Chem. Senses 28: 131-140,
2003
© Oxford University Press 2003
RESEARCH PAPERS |
Responsiveness of the Cortical Taste Area Neurons to a Mixture of the Four Basic Tastants in Rats
Department of Physiology, Kumamoto University School of Medicine, Kumamoto 860–0811, Japan
Correspondence to be sent to: K. Hasegawa, Department of Physiology, Kumamoto University School of Medicine, Honjo 2-2-1, Kumamoto 860-0811, Japan. e-mail: kayoko{at}kaiju.medic.kumamoto-u.ac.jp
Abstract
The taste coding mechanism in the cortical taste area was investigated by analyzing the responses of 59 neurons in the cortical taste area of the anesthetized rat to a mixture of the four basic tastants in both absence and presence of bicuculline methiodide, a specific antagonist to the GABAA receptors. The mixture caused response suppression more frequently than response facilitation, both in the control state and during bicuculline application. Cluster analysis revealed that only a group of the neurons with the best response to both NaCl and HCl (group NH) showed the best response to the mixture in the control state, whereas during bicuculline application, in addition to group NH, two other groups of neurons responding to sucrose, or to HCl and quinine responded vigorously to the mixture. Multidimensional scaling located the mixture outside the space of the four basic tastants facing an NaCl–HCl line in both states. GABAergic inhibition caused the group NH to represent the taste of the mixture in the control state. Thus, the mixture probably tastes salty and sour to rats. No cortical neuron was found which specifically responded to the mixture.
Key words: cortex, GABA, rat, taste interaction, taste mixture
Introduction
Animals, including humans, interact with the world through perception of
various sensory stimuli. Investigation of the central nervous system (CNS)
involved in such perception sometimes requires the use of the same stimuli as
encountered under natural conditions. In particular, a study of the central
gustatory system essentially requires investigation of the responsiveness of
neurons to mixtures of various taste substances, since foods are often
composed of multiple chemicals that individually elicit different tastes and
the gustatory system is adaptively evolved to detect such complex taste
mixtures. However, most behavioral, psychophysical and physiological
experiments on taste so far undertaken have preferred the use of simple,
single chemicals as taste stimuli to complex mixtures and have not attempted
to study the neural mechanism for complex taste mixtures. Only occasionally,
investigators have examined the interactions between the basic tastants that
underlie the gustatory perception of foods. Psychophysical studies of the
mixtures of basic taste stimuli (Kroeze,
1989
) have disclosed various phenomena, such as mixture
suppression or facilitation. Mixture suppression is more frequently observed
than mixture facilitation.
Previous studies of binary taste mixtures in animals have confirmed that
mixture suppression and facilitation occur in a wide range of gustatory
systems from the peripheral to the central neurons
(Frank, 1989;
Vogt and Smith, 1993;
Miyaoka and Pritchard, 1996).
The fraction of neurons involved in mixture suppression increased from the
nucleus of the solitary tract (NTS) to the thalamic taste relay nucleus, or
the parvicellular part of the thalamic posteromedial ventral nucleus (VPMpc)
(Hasegawa et al.,
2002). Investigation of the coding mechanism of taste mixture in
the cortical taste area (CTA) would be very helpful in understanding the
neural mechanism of the information processing of complex tastes, because the
CTA is the site of final decoding of taste information and probably includes
mechanisms for detecting taste stimuli. The neural responses to binary,
trinary and quadruple mixtures have been reported in the cortex of primates
(Miyaoka and Pritchard, 1996;
Plata-Salaman et al.,
1996), but rarely in rodents except for a mixture of umami
substances (Ogawa et al.,
1997).
The present study investigated the taste coding mechanism in the CTA of the
rat by recording the responses of CTA neurons to the four basic tastants and
the mixture of all these four tastants and by analyzing the responses using
multivariate analyses to clarify what sort of neuron groups represent the
mixture taste in the CTA. The GABAergic inhibitory system contributes to
modification or selection of taste information in the cortex
(Ogawa et al., 1998).
Therefore, the contribution of GABAergic inhibition to the coding of the
mixture in the CTA was also assessed by iontophoretic application of
bicuculline methiodide (BMI), a specific antagonist to the GABAA
receptors.
Materials and methods
Animals and surgery
Adult female Sprague–Dawley rats were used. The animals were
anesthetized with urethane (1 g/kg body wt, i.p.). After cannulation of the
trachea and femoral vein, the animal's head was mounted on a standard
stereotaxic frame with a pair of ear bars. The left cheek from the mouth
corner to the ramus of the mandible was resected and the frame was rotated
45° with the left side up. The rat was immobilized with
D-tubocurarine (1.5 mg, i.v.) and artificially ventilated. The end-tidal
CO2 was maintained at 3.5–4.5%. Whenever the effect of
D-tubocurarine seemed to be wearing off, the level of anesthesia was checked
at the corneal reflex and urethane (100 mg/kg) was given if necessary. Body
temperature was kept at 37°C with a water heater. The bone covering the
left middle cerebral artery was removed and a small opening was made on the
dura over the granular and/or dysgranular insular cortices—areas GI or
DI (Ogawa et al.,
1992). The mouth was opened to 30–40° and the
tongue stretched out anteroventrally. Cut wounds were infiltrated with 1%
xylocaine.
Stimulation and recording
The taste stimuli used were the four basic tastants (0.1 M NaCl, 0.5 M
sucrose, 0.01 N HCl, 0.02 M quinine–HCl) and a mixture solution
containing all of the four basic tastants at the above-mentioned
concentrations. Taste stimulation was controlled by a 16-bit microcomputer:
distilled water was delivered in a prestimulus period of 15 s, followed by a
taste stimulus for 10 s and then by the water for 15 s as a rinse. Taste
responses were identified when, during the 10 s of taste stimulation, there
was a change in the discharge rate by 2 SD above or below the average
prestimulus discharge rate that lasted for at least 1 s
(Ogawa et al., 1984).
The magnitude of the response was calculated as the number of impulses in the
first 5 s following the onset of stimulation minus the number of background
impulses in a corresponding prestimulus period. Average net responses of 
5
impulses/5 s were assumed to indicate significant responses and such responses
were used for statistical analysis. The response to the mixture was always
compared with the most effective component of the mixture (MEC), the stimulus
which, of the four component tastants, evoked the largest response in the
neuron under study.
Spikes from the soma of single neurons were recorded with a glass
microelectrode (tip diameter <1 µm) filled with 2% pontamine sky blue in
0.5 M sodium acetate as described previously
(Ogawa et al., 1992).
The recording microelectrode was glued to the side of a seven-barreled
micropipette used for drug application and protruded by 15–30 µm from
the end of the micropipette (the overall tip diameter of the micropipette was
5–10 µm).
BMI application
In several CTA neurons, GABAergic inhibition was blocked by BMI (5 mM, pH
3.2) applied from one of the barrels. Taste responses were recorded in the
absence (control state) or presence (BMI state) of BMI. BMI was
electro-phoretically ejected with 3–10 nA current onto neurons for
30–40 min when three to five series of responses to the four basic
tastants and the mixture of those tastants were obtained. After the recordings
of the series of responses, the ejection of BMI was discontinued and CTA
neurons were allowed to recover. A significant change in the magnitude of
taste responses in the BMI state was a mean increase or decrease by 30% in the
responses of the neurons compared to those in the control state and a change
by not less than eight impulses in the first 5 s following the onset of
stimulation (Ogawa et al.,
1998). Retaining currents of from –10 to –5 nA were
used to prevent BMI from leaking during the control state.
Data analysis
Data analysis was performed with a microcomputer. The responses of 59 taste
neurons to the four basic tastants and the mixture were arranged into a matrix
of 59 neurons x five stimuli and analyzed with two multivariate
statistical methods using SPSS software (SPSS Inc., MI), hierarchical cluster
analysis (Bieber and Smith,
1986) and multidimensional scaling (MDS)
(Schiffman et al.,
1981). The former analysis used the Pearson product-moment
correlation coefficients (corr. coefs) calculated for each pair of taste
response profiles for all 59 neurons. Hierarchical cluster analysis was used
to determine the relative similarity between the neurons, or between the
neuron clusters based on responses to the four basic taste stimuli. Cluster
amalgamation used the simple average linkage method and the results were
plotted as a dendrogram. To determine the number of clusters, each containing
functionally similar neurons, a scree test was used
(Bieber and Smith, 1986).
Cluster similarity was plotted against the number of clusters obtained during
amalgamation process. The point (elbow) where a sudden decrease in similarity
occurs when the amalgamation process proceeds, indicates the number of cluster
to extract. MDS was applied to a set of data in both the control and BMI
states to measure the multidimensional distance between taste stimuli in both
states. Taste stimuli were mapped in a taste space to reveal the spatial
organization.
Histology
Recording sites were histologically identified by extracellular dye marks
produced by negative currents of 10 µA passed for 5 min through a recording
electrode containing the dye. The marks were made at two or three recording
sites along a single electrode track to reconstruct the track. At the
termination of the experiments, the animals were deeply anesthetized with
urethane and perfused through the heart with 10% formalin in a 0.1 M phosphate
buffer. Blocks of the tissue containing the recording sites were frozen, cut
into 50 µm thick sections and stained with thionine. Cytoarchitectonic
identification of the areas GI and DI forming the CTA was made as reported
previously (Ogawa et al.,
1992).
Results
A total of 80 taste neurons were studied in the CTA in the control state. Of these, 59 neurons were successfully studied in the BMI state. Since the sample size was small, we collectively analyzed neurons in both areas GI (n = 33) and DI (n = 26) together.
Response of neurons to the tastants and mixture
Responses of the neurons
Most neurons (62.7%) responded to two or more of the four basic tastants.
Many neurons (55.9% of the 59 neurons) responded to the mixture. Neurons
discharged 11.1 ± 13.5 impulses/5 s in response to NaCl, 6.6 ±
8.8 to sucrose, 9.4 ± 14.9 to HCl, 6.2 ± 10.8 to quinine and
13.4 ± 20.0 to the mixture. Figure
1A shows the representative response of a single neuron to the
four tastants and the mixture. The neuron in the figure yielded a tonic
response to NaCl and phasic responses to HCl and quinine. The response to the
mixture was tonic with the phasic component, the magnitude of which was rather
comparable to that for HCl. The MEC was NaCl in this neuron and the response
to the mixture was smaller than that to the MEC. In the BMI state the
responses to the three tastants and the mixture were enhanced and the response
to sucrose emerged (Figure 1B).
The response to the mixture was slightly increased, but did not exceed that to
the MEC, as in the control state.
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BMI significantly affected 44 of the 59 neurons. The responses to both the tastants and the mixture were affected in 26 neurons. Only the responses to some of the tastants, but not to the mixture, were affected in 14 neurons. Only the responses to the mixture were affected in four neurons. Mean magnitudes of the responses in the BMI state relative to those in the control state were 182.1% for NaCl, 190.3% for sucrose, 164.1% for HCl, 201.6% for quinine and 183.5% for the mixture.
Response profiles
The taste response profiles of the neurons to the four tastants and the
mixture are illustrated in Figure
2A. The neurons were categorized according to the MEC. In each
category, neurons are arranged from the left to right according to the
response to the MEC in decreasing order. In both the NaCl-best and HCl-best
categories, mixture responses tended to decrease from the left to right in a
manner in which the responses to the MEC in the corresponding category
decreased. Mean response to the mixture was 104% of the mean MEC response in
the NaCl-best neurons (n = 23) and 67% of the mean MEC response in
the HCl-best neurons (n = 15). No significant differences were noted
between the mean responses to the mixture and to the MEC in both categories
(P > 0.05, Student's t-test). However, the sucrose-best
(n = 16) or quinine-best (n = 5) neurons showed smaller
responses to the mixture than to the MEC. Mean response to the mixture was 37%
of the mean MEC response in the sucrose-best neurons and 41% in the
quinine-best neurons, and was significantly smaller than the mean MEC response
in the these two categories of neurons (P < 0.005 and P
< 0.05, respectively, Student's t-test).
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The taste response profiles of the neurons in the BMI state are illustrated in Figure 2B. The neurons are also categorized according to the MEC. In all categories, mixture responses tended to decrease from left to right in a manner in which the responses to the MEC in the corresponding category decreased. Most of the NaCl-best (n = 26) or HCl-best (n = 14) neurons showed similar magnitudes of responses to both the mixture and the MEC. Mean responses to the mixture were 85 and 77% of the mean response to the MEC, respectively, in these categories, although no difference was noted between the mean response to the mixture and the MEC in both categories (P > 0.05, Student's t-test), as seen in the control state. In contrast, the sucrose-best neurons (n = 11) showed different response profiles from those in the control state. Namely, the response to the mixture did not differ from that of the MEC. This was also the case in the quinine-best neurons. (P > 0.05, Student's t-test).
The number of neurons responding to the mixture in the total population increased from 33/59 (55.9%) in the control state to 46/59 (78.0%) in the BMI state.
Mixture suppression and facilitation
The mixture might cause a response as large as the sum of the responses to
the four tastants, if the tastants in the mixture do not interact in a
transduction at either receptor or neuronal level. In previous studies
(Vogt and Smith, 1993), the
responses to binary mixtures have been compared to the response to each
component in the mixture, especially the MEC. We also compared the response to
the mixture with that to the MEC, as well as with the sum of the responses to
the four tastants.
Figure 3A illustrates the analysis of the neural responses in the control state, in which the across-neuron patterns (ANPs) of the responses to the mixture and the MEC are compared (Figure 3A-a) and those to the mixture are also compared with the sum of the responses to the four tastants (Figure 3A-b). The response to the mixture was greater by at least 5 impulses/5 s than the response to the MEC in only 12 of 59 neurons and greater than the sum of the responses to the four tastants in five neurons (Table 1). The response to the mixture was smaller than the response to the MEC in 33 neurons and smaller than the sum of the responses to the four tastants in 50 neurons. Response to the mixture greater or smaller than the sum of the responses to the four tastants indicates mixture facilitation or suppression, respectively.
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Figure 3B shows the analysis of the neural responses in the BMI state, as in the control state. The response to the mixture was greater than the response to the MEC in seven neurons and greater than the sum of the responses to the four tastants in two neurons (Table 1). The response to the mixture was smaller than the response to the MEC in 25 neurons and smaller than the sum of the responses to the four tastants in 52 neurons. The response to the mixture was similar to the response to the MEC in 27 neurons, almost double the number (14) in the control state. BMI increased the difference between the response to the mixture and the sum of the responses to the four tastants (Figure 3B-b).
Correlation of the taste mixture with four tastants
The relationships of responses to the mixture and those to the four tastants were analyzed using Pearson product-moment corr. coefs between the responses to the mixture and those to the four tastants (Figure 4A). This analysis quantitatively evaluated the similarities of the ANPs to the mixture and the four tastants. The responses to the mixture correlated significantly with those to NaCl, HCl, or quinine (corr. coef. = 0.849, 0.625 and 0.680, respectively; P < 0.0001, Student's t-test), but not correlated with sucrose (corr. coef. = 0.217; P > 0.05, Student's t-test). The corr. coef. was also calculated between the responses to the mixture and those to the MEC, and between the responses to the mixture and the sum of the responses to the four tastants. The response to the mixture was significantly correlated with the response to the MEC and the sum of the responses to the four tastants (corr. coef. = 0.804 and 0.835, respectively; P < 0.0001, Student's t-test).
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In the BMI state, the responses to the mixture correlated significantly with the responses to NaCl, HCl and quinine (corr. coef. = 0.809, 0.739 and 0.703, respectively; P < 0.0001, Student's t-test; Figure 4B), as seen in the control state. The responses to sucrose became significantly correlated with those to the mixture (corr. coef. = 0.361; P < 0.005, Student's t-test), although the coefficient was small. The response to the mixture was significantly correlated with the response to the MEC and the sum of the responses to the four tastants (corr. coef. = 0.901 and 0.846, respectively; P < 0.0001, Student's t-test).
Multivariate statistical analysis
Cluster analysis
Cluster analysis of the similarity between neurons was performed to
identify which group of neurons carries the response to the mixture. Since the
scree test indicated an elbow at the number of clusters = 5, five groups were
identified in the dendrogram (Figure
5A-a): groups of neurons with the best responses to HCl (i.e. MEC:
HCl, group H), to quinine (i.e. MEC: quinine, group Q), to NaCl–quinine
(i.e. MEC: NaCl and quinine, group NQ), to NaCl–HCl (i.e. MEC: NaCl and
HCl, group NH) and to sucrose (i.e. MEC: sucrose, group S). Group NH contained
almost all neurons yielding the largest responses to the mixture, as marked
with stars at the left column in Figure
5A-a (see mean response profiles in
Figure 5A-b). This indicates
that group NH carries the information of the mixture.
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In the BMI state, the scree test identified seven groups of neurons categorized according to the best stimuli among the four basic tastants: i.e. groups NH, N, Q, S, HQ-1, HQ-2 and H in the dendrogram (Figure 5B-a). Groups NH and HQ-1 contained neurons most strongly responding to the mixture, marked with stars at the right column in Figure 5B-a (see the mean response profiles in Figure 5B-b). A fraction of group S also contained neurons most strongly responding to the mixture. This indicates that both groups NH and HQ-1 together with a fraction of group S carry the information of the mixture in the BMI state.
MDS analysis
Distances between the four tastants and the mixture were assessed by the
MDS method. Figure 6 shows the
twodimensional map of the taste stimuli in the control and BMI states. In both
states, the mixture was located outside the area defined by the four basic
stimuli facing a line connecting NaCl and HCl, and sitting closer to NaCl. The
spatial relationship of the relative positions of the mixture and four
tastants did not change in the BMI state, but the distances among the five
tastants increased.
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Discussion
Mechanisms of mixture suppression and facilitation
The phenomenon of mixture suppression has been primarily identified for
heterogeneous mixtures of tastants in psychophysical studies
(Pangborn, 1960). The
interactions of heterogeneous tastants may involve central or both peripheral
and central mechanisms (Kroeze,
1989). Neurophysiological studies in rodents have shown that
mixture suppression (20–50%) is more frequently observed than mixture
facilitation (5–15%) for binary mixtures from the peripheral to the CNS
(Frank, 1989;
Vogt and Smith, 1993;
Miyaoka and Pritchard, 1996).
In the present study, mixture suppression was observed in many neurons in the
CTA. The fraction of mixture suppression for the quadruple mixture (84.8%) was
much larger than that for the binary mixture (20–50%)
(Frank, 1989;
Vogt and Smith, 1993;
Miyaoka and Pritchard,
1996).
Previously, we studied responses of neurons in NTS and VPMpc to the mixture
of the four basic tastes (Hasegawa et
al., 2002). The fraction of mixture suppression in the CTA
was significantly larger than that in the NTS (63.4%; P < 0.025,
2 test), but did not differ from that in the VPMpc (77.5%;
P > 0.05, 2 test). The finding suggests that
additional mixture suppression is not generated by a synaptic transfer from
the VPMpc to the CTA, but might be generated somewhere in the gustatory
pathway from the NTS to the VPMpc.
Human psychophysical studies indicate that enhancement of the intensity of
one taste quality in a tastant by the addition of another tastant usually
occurs only when the added tastant is of weak stimulation
(Kroeze, 1989) and homogeneous
in quality (Pangborn, 1962).
Mixture facilitation is found occasionally for a heterogeneous taste solution,
particularly when the tastes of two components in the solution overlap in
quality (Bartoshuk, 1975). In
the present study, mixture facilitation was observed in a small fraction of
taste neurons (8.5%), probably because individual taste qualities of the
components in the mixture do not overlap. Mixture facilitation occurs also in
the chorda tympani fibers (15%) (Hyman and
Frank, 1980), NTS (14.5%)
(Hasegawa et al.,
2002) and VPMpc (10.0%)
(Hasegawa et al.,
2002). There was no significant difference in these fractions of
mixture facilitation (P > 0.1, 2 test).
Taste quality of mixture
The cluster analysis in the present study identified five separate groups
of taste neurons in the CTA, but only the group NH contained neurons strongly
responding to the mixture. The NTS, parabrachial nucleus (PBN) and VPMpc
contain three to four groups of neurons responding to one of the four basic
tastants and each group contains neurons with a high sensitivity to the
mixture (Hasegawa et al.,
2002). The findings indicate that mixture information may be
carried in the lower CNS by multiple groups of neurons, each sensitive to one
of the four tastants, but in the CTA only by a single group of neurons, i.e.
group NH. Therefore, the mixture may be represented as a taste similar to that
of NaCl and HCl in the CTA.
Behavioral responses of animals to binary mixtures should be consistent
with the neural recordings in the CTA if neural responses are adequately
analyzed. Hamsters usually generalize an aversion conditioned to a binary
mixture to both components of stimuli when tested individually, except for the
mixture of NaCl and quinine (Nowlis and
Frank, 1977). The animals strongly generalize an aversion
conditioned to the latter mixture to NaCl, but not to quinine at all. The
neural mechanism underlying this phenomenon was suggested when responses of
best-stimulus categories of PBN neurons in hamsters were analyzed
(Travers and Smith, 1984): the
mean response of the NaCl-best neurons to a mixture of NaCl and quinine was
comparable to that for NaCl alone, but the mean response of the quinine-best
neurons to the mixture was only 75% as large as that to quinine alone. A
similar mechanism may be present in the brainstem or cortical gustatory
neurons of the rat, as well. On top of that, the present study clarified the
role of the GABAergic inhibition in the CTA that selects a certain group of
neurons to represent the mixture.
The MDS analysis located the mixture outside the taste space defined by the four basic stimuli, though facing a line connecting NaCl and HCl. This indicates that the mixture is represented in the CTA as a taste different from each taste component of the mixture, which is not compatible with both behavioral and physiological experiments on taste. Therefore, the mixture information is not coded by a large number of neuron groups, but by a certain group of neurons.
GABAergic inhibition in the coding of taste mixture
Most CTA neurons contain GABAA receptors and the GABAergic
inhibitory system apparently contributes to modifying or selecting taste
information in the CTA (Ogawa et
al., 1998). Therefore, GABAergic inhibition is likely to
contribute to the coding of taste mixtures. The suppression of GABAergic
inhibition caused responses to the mixture in neurons in group HQ-1 and a
fraction of group S, in addition to those in group NH that responded to the
mixture in the control state (Figure
5B). Results in the BMI state are quite similar to those found in
the NTS, PBN and VPMpc (Hasegawa et
al., 2002). Therefore, because of GABAergic inhibitory action
which suppresses several groups of neurons otherwise responsive to the
mixture, only group NH neurons seem to represent the taste mixture in the CTA
in the control state. Presumably, the group NH neurons suppressed the
activities of the other groups of neurons through GABAergic interneurons in
the CTA.
Two different multivariate analyses (cluster analysis and MDS) used in the present study showed different findings concerning the effects of GABAergic inhibition on coding of the taste mixture. The cluster analysis showed that GABAergic inhibition increased discrimination of tastants by filtering out a single group of cortical neurons responding to the mixture. On the other hand, however, MDS showed that GABAergic inhibition decreased distances, i.e. caused hard discriminations, between tastants in a twodimensional taste space. The present findings indicate that cluster analysis is more suitable for data analysis of CTA neurons than MDS.
Tastant detection and mixture as a taste stimulus
Taste stimuli are received at the taste receptor cells in the oral tissue,
coded into a series of nerve impulses in the peripheral taste fibers, such as
the chorda tympani fibers and transmitted to the NTS and then to the PBN. The
afferents from the NTS to the PBN converge without receiving much inhibitory
action, so the response magnitude for taste stimuli reaches the maximum in the
PBN (Ogawa et al.,
1984). Receptive fields are enlarged in the VPMpc and CTA,
probably because of the afferent convergence from the bilateral PBN in the
thalamus (Nomura and Ogawa,
1985; Ogawa and Nomura,
1988; Ogawa et al.,
1992) or callosal afferents from the other hemisphere in the
cortex (Kadohisa et al.,
2000). However, various forms of neural modification, e.g.
descending inhibition from the cortex
(Ogawa and Nomura, 1988) or
intracortical inhibition (Ogawa et
al., 1998), probably decrease the response magnitude to the
basic tastants in the VPMpc and thus in the CTA. The decreased response
magnitude together with the enlarged receptive fields, a manifestation of
neural integration, suggests changes in the adequate stimuli from basic
stimuli to complex stimuli as seen in other sensory cortices, e.g. the
somatosensory (Iwamura et al.,
1985), visual (Gross et
al., 1972) and auditory cortices
(Maruyama et al.,
1979). Thus, it is assumed that neurons in the CTA and probably
also in the VPMpc could be tuned to some natural food consisting of several
taste qualities, but not to simple basic stimuli.
The mixture evoked significant responses (see Materials and methods) in
90% of the taste neurons in the NTS, the PBN and the VPMpc
(Hasegawa et al.,
2002), but in only 56% of the CTA neurons in the present study.
Changes in the adequate stimulus to excite most neurons are observed along the
ascending pathway in other sensory systems. For example, in the visual system
in cats, a concentric circle of light is an adequate stimulus for the retina
ganglion cells, whereas a slit of light with adequate slant is needed for
neurons in the primary visual cortex. Light covering most of the visual field
of the cat evokes little or no response in the retina ganglion cells to the
visual cortex neurons (Kuffler and
Nicholls, 1977).
In the present study, group NH neurons carried the information of the mixture, but only a few neurons produced greater responses to the mixture than to the sum of the responses to the four tastants, and the magnitude of the response of all cortical neurons to the mixture was small. Therefore, no neuron was specially tuned to the present mixture, although the CTA probably has mechanisms for detecting mixtures of several basic tastants as found in natural products. It is possible that the present species of the taste mixture was not suitable to activate neurons involved in such a mechanism. Further studies are necessary to search for such complex taste stimuli that specifically activate the mechanism for detecting the taste mixture in the CTA.
Acknowledgments
The study was partly supported by a grant-in-aid for priority areas on Higher-order Brain Functions, from the Ministry of Education, Science and Culture, Japan.
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Accepted December 2, 2002
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