 15 stimuli (Table 4; orthogonal rotation, BMD program 4 M, SYSTAT). The Kaiser's criterion for the principal solution indicated that four factors accounted for 85.8% of the variance in the data. The highest loadings on each factor go to the members of one stimulus group. For each chemical except quinine HCl, one factor accounts for at least 50% of the variance in the data, and, in all but two cases, more than 74%. The separation between the stimulus groups (absent quinine) is emphasized more by the fact that only 3 of the remaining 42 possible stimulus-factor correlations account for >10% of the variance. Thus each factor accounts for a majority of the variance for one group of chemicals, but usually <10% of it for any other single stimulus. Quinine HCl was an exception on several counts. No single factor accounted for even 30% of the variance in the neural responses. Quinine HCl had a reasonably high loading on a fifth factor (0.841). This factor accounted for very little of the overall variance, but >70% of the variance in the quinine responses.

 
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TABLE 4. Factor loading matrix for 15 sapid stimuli using orthogonal Varimax rotation

Simulation analysis

To test the idea that NaCl-best neurons might carry information about more than one taste quality, we simulated the effects of amiloride on our sample of 44 gustatory neurons. Application of amiloride, a Na+-entry blocker, to gustatory receptors reportedly suppresses responses to sapid Na+, particularly in NaCl-best neurons, without having significant effects on responses to other chemicals (Brand et al. 1985; Formaker and Hill 1988; Giza and Scott 1991; Hettinger and Frank 1990; Ninomiya and Funakoshi 1988). To simulate this effect, we used a technique introduced by Smith and his colleagues (Smith et al. 1983a,b). For all neurons that responded primarily to the Na+, rather than the non-Na+ salts (i.e., 12 neurons in N2-cluster in Fig. 5 that had strong correlations on factor 1 in Table 3), we replaced the response values generated by the Na+ salts with zeros and then recalculated both the multidimensional scaling and the factor analysis. Eliminating Na+ responses from our data in this manner had little effect on the relative positions of the normally preferred stimuli, the acids, or the non-Na+, Cl- salts in the multidimensional space (Fig. 10). Predictably, it did disperse the Na+ salts. MSG was positioned between acids and the normally preferred stimuli; NaNO3 moved closer to the acids; NaCl aligned closely with KCl and MgCl2. Because the responses of the other NaCl-best neurons (those that were activated by all the Cl- salts) were not eliminated from the data matrix, the realignment of NaCl with the non-Na+, Cl- salts might imply that about one-half of the NaCl-best neurons in the PBN were coding for Cl- rather than Na+.


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FIG. 10. Distributions of 15 sapid chemicals in a 3-dimensional space resulting from multidimensional scaling using the data set that simulated the effects of applying amiloride. See Fig. 2 for abbreviations.

When the same altered data were submitted to a factor analysis, similar rearrangements occurred, but the presence of a fourth factor extends the interpretation (Table 5). The loading for MSG on the factor dominated by the normally preferred stimuli did increase modestly (from 0.360 to 0.585), and NaCl increased its weighting on the factor dominated by the non-Na+, Cl- salts (from -0.277 to -0.852). Despite these shifts, however, the Na+ salts still dominated one factor. The loading for NaCl on this factor was less than one-half that when the analysis included the Na+ data (0.904 vs. 0.415), but those for MSG and NaNO3 changed relatively little. Without the neural activity generated by the Na+ in NaCl-best neurons, NaCl probably tastes somewhat similar to non-Na+, Cl- salts. This assertion is supported by the fact that, when treated with amiloride during both acquisition and testing, rats with a learned aversion to NaCl failed to avoid other Na+ salts, but did generalize to non-Na+, Cl- (and acetate) salts (Hill et al. 1990). Nevertheless, in our data, the Na+ salts still dominated one factor (i.e., factor 4) in the analysis implying that, even without the highly specific neural responses to Na+, these stimuli retain some characteristics that distinguish them from the other chemicals in the array.

 
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TABLE 5. Factor loading matrix for 15 sapid stimuli using orthogonal Varimax rotation derived from the data set that simulated results after application of amiloride

    DISCUSSION
Abstract
Introduction
Methods
Results
Discussion
References

This study replicated an earlier one in the parabrachial nuclei that used only 4 stimuli and, by adding 11 more chemicals, it paralleled another that examined taste neurons in the nucleus of the solitary tract (Nakamura and Norgren 1993; Nishijo and Norgren 1990b). These data also were obtained from awake, behaving rat, and they were subjected to the same statistical analyses used in the earlier publications. These methods (best-stimulus categories, cluster analysis, multidimensional scaling, and factor analysis) each have drawbacks, but collectively they provide a basis for comparing data sets from a sensory system in which the physiologically relevant stimulus dimensions are not always apparent. Based on the mean spontaneous rate, the response profiles, the breadth of tuning (entropy), and the order of effectiveness for the four standard stimuli, the present sample of taste cells compared favorably with our previous studies in the PBN of awake rats (Nishijo and Norgren 1990b, 1991). The recording sites overlapped the area from which gustatory responses were recorded when the entire oral cavity was stimulated in anesthetized rats (Norgren and Pfaffmann 1975). For this reason, we feel that this sample of neurons probably reflects a population of cells similar to that examined in earlier experiments. The present analyses suggest five stimulus channels that might be comparable with those suggested by behavioral studies (see INTRODUCTION).

Responses to acids and quinine

The two normally aversive stimuli produced unexpected results. Quinine HCl was remarkable because its behavioral effectiveness was not reflected in the neural responses of either the medulla or the pons. The concentration used in this study (0.0001 M) elicits behavioral responses consistent with rejection of the fluid (Grill and Norgren 1978a,b) but is an order of magnitude lower than that typically used in acute experiments. Indeed, this lower concentration was chosen specifically to avoid vigorous rejection responses that might compromise the recording. Nevertheless, the relative weakness of the quinine might be one reason for its apparent ineffectiveness in driving gustatory neurons in the pons. Prior neurophysiological experiments in this series, however, used a concentration series of four prototypical sapid stimuli: sucrose, NaCl, citric acid, and quinine HCl (Nakamura and Norgren 1991; Nishijo and Norgren 1990b). Concentrations of quinine HCl up to 0.003 M did not appreciably alter the number of neurons that responded to this stimulus. In both the PBN and the NST, quinine was the least effective stimulus, in terms of overall responsiveness of the neural sample and of the number of cells that responded maximally to that chemical. Possible reasons for this disjunction between the behavioral and neurophysiological effectiveness of quinine were covered in an earlier paper when the issue first arose (Nishijo and Norgren 1990b). Briefly, alert animals may adjust their orolingual behavior in such a way as to enhance rewarding tastes and minimize aversive ones.

The lack of response was striking enough that, in the expanded array experiments, we chose not to add more explicitly bitter stimuli. Not surprisingly, the magnitude of responses to quinine remained low in both the NST and PBN neurons that were tested with 15 rather than 4 sapid chemicals. In the PBN, only 7 of 44 cells (16%) responded significantly to quinine HCl. Only one of these was quinine-best, and it was broadly tuned, responding significantly to 11 of the 15 stimuli (2 of the 11 were inhibitory responses; see unit 27, Fig. 4B). In the multidimensional stimulus space, quinine segregates with the three acids in two dimensions, but not in the third. In the factor analysis, this prototypical bitter stimulus has modest loadings on one factor that is otherwise dominated by the acids (0.427) and on another that is dominated by the non-Na+, Cl- salts (-0.517). When a fifth factor is admitted, it accounts for relatively little variance (4.5%) but is dominated by quinine (0.841). This could be interpreted to mean that, even though it missed much of the signal, this sample of neurons can still differentiate quinine from the other stimuli in the array.

In the earlier studies, the responses to citric acid posed two different conundrums. In the NST, acid-best neurons were quite common, but far more specific than those reported for peripheral taste cells or in the NST of anesthetized rats (Nakamura and Norgren 1991). In the PBN, however, acid-best cells were very scarce; only 2 of the 59 units tested (Nishijo and Norgren 1990b). With the expanded array, NST acid-best cells remained both common (17 of 57; 30%) and quite narrowly tuned (Nakamura and Norgren 1993). About one-third of them exhibited some responsiveness to NH4Cl or MgCl2. In the pons, acid-best cells remained less common (5 of 44; 11%) than in the NST and had a somewhat altered response profile. As in the medulla, the responses to the acids were less vigorous than most of the sucrose-best and NaCl-best neurons were to their preferred stimuli. Their responsiveness to the other stimuli in the array was more varied, or at least of greater magnitude, than that of their counterparts in the NST. The three acids were virtually equivalent in effectiveness, and NH4Cl equaled or bested them (Fig. 6). This demonstrated that the relative paucity of acid-best neurons in the PBN did not arise from something idiosyncratic to one organic acid. Most of the other stimuli drove two or three of the acid-best cells, although the responses elicited by the normally preferred chemicals were small. The somewhat broader responsiveness of the acid-best cells did not materially alter the distinctiveness of the acids vis-a-vis the other stimuli in the array, at least as portrayed in the cluster and multidimensional analyses (Figs. 8 and 9). This distinctiveness is consistent with behavioral studies in rodents (Frank and Nowlis 1989; Morrison 1967; Nachman 1963; Nowlis et al. 1980; Yamamoto et al. 1985).

Responses to normally preferred chemicals

The order of effectiveness for the stimuli that are normally preferred by rats was sucrose > glycine > fructose > maltose > Polycose, regardless of whether all 44 taste neurons or only the 15 sucrose-best ones were considered. This ordering is similar to that seen in NST neurons of anesthetized rats when these stimuli (at similar concentrations) were applied to the nasoincisor ducts, and to the multiunit activity from the greater superficial petrosal nerve, which innervates nasoincisor ducts (Nejad 1986; Travers and Norgren 1991). In the NST of the chronic rat, fructose, maltose, and Polycose were more or less equally effective, but sucrose was still the most potent stimulus and glycine second. When the anterior tongue was stimulated in anesthetized rats, however, the order switched for NST neurons to glycine > sucrose > fructose or maltose (Travers and Norgren 1991). In hamsters at least, much of the efficacy of Polycose for stimulating the anterior tongue derives from inorganic cation contaminants (Rehnberg et al. 1996). These results suggest that, in the alert rat, sensory input from the nasoincisor ducts dominates responses to sweeteners in the brain stem taste areas.

The cluster analysis gives the impression that MSG is almost uncorrelated with the normally preferred stimuli and quite similar to the other two Na+ salts (Fig. 8). Nevertheless, for sucrose-best neurons, MSG was as effective a stimulus as fructose and maltose, and more effective than Polycose. That relationship is hinted at in the plot of the multidimensional analysis, because MSG is positioned closer to the normally preferred stimuli than are either of the other Na+ salts. The factor analysis, however, makes the sapid complexity of MSG more explicit (Table 4). Its highest loading is on factor 3, which is dominated by the Na+ salts, but it also has modest positive loadings on factor 1, which is dominated by the normally preferred stimuli, and on factor 4, which is dominated by negative loadings for the non-Na+, Cl- salts and quinine. Similar relationships occur among NST cells, except that the loadings for MSG are almost equal on the factor dominated by Na+ salts and the one representing preferred stimuli (Nakamura and Norgren 1993). Thus, in the brain stem at least, MSG is a reasonably potent stimulus for neurons that respond well to either Na+ or sucrose (for a more complete treatment of the sapid qualities of MSG, see Nishijo et al. 1991).

Responses to salts (Na+ salts vs. non-Na+, Cl- salts)

Although Polycose was somewhat less effective as a stimulus for PBN than for NST taste neurons, on balance, the pons and medulla handled the normally preferred chemicals similarly. The responses to sapid salts, however, were distinctly different at the two levels. In the NST, NaCl-best neurons responded well to any salt with a Na cation, but were largely insensitive to non-Na+, Cl- salts. (Non-Na+, non-Cl- salts were not included in the stimulus array.) In the PBN, about one-half of the NaCl-best cells had similar response profiles, i.e., they responded nearly equivalently to MSG, NaNO3, and NaCl. The remaining NaCl-best units failed to respond to the other Na+ salts but were activated by the three, non-Na+, Cl- salts. This differential sensitivity is reflected in the cluster analysis of neurons (Fig. 5) that displays two groups of NaCl-best cells, one modestly correlated with the cluster containing sucrose-best neurons, the other exhibiting no correlation with the acid-best cells and a slightly negative correlation with the sucrose-best and the other NaCl-best units. A similar analysis of the comparable sample of NST taste neurons produced only one ordering of NaCl-best cells (Nakamura and Norgren 1993) (Fig. 6). The fact that this separation occurred in third-order taste cells of the PBN, but was not apparent in second-order NST neurons, argues against a strictly peripheral coding of the difference.

Both in the chorda tympani and glossopharyngeal nerves of rats and hamsters, two types of Na+-sensitive cells are reported: those that respond almost exclusively to the Na+ and those that respond nearly as well or even better to acids (Boudreau et al. 1983; Frank 1973, 1991; Frank et al. 1988). The latter variety often respond to other Cl- salts as well. Boudreau et al. (1987) reported a few salt-responsive units in the rat petrosal ganglion that responded broadly to Cl- salts. When only the anterior tongue is stimulated in anesthetized rodents, gustatory neurons in both the medulla and pons also exhibit these two types of response profiles to Na+ (see Travers et al. 1987). In the awake, behaving animal, the so-called Na+-specific cells remain evident in both the NST and the PBN. The other Na+-responsive neurons, however, change their response profiles at both levels. In the medulla, acid-best units seldom respond to Na+, and NaCl-best cells respond little if any to acids or to non-Na+, Cl- salts (Nakamura and Norgren 1993). In the pons, acid-best neurons are rarer, but, except for NH4Cl, they remain quite specific. At this level, about one-half the NaCl-best cells do respond to the non-Na+, Cl- salts, but they are insensitive to either acids or non-Cl-, Na+ salts.

Behavioral studies in rodents also indicate that Na+ salts (NaCl, NaNO3) are distinct from non-Na+ salts (MgCl2, NH4Cl, KCl). In conditioned taste aversion tests, NaCl and NaNO3 generalized to each other, as did MgCl2, NH4Cl, and KCl. There was virtually no generalization between the Na+ and the non-Na+, Cl- salts (Frank and Nowlis 1989; Nachman 1963; Yamamoto et al. 1985). Some of this distinctiveness appears to rely on axons in the chorda tympani nerve, because when it was severed bilaterally, rats that have been trained to discriminate one chemical from the other failed to maintain their performance (Spector and Grill 1992). A corresponding transection of the glossopharyngeal nerves, which innervate four times more taste buds than the chorda tympani, had no effect on the same discrimination task. A pharmacological version of this distinction can be demonstrated when the Na+ channels of the taste buds are blocked with amiloride. Under these circumstances, NaCl generalized to both KCl and NH4Cl in a taste aversion paradigm, suggesting that the residual gustatory sensation is dependent on the Cl- anion, either directly or via a Cl--dependent cation current (Formaker and Hill 1988; Hill et al. 1990). Similarly, treatment with amiloride degraded performance in an NaCl versus KCl discrimination task (Spector et al. 1996). These results are consistent with the simulation performed with the current data, and, taken with others, they reinforce the idea that salt taste results from the activation of specific peripheral receptors and that this distinctiveness is maintained in the CNS by neurons that preferentially respond to those receptors (Scott and Giza 1990).

This resorting of response properties across synaptic levels is not readily explicable, particularly because some other response profiles remain quite consistent. Several possible contributing factors (sampling bias, anesthetics, stimulus concentration) have been examined in an earlier paper in this series (Nishijo and Norgren 1990b). Regardless of the reason, two trends are apparent. First, taste neurons respond more selectively in awake, behaving animals than in anesthetized preparations. Second, they also are more selective in the PBN than on the periphery. The first trend can be documented with the breadth of response measure, but not so for the second (Nakamura and Norgren 1991). In fact, in behaving rats, the average breadth of tuning remains virtually unchanged (at 0.55-0.60) from the NST through the cortex. The breadth of tuning measure, however, uses data from only four prototypical taste stimuli, and these categories may be differentiable at brain stem levels. When more stimuli are added to the array, other response categories become possible both at the neural and the behavioral level. Based on the conditioned taste aversion data, rats tend to categorize non-Na+, Cl- salts differently from both acids and Na+ salts. That distinction may not be obvious in the neural response patterns of the peripheral gustatory nerves and the NST, but the information must be available. In the NST, none of the neurons responded distinctively to the non-Na+, Cl- salts but, when the data were analyzed for stimulus similarity, these chemicals were grouped together (Nakamura and Norgren 1993). In addition, in the pontine parabrachial nuclei, the next synapse in the central gustatory system, a subset of neurons manages to extract that information into a distinctive response profile.

Taste quality coding in the PBN

Based on a factor analysis of the responses to these 15 stimuli, we inferred that parabrachial gustatory neurons may distinguish as many as 5 categories of sapid chemicals, perhaps better than their peripheral counterparts. Subsets of neurons in the sample responded to a single class of chemicals and, based on behavioral tests, those chemicals are related as much by taste quality as by composition. Some subsets were well represented; cells that responded primarily to the Na+ cation (unit 19), the Cl- anion (unit 39), or the H+ cation (unit 42) for instance. The subset of neurons that responded to the normally preferred chemicals was as large as the others but included a hint that further subdivisions might exist. Most of the sucrose-best cells (12/15) responded more or less to all the stimuli in this behaviorally defined category and had their heaviest loading on factor 2. Two cells, however, responded better to stimuli that consisted only of glucose moieties, i.e., glucose, maltose, and Polycose, than to the other chemicals in this category. These two cells had only a modest loading on factor 2, but strong representation on factor 5. Given the behavioral evidence that the polysaccharides of glucose are distinct from the other preferred stimuli, it is tempting to view such neurons as evidence that this distinction is either extracted or preserved at the level of the parabrachial nuclei. Another response characteristic was uncommon, even unique, but represents such a prominent taste quality (bitter) that it cannot be ignored. Indeed, as discussed previously, the paucity of bitter responses in the central gustatory system must be explained before any account of quality coding can be considered remotely adequate (Halsell et al. 1993; Nishijo and Norgren 1990b).

Regardless of the number of category distinctions achieved by parabrachial taste neurons, the second central gustatory nuclei transform, as well as relay, the information received from the first level in the NST. In the NST, neurons tested with this extended array of stimuli remain amenable to a rough characterization based on their largest response to one of the four prototypical sapid chemicals: sucrose, NaCl, citric acid, or quinine HCl (Nakamura and Norgren 1991). In the PBN, taste cells that respond equivalently to NaCl clearly distinguish between Na+ salts and non-Na+, Cl- salts. In addition, cells that respond best to sucrose may distinguish between at least two categories of normally preferred stimuli. In other words, the simple categorization scheme that works well on the periphery and in the NST appears to be misleading at the next level of processing.

The perspective provided by the factor analysis, buoyed with behavioral evidence from generalization studies with animals (see above), lends credence to considering brain stem gustatory neurons as category analyzers. At this level of function, no larger capacity may be necessary (Travers et al. 1987). Nevertheless, both humans and animals are capable of intracategory distinctions, and thus this information must be carried in the gustatory neural traffic. Two mechanisms have been proposed to accomplish these ever finer distinctions. The first is a variant of the across-fiber pattern theory in which category distinctions are based on the activity of specific subpopulations of neurons, but intracategory discrimination relies on the variable responsiveness of other neurons to stimuli within that category (Smith et al. 1983b). The second approach, which by no means mutually excludes the first, assumes a hierarchical organization in which gustatory neurons become capable of ever finer discrimination as they ascend the neuraxis. Not surprisingly, support for this position arises primarily from studies of cortical gustatory neurons (Baylis and Rolls 1991; Kosar and Schwartz 1990; Yamamoto et al. 1987, 1989). The present data provide incidental support for this latter position, but probably more through analytic emphasis than empiric mandate. In awake, behaving animals, PBN taste neurons are more narrowly tuned than are peripheral axons (in anesthetized preparations), but the response patterns still contain more than sufficient variance to accommodate intracategory distinctions based on activity across a broad population of cells.

    ACKNOWLEDGEMENTS

  The authors thank M. J. Bartholomew, Dr. M. B. Jones, and Dr. T. Uwano for assistance with the statistical analyses, K. Smith for histology and animal care, and Dr. Patricia Sue Grigson for comments on an earlier draft of the manuscript.

  This research was supported by National Institute of Deafness and Other Communications Disorders Grant DC-00240. R. Norgren is a recipient of National Institute of Mental Health Research Scientist Award MH-00653.

    FOOTNOTES

  Address for reprint requests: R. Norgren, Dept. of Behavioral Science, College of Medicine, The Pennsylvania State University, Hershey, PA 17033.

  Received 18 February 1997; accepted in final form 3 July 1997.

    REFERENCES
Abstract
Introduction
Methods
Results
Discussion
References

0022-3077/97 $5.00 Copyright ©1997 The American Physiological Society