Two subtypes of taste-specific responses in BLA
, a representative photomicrograph, reveals the electrode cannula track and location of one set of electrode tips situated in BLA (Paxinos and Watson, 1997
); overlain on this image are the locations of the other bundle tips. A total of 96 BLA neurons were collected from chronically indwelling electrode bundles in 7 rats (22 sessions in all; 4.4±2.1 neurons/session). Of these, 75 were held across multiple (> 7) applications of the full array of 4 tastes, and of these, 21 (28% of the total sample) responded with taste-specific average firing rates (p < 0.05 for the main effect of taste in a 2-way [taste × time] ANOVA). The interaction terms of the same ANOVAs revealed a further 9 (12% of the total sample) BLA neurons that produced responses with different time-courses to different tastes. Overall, 25 neurons (33% of the total BLA sample) were taste-specific according to rate, time-course, or some combination of the two. This represents a much higher percentage than that previously reported for monkeys (Scott et al., 1993
) and rats (Nishijo et al., 1998
)—a fact attributable to our consideration of time-course, and to the delivery of multiple trials of each taste (which added statistical power to our analysis).
We further examined the time-courses of BLA taste responses, calculating the onset times and durations of firing rate changes (compared to baseline firing) using a moving-window analysis. In the entire sample, 65 significant elevations from baseline were observed in 28 neurons (this number is slightly different than those described above because the moving window analysis compares individual responses to pre-stimulus baselines, whereas the 2-way ANOVA compares responses between taste, and because the moving window analysis is more conservative with regard to detecting inhibitory responses). The vast majority (85.5%) of these modulations had latencies of less than 250 msec (mean, 86.6±12.2 msec), but response durations varied widely, from < 100 msec to well over a second.
When average response latencies and durations were plotted against one another, it became clear that taste-responsive BLA neurons fell naturally into two categories, one of short-latency, long-duration responses, and another of even shorter-latency, short-duration responses (). Cluster analysis confirmed this separation (). For convenience, we refer to these sub-groupings as long- and short-duration (LD and SD) neurons, respectively. The two clusters did not differ in either anatomical localization or waveform shape (data not shown), but they differed significantly along both dimensions of —SD neuron responses were of shorter average duration than those of LD neurons (144±28 vs 1388±71 msec respectively, t(22) = 19.9, p < 0.001), and were also of shorter average latency than LD neurons (61±9 vs 130±25 msec respectively, t(22) = 3.29, p < 0.01).
To simplify further analysis of the neurons that were tested with all 4 tastes, responses were collapsed into 250-msec bins (results were similar using 50-, 100-, or 200-msec bins, however). shows the general time-courses of taste responses in SD (red trace) and LD (green trace) neurons, averaged across taste. During the first 250 msec bin, the two types of neurons responded strongly and similarly, but afterward the responses were quite different—SD responses remained elevated above baseline for only the first 250 msec (t-tests comparing bin 1 to other bins, all p < 0.001), while LD responses declined much more slowly. A 2-way repeated-measures ANOVA of these data revealed that SD and LD responses had significantly different time-courses (interaction F(54,1) = 7.17, p <.001). Post-hoc tests demonstrated that SD and LD firing rates were different from 0.25 to 1.75 sec after taste administration.
LD neurons convey palatability-related information in the middle of three response epochs
In addition to differing in time-course, SD and LD responses also differed in information content. An initial appreciation of this fact can be gained by looking at a simple measure of taste-specificity, the average difference between responses to pairs of tastes (); in this analysis, neurons that respond identically to any pair of tastes (i. e., fire the same number of spikes/sec to all tastes) show a difference of 0 for those two tastes in that time bin.
This analysis revealed the brief SD responses to be taste-specific (although it does not reveal precisely which pairs of tastes contribute to that taste-specificity; that issue will be taken up below), in that the differences between responses to the different stimuli were significantly larger than those observed during pre-stimulus periods (t (59) = 5.01, p < 0.001). In fact, SD neurons responded more taste-distinctively than LD neurons during the first 250 msec bin of the taste responses—during this same period, the LD responses were not taste-specific at all (p > 0.2), despite the fact that their absolute firing rates peaked during this bin (). LD neurons responded in a more taste-specific manner than SD neurons in each of the next 4 bins, however (all p < 0.05), across a period in which the overall response amplitudes steadily declined. LD responses remained significantly taste-specific (p < 0.01) for a relatively long time following taste administration. A 2-way ANOVA (time by neuron type) revealed the difference between the patterns of SD and LD taste-specificity to be significant (interaction F (9,1) = 7.73, p < 0.001).
We predicted that the protracted LD neuron responses would progress through a series of three processing epochs, each containing distinct types of information, in reflection of co-operative coding between BLA and GC. Our analysis supported this prediction. The time-structure of BLA taste responses could be observed by eye (; shading denotes significantly elevated firing): LD neurons responded first to all tastes (we called this period Epoch 1), and then to a subset of tastes (in this case, NaCl and sucrose; Epoch 2); following Epoch 2, LD neurons typically responded to only one taste at any particular time (here, the response was to sucrose at one point and NaCl at another point)—this was called Epoch 3. Population analysis () bore out these trends: LD neurons responded to all 4 tastes during the first 250-msec post-stimulus bin; this generality of response faded quickly however, and vanished completely before 0.5−0.75 sec of post-stimulus time had elapsed. During the period of 0.25 to 1.0 sec post-delivery, LD neurons instead responded to 2−3 tastes (red line). After 1.0 sec post-delivery, they responded to only 1 taste (blue line). In both the number of response epochs and the timing of epoch transitions, LD responses matched well with GC responses (Katz et al., 2001a
LD neurons produce time-varying taste responses with dynamics similar to those of GC
Because the amygdala is known to be a primary processor of taste palatability, we tested the hypothesis that LD neurons—specifically, the 2nd
epoch, in which they responded to either 2 or 3 tastes— provide palatability-related information. The term “palatability” is widely regarded to refer to how likeable and pleasing a taste is (Breslin et al., 1992
; Berridge, 2000
); for this analysis, we made use of the fact that the rat finds sucrose and NaCl pleasing and finds quinine and citric acid aversive, a fact evident in the palatability-specific faces that a rat makes when these tastes are on its tongue (, see also Grill and Norgren, 1978
; Breslin et al., 1992
; Fontanini and Katz, 2006
; Caras et al., 2008
LD neurons carry palatability-related information in the middle portion of their temporal codes
shows which tastes LD neurons responded to in Epoch 2. Most notable is what was absent: not one single neuron responded to both sucrose and quinine, the two extremes of the palatability continuum. In fact, the bulk (60%) of responses in the period between 0.25 and 1.0 sec following taste delivery were restricted to palatability-specific pairs of tastes; the percentage was even higher (86%) when analysis was restricted to bins in which neurons responded to 2 tastes alone. More LD neurons responded to the aversive tastes than to the palatable tastes, a finding that accords well with previous work (Zald et al., 1998
; Oya et al., 2002
NaCl and sucrose behaved similarly in the vast majority (80%) of these cases—both caused responses in 40% of the bins, and both were ineffective in 40% (the exceptions were the NCQ and NQ bins). N behaved like C and Q, meanwhile, in only 30% and 20% of the bins, respectively. Analogously, aversive Q behaved more like aversive C (70% of bins) than it did like either N or S (20% and 0%, respectively).
reveals the general impact that this pattern of responses had on palatability-specificity in LD responses, showing average between-taste differences for tastes with similar palatabilities (sucrose/NaCl, quinine/acid) or distinct palatabilities during each epoch of the responses—the first 250 msec of the response (i. e., the period when most neurons responded to all 4 tastes), the period between 0.25 and 1.0 sec after taste delivery (when most neurons responded to either 2 or 3 tastes), and later time points. For both the 1st and 3rd epochs of the responses, the differences between palatability-specific pairs were similar to those between pairs with distinct palatabilities. During Epoch 2, however, there was significantly less difference between sucrose and NaCl (and between quinine and citric acid) than between other taste pairs (t(96) = 2.69, p < 0.01). While a low but significant (t (22) = 2.07, p < 0.05) level of palatability-specificity could be detected in Epoch 3 in an analysis that collapsed across bins (data not shown), the vast majority of palatability-related LD response information lives in Epoch 2.
These results suggest that it should be harder to tell LD responses induced by NaCl from those induced by sucrose than from those induced by quinine and citric acid. To test this prediction, we built “templates” of the Epoch 2 population responses to each taste, and then used those templates to classify the individual trials. The results of this analysis () shows both how reliably well-defined (i. e., taste-specific) each neural response was, and also reveals which tastes were most often confused for each other. Each taste was correctly identified at approximately twice the rate that one would expect by chance (chance = 25%). Furthermore, for each taste the most common error made by the classifier algorithm was to misidentify the trial as coming from the other taste with the same palatability—32.8% of the trials were within-palatability confusions, while only 9.7% were opposite-palatability confusions. This pattern of confusion confirms that LD responses serve as good predictors of stimulus palatability.
SD neurons reflect rewarding taste properties during surprise deliveries
As already noted (), taste-related information is available in BLA within 60 msec of taste delivery, via
the responses of SD neurons. This response latency is much smaller than that observed in GC, and in fact is unlike that of any taste responses of which we are aware (Katz et al., 2001a
; Fontanini and Katz, 2006
; but see Stapleton et al., 2006
; Grossman et al., 2008
). What these responses do resemble, in their latency and brevity, are reward responses. Neurons within the reward system, including both dopamine neurons in the midbrain and their amygdalar targets, respond to the presentation of rewarding stimuli with phasic bursts of action potentials that strongly resemble those produced by SD neurons in response to tastes (Mirenowicz and Schultz, 1996
; Pratt and Mizumori, 1998
; Schultz, 2001
; Paton et al., 2006
; Roesch et al., 2007
; Tye and Janak, 2007
One reasonable hypothesis as to the nature of SD neurons is therefore related to BLA's known involvement in reward—in determining what stimuli an animal will work to receive or avoid. Midbrain dopamine neurons typically respond more vigorously to appetitive stimuli than to punishing stimuli (Mirenowicz and Schultz, 1996
; Pan et al., 2005
; Roesch et al., 2007
), and BLA contains both neurons that respond to positive rewards and those that respond to punishment (Schoenbaum et al., 1999
; Paton et al., 2006
; Belova et al., 2007
); furthermore, a subset of neurons in both locations have been shown to respond to rewards of either valence (sometimes called “non-valenced” neurons, see in Belova et al., 2007
). So it was in the majority of our SD neuron sample: 4 out of 10 SD neurons responded most strongly to sucrose, which is by far the most rewarding of our four tastes (NaCl is palatable but not particularly rewarding, see Berridge and Schulkin, 1989
) and least to quinine (the uniquely punishing taste in our array, ), or else most strongly to quinine and least strongly to sucrose (); these patterns occurred more than twice as often as would be expected by chance, assuming equal probability of each pattern (16.7%). Furthermore, 5 of the remaining SD neurons responded to both sucrose and quinine with similar bursts of moderate magnitude.
We confirmed that SD neurons did not, as a group, provide information on taste palatability, analyzing response differences for similar and dissimilar taste pairs as was done for LD neurons. SD responses to taste pairs with similar palatability (e. g., sucrose and NaCl) were not significantly more similar than responses to taste pairs with divergent palatability (e. g., sucrose and quinine). The average firing rate difference for similar taste pairs was 7.4 ± 1.8 spikes/sec while the average firing rate difference for dissimilar taste pairs was 8.8 ± 1.6 spikes/sec; (t (58) = 2.00, p > 0.5).
Previous results from human and non-human primates suggest that dopamine reward responses, both amygdalar and midbrain, are strongest when the reward, positive or negative, is unanticipated (Schultz et al., 1997
; Belova et al., 2007
; Roesch et al., 2007
; Kufahl et al., 2008
), much like behavioral “alpha” responses to strong, unexpected stimuli (Gruart et al., 2000
). When rewards are expected, reward responses shift from the rewarding stimulus itself to the stimulus triggering that expectation (Schultz, 2001
). We therefore analyzed the trials in which the rats initiated delivery of a randomly selected taste by pressing a lever (these trials were pseudo-randomly interspersed among the experimenter-initiated deliveries). While our rats could not learn to predict which taste would arrive following each lever press, they clearly learned to press a lever to receive tastes, and thus to expect taste delivery (delivery that, perhaps due to water restriction, carries a basal reward value). We reasoned that any BLA reward/alpha responses would be uniquely sensitive to the difference between and passive delivery and self-administration, and therefore predicted: 1) that SD taste responses would largely vanish during self-administration, and 2) that these same neurons would show strong, sharp tone responses.
In fact, SD taste responses were almost completely blocked by this manipulation of taste delivery. A full 60% of the SD neurons identified in experimenter-initiated trials responded significantly differently in self-administration trials; in 66.7% of these neurons, this was true for every taste response. Furthermore, the entirety of the changes in SD taste coding wrought by self-administration consisted of response diminutions or outright response eliminations, such that the average magnitude of an SD response was significantly smaller (reduced by > 75%) in self-administration trials (), according to 2-way ANOVA (time post stimulus × delivery condition; Fcondition (9,1) = 8.8, p < 0.01; Finteraction (9, 1) = 25.6, p < 0.001). Only insignificant elevations of SD neuron activity were observed in anticipation of taste delivery, but self-administration nearly abolished taste responses themselves.
Self-administration affects SD responses but not LD responses
shows that the opposite was true for LD neurons. While anticipation of self-administration caused significant elevations of pre-stimulus LD firing rates in the 250 msec immediately preceding stimulus delivery (t(30) = 2.38, p < 0.05), the LD taste responses themselves were unchanged by self-administration (Finteraction (9, 1) = 1.54, p > 0.1). Self-administration changed only 12% of the bins in which LD neurons responded to tastes, the majority (57%) of which were found in the first 250 msec of the responses.
This blocking of taste response was unlikely a direct cause of motor inhibition. Rats were well trained, typically pressing only once upon hearing the tone (average number of presses in the 2.5 sec following the first lever press = 0.069 ±0.055). It is unlikely that any residual movement (end of lever release) could have caused activity that blocked the taste responses, and the latency of the next lever press within the 2.5 seconds post-taste was 1.42±0.46 sec. Furthermore, not only did lever pressing have no effect on LD taste responses, it also failed to inhibit the activity preparatory to LD responses.
Self-administration trials were preceded by a tone that announced taste availability. SD neurons specifically responded to that tone in self-administration trials with short-latency phasic increases in firing (), just as reward neurons in the dopamine system have been shown to do (Schultz, 2001
). The population average and representative example (inset) show these to be classic examples of auditory responses—phasic, and sharply time-locked to tone onset; as each consisted of one or a few spikes/trial, and rats’ reaction times to the tone varied widely (avg ± s.d. = 684 ± 258msec) , these tone responses had no noticeable impact on PSTHs keyed to taste delivery (i. e., ). LD neurons, meanwhile, responded only slightly and gradually to the tone, despite showing strong anticipatory firing leading up to taste delivery (). SD tone responses were significantly stronger than LD tone responses (t(966) = 1.96, p < 0.001).
In summary, SD neuron taste responses were strongly affected by stimulus self-administration, and LD neuron taste responses were not (Finteraction
(9, 1) = 7.19, p < 0.001). Given the similarity between these neurons’ responses and those noted in work on amygdalar reward coding (Schoenbaum et al., 1999
; Belova et al., 2007
; Kufahl et al., 2008
)—their brevity, their short latencies, their patterns of taste and tone responses, and their sensitivity to expectation—we argue that SD neurons are likely involved in the coding of stimulus reward value (while recognizing that they may also be involved in the coding of palatability or motor variables, see Discussion).