Information

What salient features of a {conditioned stimulus,unconditioned stimulus} pair are represented in the lateral amygdala?

What salient features of a {conditioned stimulus,unconditioned stimulus} pair are represented in the lateral amygdala?

In classical conditioning, a conditioned stimulus (CS, e.g., a tone) is presented just before an unconditioned stimulus (UCS, e.g., a mild toe pinch) in repeated trials, such that the CS will eventually evoke the unconditioned response (e.g., withdrawal reflex) on its own.

Such memories of fear and discomfort are said to be held in the lateral amygdala, with a representation of the CS and its UCS (Díaz-Mataix et al, 2011).

Certain areas of the brain have particular representations of stimuli, e.g., a tone of a given frequency, as the primary auditory cortices have "tonotopic" zones in which different areas have a differential response to separate frequencies.

Since the CS/UCS pairing is more abstract than a single tone, I'm curious as to what type of representation of the CS/UCS is actually encoded within the local subnetworks amygdala. I can't imagine that, for the above example, a particular area holds a representative frequency of a tone used as a CS in tight collaboration with a "pain" signal. It might be realistic, but anatomically, that whole area would also have to reflect an exhaustive set of all of the other possible "life events" that the animal has experienced.

So, is this representation in the lateral amygdala just a placeholder to retrieve other pertinent memories stored elsewhere in cortex -- is the hippocampus a major player in keeping this sorted? If, in fact, all these pairings are just weak bindings of diverse stimuli, why is it so difficult to untangle and extinguish more complex types of fears in human patients?

Díaz-Mataix, L., Debiec, J., LeDoux, J.E. & Doyère, V. (2011). Sensory-specific associations stored in the lateral amygdala allow for selective alteration of fear memories. The Journal of Neuroscience, 31, 9538-9543… PDF


The lateral amygdala appears to be involved in representing fear memories after extinction (Hobin, Goosens and Maren, 2003). The extent of the lateral amygdala's involvement in representing these appears to revolve around the context of the {CS, UCS} pair. The authors state the following in their abstract:

Similarly, the majority of LA neurons exhibited context-dependent spike firing; short-latency spike firing was greater to both CSs when they were presented outside of their own extinction context. In contrast, behavioral and neuronal responses to either non-extinguished CSs or habituated auditory stimuli were not contextually modulated. Context-dependent neuronal activity in the LA may be an important mechanism for disambiguating the meaning of fear signals, thereby enabling appropriate behavioral responses to such stimuli.

You appear to be right to suspect the hippocampus' involvement. In a subsequent study by Maren and Hobin (2007) using a similar Pavlovian methodology to the previous study, the authors reported that hippocampal activity was associated with regulation of context-dependent lateral amygdaloid activity and concluded the following:

After saline infusion, rats froze more to the CS when it was presented outside of its extinction context, but froze equally in both contexts after muscimol infusion. In parallel with the behavior, lateral nucleus neurons exhibited context-dependent firing to extinguished CSs, and hippocampal inactivation disrupted this activity pattern. These data reveal a novel role for the hippocampus in regulating the context-specific firing of lateral amygdala neurons after fear memory extinction.

Finally, a context-related function of the lateral amygdala seems to provide a simple and plausible explanation for why fear extinction is far more difficult in human patients than laboratory rats: humans encounter a virtually infinite and certainly unpredictable space of possible contexts, whereas lab rats, by the nature of their unfortunate lot in life, tend to encounter relatively few and predictable contexts.

(I found it somewhat difficult to cover all the bases for your question and subquestions, so please comment if I need to expand on something.)

References

  • Hobin, J. A., Goosens, K. A., & Maren, S. (2003). Context-dependent neuronal activity in the lateral amygdala represents fear memories after extinction. The Journal of neuroscience, 23(23), 8410-8416.
  • Maren, S., & Hobin, J. A. (2007). Hippocampal regulation of context-dependent neuronal activity in the lateral amygdala. Learning & Memory, 14(4), 318-324. Chicago

Role of sensory input distribution and intrinsic connectivity in lateral amygdala during auditory fear conditioning: A computational study

We propose a novel reduced-order neuronal network modeling framework that includes an enhanced firing rate model and a corresponding synaptic calcium-based synaptic learning rule. Specifically, we propose enhancements to the Wilson–Cowan firing-rate neuron model that permit full spike-frequency adaptation seen in biological lateral amygdala (LA) neurons, while being sufficiently general to accommodate other spike-frequency patterns. We also report a technique to incorporate calcium-dependent plasticity in the synapses of the network using a regression scheme to link firing rate to postsynaptic calcium. Together, the single-cell model and the synaptic learning scheme constitute a general framework to develop computationally efficient neuronal networks that employ biologically realistic synaptic learning. The reduced-order modeling framework was validated using a previously reported biophysical conductance-based neuronal network model of a rodent LA that modeled features of Pavlovian conditioning and extinction of auditory fear (Li et al., 2009). The framework was then used to develop a larger LA network model to investigate the roles of tone and shock distributions and of intrinsic connectivity in auditory fear learning. The model suggested combinations of tone and shock densities that would provide experimental estimates of tone responsive and conditioned cell proportions. Furthermore, it provided several insights including how intrinsic connectivity might help distribute sensory inputs to produce conditioned responses in cells that do not directly receive both tone and shock inputs, and how a balance between potentiation of excitation and inhibition prevents stimulus generalization during fear learning.

Highlights

► New firing rate model with full spike-frequency adaptation and non-zero rheobase. ► Calcium-based learning rule implementation for networks of firing rate neurons. ► Framework to study possible tone-shock distributions in LA for learning fear. ► Tone-interneuron connectivity should be >60% to match experimental data. ► Model shows how impairment in inhibitory LTP might cause fear generalization.


Experiment 1

The experimental series reported here was designed to confirm and extend Robinson et al.’s (2010) demonstration of familiarity-based stimulus generalization in a conditioned suppression procedure with rat subjects. Experiment 1 was intended merely to confirm the reliability of Robinson et al.’s basic procedure before its further examination in the remainder of the experimental series. Robinson et al.’s demonstration of familiarity-based generalization comes from two groups of rats that had received sham brain surgery to permit comparison with a separate pair of rats that had received excitotoxic cortical lesions. It is unlikely, though possible, that the rats’ sham surgery had some unintended collateral effect on familiarity-based generalization finding. Experiment 1’s demonstration employed rats that had not received surgery of any type and should, thus, yield fully generalizable findings.

Experiment 1 employed a conditioned suppression procedure in rats and its design is summarized in Figure 1 . During conditioning, Group CT and Group T, received pairings of a clicker (C) and a brief footshock. During testing, generalization of responding, established to C, was assessed to a tone (T). Before those stages, both groups of rats received preexposure to T but only Group CT was given presentations of C. Thus, during the test, for Group CT, both C and T would be familiar but for Group T, only T would be familiar. Pairings of C and the shock during conditioning may also make C familiar. To limit the extent of C’s familiarity for Group T, only four pairings of C and the shock were given. If generalization from C to T were based only on physical stimulus features (i.e., those common to C and T), there would be no difference in the generalized response during test. However, if Robinson et al.’s (2010 see also, Best & Batson, 1977 Iordanova & Honey, 2012 Honey, 1990) finding is replicable, Group CT’s responding to T should be of greater magnitude than Group T’s.

Top: Experimental design of Experiment 1. C = 10 Hz clicker, T = 2-kHz tone, + = 0.5-s, 1.0-mA shock. During preexposure, rats in Group CT received, separately and irregularly sequenced, nonreinforced preexposure to T and to C. Rats in Group T received a similar preexposure treatment except that stimulus C was omitted. The two groups of rats received identical treatments during conditioning and test. During conditioning, rats received C + pairings. During the test rats were presented with T. See text for complete details. Bottom: Mean instrumental response rates during T in the test of Experiment 1 expressed as responses per minute (RPM). Error bars indicate one standard error of their mean.

Method

Subjects and apparatus

Experimentally naïve, male, Lister hooded rats (Rattus norvegicus Charles River, UK) served as subjects. When experimentation was not occurring (see Procedure below), rats were held in an air-conditioned vivarium that was illuminated by fluorescent strip lights between 0700�. Temperatures were maintained between 20 and 23 ଌ. Rats were housed in acrylic cages. To provide rats with environmental enrichment, each cage contained a large cardboard cylinder, and all rats were pair housed. Cages contained fresh wood-chip bedding and tap water was always available. Rats received free access to food (Harlan Teklad, Bicester, UK) in the cages until one week before the experiment began. At that time, rats’ weights were recorded (mean: 247g range: 229�g) and food access was thenceforth restricted. Measured amounts of food were given once daily to reduce gradually rats’ weights to between 80% and 90% of their baseline weight. To promote healthy growth increase during the experiment, rats’ target weight was increased each week. The rate of that increase was based on the mean weekly weight change of a separate group of rats that had been allowed unrestricted access to food and water in our vivarium. Sixteen rats began the experiment but due to a failure of the lever in one Skinner box, it was necessary to exclude one rat from each group, (i.e., ns = 7).

Eight identically specified Skinner boxes (MED Associates, St Albans, VT) were used (30.0 cm 24.0 cm × 20.5 cm high), which were normally not illuminated. Each was individually housed in a sound- and light-attenuating shell. The ceiling and 30.0-cm Skinner box walls (one of which served as a door) were constructed from clear polycarbonate. The 24.0-cm walls were constructed from metal plates. One wall was equipped with a recessed tray to which 45-mg food pellets (Noyes, Lancaster, NH) could be delivered. An infrared beam was sent from one lateral side of the food tray and received on another. Beam interruption could be recorded as a response (henceforth, food-tray activity). A lever was located to the left of the food tray, depression of which actuated a switch that could also be used to record responding (henceforth, lever pressing). The lever could be retracted into the wall to prevent lever pressing. Two lamps, whose 2.5-cm diameter, circular covers were composed of opaque plastic, were located symmetrically adjacent to the food tray (10.5 cm from the floor and 16.0 cm apart, center-to-center). A third lamp was located on the opposite metal wall, centrally and 17.5 cm above the floor. The lamp was shrouded in a metal hood that could direct light toward the ceiling. None of the lamps were operated in any of the experiments reported here.

A heavy-duty relay, located on the outer side of the wall, could be operated at 10 Hz to produce an 80-dB (re. Scale A) train of clicks (henceforth, C). A loud speaker, located on the wall opposite the food tray, could be used to present a 2-kHz and 㲅-dB pure tone (henceforth, T). Background noise (principally provided by an exhaust fan located in the shell) was 65 dB. C and T were of 30-s duration.

The floor was constructed from 19, 4.8-mm diameter, stainless steel rods that ran parallel to the metal walls. Rods were spaced 1.6 cm apart, center-to-center. The floor could be electrified by a scrambled 0.5-s, 1.0-mA current (MED Associates, St Albans, VT, ENV-414SA) to produce a footshock. Experimental events were controlled and recorded with a Microsoft Windows-based personal computer that used the MED PC programming language. All apparatus was held in a quiet laboratory illuminated by ceiling-mounted fluorescent lamps.

Procedure

The procedure comprised three main stages: preexposure, conditioning, and test (see Figure 1 ). The treatment between groups differed only during preexposure.

Baseline training

Lever pressing was established to assess the fear responding (suppression of responding) during the test. Initially the lever was retracted and rats were given response-independent food pellets according to a 60-s, fixed-interval schedule. On the following session, the lever was extended into the box and rats could earn pellets according to variable-interval (VI) schedules. By the end of Baseline Training, rats’ lever pressing was reinforced according to a VI-60 schedule but richer schedules were used earlier in training. The lever pressing VI-60 schedule was operational throughout the remainder of the experiment. Rats received three 1-hr sessions of VI-60 Baseline Training sessions before progression to the preexposure stage.

Preexposure

Rats were divided into two groups, Group CT and Group T that were matched according to their response rates from Baseline Training. During each of six sessions Group CT was exposed to C and T each eight times. On the 1st, 4th and 5th sessions the sequence was T C C T T C C T T C C T T C C T on the other three sessions the sequence was C T T C C T T C C T T C C T T C. Group T’s treatment differed from Group CT’s only in that C was deleted. Group CT and Group T were run on separate sessions to prevent Group T inadvertently hearing C. On half the preexposure days, Group CT was run before Group T. The session duration was around 80 min. Intertrial intervals (ITIs) varied around means of 280 s and 560 s for, respectively, Group CT and Group T.

Conditioning

Conditioning was intended to establish a response (suppression of lever-press responding) to C. Two 1-hr sessions were given during the conditioning stage. In each, C was presented twice, coterminally with the shock. Trials began 570 s and 2370 s from the session’s beginning. A session was subsequently given to allow responding to recover food pellets were earned on the VI-60 schedule but no other stimuli were scheduled to occur.

The test stage was intended to examine differences in the (generalized) responding exhibited to T by Group T and Group CT. T was presented three times in a single session. The intertribal interval (ITI) varied around a mean of 280 s.

Data treatment

A variety of appropriate parametric analyses were used for null-hypothesis testing. Tests evaluated two-tailed hypotheses and α = .050. A Bayesian analysis supplemented the interpretation of a key null result (JASP (Version 0.7.5.5), Amsterdam, the Netherlands). Partial eta squared (ηp 2 ) was used to represent main effect and interaction effect sizes. Standardized 90% confidence intervals for ηp 2 were computed using the methods described by Kelley (2007).

Results and Discussion

Baseline training proceeded successfully. Responding during the first four trials of preexposure is summarized in Table 1 . The introduction of C to Group CT during preexposure resulted in some transitory suppression. Analysis of variance (ANOVA) yielded a significant trial main effect, F(3, 18) = 10.3 p < .001 ηp 2 > .631, 90% CI [.29, .72]. For both groups, the introduction of T during preexposure resulted in a similar disruption of responding. ANOVA yielded a significant trial main effect, F(3, 36) = 3.4 p < .030 ηp 2 > .219, 90% CI [.01, .35], but no group main effect nor Group x Trial interaction, both Fs < 1. A notable implication of this evidence of unconditioned suppression, and its habituation, is that it may modify the conditioned suppression seen during the subsequent conditioning and test stages.

Table 1

Trial/block
CT
GroupStatistic12341234
Note. The leftmost and rightmost quartets of columns summarize responding to the clicker (C) and to the tone (T) respectively. An em dash indicates that a group did not receive preexposure to either stimulus.
Experiment 1
CTM8.015.111.122.66.010.99.711.1
T 4.68.66.911.4
CTSEM2.02.92.22.22.12.41.71.9
T 1.42.22.32.3
Experiment 2
CTM10.826.329.325.05.010.820.320.8
T 4.012.330.521.3
C 20.811.535.823.0
0
CTSEM3.53.95.03.31.32.43.42.4
T 1.42.56.53.6
C 4.82.95.33.4
0
Experiment 3
CT 420M2.38.310.312.37.512.311.310.0
CT 280 3.011.815.017.811.818.513.516.3
CT 140 .57.513.513.86.315.011.312.5
0
T 6.08.814.313.0
CT 420SEM1.51.81.51.62.32.11.41.8
CT 280 1.82.82.32.02.31.71.62.3
CT 140 .32.51.61.62.52.62.11.3
0
T 1.92.02.01.5

Responding to C during its four conditioning pairings with the shock was almost completely suppressed by the end of that stage but, earlier in that stage, suppression to C was less marked in Group CT (mean rpm rates: 22, 23, 4, 2 SEMs: 2.6, 1.8, 1.2, 0.9) than in Group T (mean rpm rates: 14, 1, 1, 0 SEMs: 2.6, 1.8, 1.2, 0.9). ANOVA yielded main effects of both trial, F(3, 36) = 42.3 p < .001 ηp 2 > .779, 90% CI [.64, .83], and group, F(1, 12) = 47.3 p < .001 ηp 2 > .798, 90% CI [.53, .87], and an interaction between those variables, F(3, 36) = 13.6 p < .001 ηp 2 > .530, 90% CI [.29, .63]. Between-groups simple main effect (SME) analysis, which used the common error-term, yielded reliable group differences at Trials 1 and 2, smaller F(1, 48) = 11.3 p < .010, but at neither Trial 3 nor Trial 4, larger F(1, 48) = 2.3 p > .050. The pattern of results is most simply understood as reflecting Group T’s initial unconditioned suppression to C, like that seen during preexposure to C by Group CT, and its gradual replacement by conditioned suppression. For Group CT, preexposure to C allowed unconditioned suppression to habituate and its changes reflect only the acquisition of conditioned suppression.

The data of principle interest, those of the test of T, are summarized in Figure 1 . Suppression was relatively great on the first trial in both groups but decreased over the course of testing. However, the level of suppression throughout the test was more marked in Group CT than in Group T. That impression was confirmed using ANOVA that yielded main effects of group, F(1, 12) = 5.9 p < .033 ηp 2 > .328, 90% CI [.02, .56], trial, F(2, 24) = 9.4 p < .001 ηp 2 > .439, 90% CI [.15, .58], but no interaction between those factors, F(2, 24) = 1.4 p > .273. An estimate of baseline response rates was made using the response rates during the 30-s period immediately preceding each of the tone presentation and these data are summarized in Table 2 . ANOVA on these data, having the same format as that of the test data, yielded a main effect of trial, F(2, 24) = 4.5 p < .023 ηp 2 > .272, 90% CI [.02, .44] but no main effect of group nor Group x Trial interaction, Fs < 1.

Table 2

GroupStatisticTrial/Block
1234
Note.𠀼 = clicker T = tone.
Experiment 1
CTM8.38.03.1
T 8.914.04.9
CTSEM3.43.41.2
T 2.23.81.3
Experiment 2
CTM49.132.360.634.8
T 67.047.859.539.8
C 40.838.853.336.9
0 50.432.853.032.6
CTSEM4.93.36.83.1
T 7.05.98.14.2
C 7.04.27.04.7
0 9.52.54.34.9
Experiment 3
CT 420M11.09.510.88.0
CT 280 9.813.09.812.0
CT 140 11.813.011.310.3
0 12.013.011.58.3
T 9.59.815.512.3
CT 420SEM1.80.91.21.5
CT 280 2.22.62.52.3
CT 140 2.73.43.42.5
0 3.42.72.42.5
T 1.71.82.81.3

The results of Experiment 1 provide a replication of Robinson et al.’s (2010) demonstration of familiarity-based generalization in surgically naive rats. This procedure parallels findings in conditioned taste aversion (Best & Batson, 1977) and appetitive conditioning (Honey, 1990). Group CT’s preexposure treatment involved presentation of both C and T and was designed to ensure those stimuli were both encoded as familiar. In contrast, Group T’s preexposure treatment was designed to make C’s and T’s coding incongruent that is, with T familiar and C novel. Based on standard assumptions, C and T will have a set of common representational elements that govern stimulus generalization to the same extent in both groups. The fact that Group CT’s level of suppression was greater than Group T’s suggests that, if standard assumptions are correct, some additional process was occurring to enhance generalization from C to T in Group CT—that process could be the result of generalization based upon novelty or familiarity coding. However, several other factors that could affect test performance to T will be considered before accepting that interpretation. First, unconditioned suppression to T was detected during preexposure, which could have certainly have affected test performance to T (i.e., the generalized fear response could be contaminated by unconditioned suppression see, e.g., Robinson, Sanderson, Aggleton, & Jenkins, 2009 Jones, Whitt, & Robinson, 2012). But because both groups received preexposure to T, and because the course of habituation of unconditioned suppression was similar, this seems unlikely to generate the crucial group difference. One might anticipate that Group CT’s habituation of unconditioned suppression to C might generalize to T, being mediated by a subset (x) of shared representational elements, and reduce suppression relative to Group T. If such a process did occur, we did not detect it during preexposure and, of course, that process would have worked against—not in favor of—the obtained group difference. Neither account based on unconditioned suppression appears to provide a suitable account of the results.

Second, any account based upon latent inhibition (e.g., Lubow & Moore, 1959), either of C or of the subset of features (x) shared by C and T, appears similarly inadequate in explaining the results. Group CT’s preexposure to C might reduce C’s capacity to govern responding in that group but that would act against the observed group difference. Here, the set of x features that mediate generalization may lose more associability in Group CT than in Group T𠅍uring preexposure x was presented twice as often in Group CT than in Group T (cf. Bennett, Wills, Wells, & Mackintosh, 1994 McLaren & Mackintosh, 2002). Thus, like the habituation account, this latent inhibition account fails to produce a realistic alternative account of the main findings because it predicts the opposite result to our findings.


Intranasal oxytocin decreases fear generalization in males, but does not modulate discrimination threshold

A previously acquired fear response often spreads to perceptually or conceptually close stimuli or contexts. This process, known as fear generalization, facilitates the avoidance of danger, and dysregulations in this process play an important role in anxiety disorders. Oxytocin (OT) has been shown to modulate fear learning, yet effects on fear generalization remain unknown.

Methods

We employed a randomized, placebo-controlled, double-blind, between-subject design during which healthy male participants received either intranasal OT or placebo (PLC) following fear acquisition and before fear generalization with concomitant acquisition of skin conductance responses (SCRs). Twenty-four to 72 h before the fear learning and immediately after the fear generalization task, participants additionally complete a discrimination threshold task.

Results

Relative to PLC, OT significantly reduced perceived risk and SCRs towards the CS+ and GS1 (the generalization stimulus that is most similar to CS+) during fear generalization, whereas the discrimination threshold was not affected.

Conclusions

Together, the results suggest that OT can attenuate fear generalization in the absence of effects on discrimination threshold. This study provides the first evidence for effects of OT on fear generalization in humans and suggests that OT may have therapeutic potential in anxiety disorders characterized by dysregulated fear generalization.


Acknowledgements

We thank B. Werner, N. Kaouane, and the Next Generation Sequencing (NGS) Core at Vienna Biocenter Core Facilities GmbH (VBCF) for neuronal population sequencing and S. Rumpel for scientific discussion and advice. We thank M. Pasieka of the Scientific Computing Unit at the Vienna Bio Campus (VBC), the Facility for Advanced Microscopy at the Vienna Bio Campus (VBC), and in particular, P. Pasierbek and T. Lendl for help with confocal microscopy. We further thank the Facility for Preclinical Phenotyping at the Vienna Biocenter Core Facilities GmbH (VBCF), M. al Banchaabouchi, the IMP animal facility, and A. Stepanek for help with behavioral assays and animal research. We thank HistoPathology at the VBCF for expertise and histological services. B. Ferger (Boehringer Ingelheim, Germany) and G. Filk (Brains On-Line LLC, San Francisco, USA) provided valuable discussions and microdialysis data, and L. Piszczek set up and analyzed FACS control experiments for D1R knockdown. We thank M. Roth and J. Jude for advice in RNAi experiments. W.H. was supported by a grant from the European Community’s Seventh Framework Programme (FP/2007-2013)/ERC grant agreement no. 311701, the Research Institute of Molecular Pathology (IMP), Boehringer Ingelheim, and the Austrian Research Promotion Agency (FFG). S.M., T.M., and V.L. were supported by the DFG (TP B06 of SFB 779). The Vienna Biocenter Core Facilities GmgH (VBCF) Preclinical Phenotyping Facility acknowledges funding from the Austrian Federal Ministry of Science, Research & Economy and from the City of Vienna.


Affiliations

Laboratory for Behavioral Neurology and Imaging of Cognition, Department of Neuroscience, University of Geneva, 1202, Geneva, Switzerland

E. Meaux, V. Sterpenich & P. Vuilleumier

Laboratory of Cognitive Neurosciences (LNC²), UMR INSERM U960, Ecole Normale Supérieure, PSL Research University, 75005, Paris, France

Department of Clinical Neurology, University Hospital of Geneva, 1206, Geneva, Switzerland

Swiss Center for Affective Sciences, University of Geneva, 1202, Geneva, Switzerland


Conclusion

Our results demonstrate the importance of contingency awareness for contextual fear conditioning. There were striking differences between subjects classified as aware and those classified as unaware. Furthermore, these differences not only showed that contingency awareness is necessary for contextual conditioning, but also shed light on potential mechanisms for contingency learning. Hence, our study contributes to the current debate on the necessity of contingency awareness during associative learning and extends it to contextual conditioning paradigms.


Involvement of the amygdala in stimulus-reward associations: Interaction with the ventral striatum

The involvement of the amygdala in the potentiation of responding for conditioned reinforcers following intra-accumbens amphetamine injections has been studied. Thirsty rats were trained to associate a light-noise compound stimulus with water and then implanted with guide cannulae in the nucleus accumbens. Half of these rats received excitotoxic lesions of the basolateral region of the amygdala by infusingN-methyl- d -aspartate, whereas the other half received infusions of the vehicle. In the test phase, water was no longer presented but responding on one of two novel levers produced the light-noise compound (the conditioned reinforcer) whereas responding on the other lever had no effect. The two groups received four counterbalanced intra-accumbens infusions of amphetamine (3, 10 and 30 μg/μl) or vehicle over four test days. Intra-accumbens amphetamine infusions dose-dependently increased responding on the lever providing a conditioned reinforcer but had no significant effect on responding on the lever which did not produce the conditioned reinforcer. Compared with controls, the lesioned group exhibited a significant, selective reduction in responding on the lever providing a conditioned reinforcer. with no change on the lever on which responding had no consequence, irrespective of drug or control treatment. Control experiments showed that the amygdala lesioned animals were not hypodipsic and exhibited similar levels of hyperactivity following intra-accumbens infusions of d -amphetamine. Furthermore, the capacity to discriminate the conditioned stimulus as well as to acquire a new motor task was not altered by the lesion.

These results indicate a role for the amygdala in mediating the effects of stimulus-reward associations on behaviour, via an action on dopamine-dependent mechanisms of the ventral striatum.


III. Can neural systems analysis help us understand the contents of learning?

In section I, I noted that Spence disparaged physiologizing, even Hull's, as more likely to be misleading than useful in characterizing mathematical and behavioral aspects of habit learning. However, the results of the devaluation tasks I've described imply that associative learning can engage a variety of levels of neural processing. Plasticity is not unique to any of the circles in Figure 1b . For example, studies of neural plasticity in eyelid conditioning (e.g., Medina et al., 2000 Steinmetz et al., 1989 Thompson et al., 1998) have identified cerebellar sites of plasticity that are characterizable as being within “output” paths and hence more “S-R”, as well as other sites earlier in the processing stream. A reasonable research program might imagine the circumstances under which cues come to control processing in different brain systems, which preferentially control different aspects of behavior. Understanding information flow in the brain may help us understand why, for example, some products of learning, such as the control of TR responses and the ability to support mediated learning, are related in their rapid bitonic acquisition functions, why others seem to maintain sensitivity to devaluation over extensive training, and still others seem to lose such sensitivity over training.

A variety of neurobiological techniques have been harnessed to provide information relevant to understanding the contents of learning. The methods of brain stimulation have gone far beyond the crude stimulation of motor cortex, as in Loucks's (1935) experiments. For example, in the neural systems analysis of eyelid conditioning, the replacement of real events such as CS and US (or both, e.g., Steinmetz et al., 1989) with brain stimulation has revealed events critical for eyelid conditioning. Similarly, patterned stimulation of amygdala has helped elucidate the mechanisms of acquisition and extinction of fear conditioning (Vidal-Gonzalez et al., 2006).

Precise, pharmacologically selective lesions and reversible inactivations of various cell groups can selectivity alter rats' sensitivity to devaluation, without affecting other aspects of performance. For example, damage to components of circuitry including the basolateral amygdala (BLA), orbitofrontal cortex (OFC), subregions of the medialprefrontal cortex, and in some situations the mediodorsal thalamus, interfere with rats' Pavlovian devaluation performance without affecting the acquisition of food-cup CRs or taste aversions (Gallagher et al., 1999 Hatfield et al., 1996 Maddux & Holland, 2007 Pickens, 2008 Pickens et al., 2003). Furthermore, these studies indicate that different portions of that circuitry have specialized functions within the devaluation task. For example, for rats to display devaluation effects with single-reinforcer procedures, BLA function is needed during initial CS-food pairings, but not thereafter. That is, if rats acquired CS-food associations while BLA function is intact, then subsequent lesions do not impair performance on this form of devaluation, as if BLA function is needed for rats to acquire S-S rather than S-R associations, but not to use previously-established S-S associations to control behavior (Pickens et al., 2003). By contrast, OFC function appears to be critical for the expression as well as the acquisition of such associations in devaluation tasks. Lesions of OFC disrupt devaluation performance (that is, rats fail to spontaneously reduce responding to the CS after US devaluation) whether they are performed prior to CS-food, food aversion, or final test phases (Pickens et al., 2003, 2005). Finally, involvement of these brain regions may vary with variations in task demands. For example, although when a single cue-reinforcer combination is used, BLA function is not required once cue-reinforcer associations are established, when two or more cues and reinforcers are used, BLA function must also be intact at the time of taste aversion training and/or devaluation testing (Johnson et al., 2007). Similarly, Pickens (2008) found that function of mediodorsal thalamus was important for performance on a Pavlovian devaluation task only if that task required a strategy shift from a previous task.

The results of recent electrophysiological recording studies also suggest that conditioning procedures may establish a variety of types of associations, both within and across interconnected brain regions. For example, using an odor-cued discrimination task, Schoenbaum, Chiba, and Gallagher (1998) found neurons in BLA and OFC that might be characterized as reflecting S-S and response-stimulus (R-S) associations. These neurons initially responded selectively to one of the two reinforcers used in the task, but over the course of training their activity came under the control of either a particular odor cue or a particular response. Later studies showed that the nature of neuronal coding of stimulus- or response-outcome information in these two brain regions depended on communication between them (e.g., Saddoris, Gallagher, & Schoenbaum, 2005 Schoenbaum, et al., 2003). Most recently, Furuyashiki, Holland, and Gallagher (2008) also contrasted the activity of OFC neurons that coded outcome information with those that coded response information. These latter neurons responded specifically to particular responses but not to particular reinforcers. Although these latter neurons cannot be construed as a substrate for S-R associations, because they increased their activity only after performance of the coded response, their existence shows that at least in some brain regions, individual neurons may code a variety of kinds of task information.

Finally, we have been using techniques of immediate-early gene expression to relate brain function to performance in simple devaluation (and other) tasks. Our intent is to relate variations in performance under different conditions to differences in brain systems engaged under those conditions. Post-mortem tissue analysis can reveal detailed information about individual neurons that were active (Lee et al., 2005) or undergoing plastic change (Guzowski & Worley, 2001 Petrovich et al., 2005) during fairly restricted time intervals, such as a particular behavioral test episode, before sacrifice. For example, after assessing TR responses to a minimally-trained tone CS, in the absence of sucrose, Kerfoot et al. (2007 Figure 5 ) sacrificed their rats to examine the expression of FOS, the protein product of the activity-dependent immediate-early gene c-fos. They found learning- and devaluation-dependent FOS expression in a number of brain regions known from lesion experiments (just described) to be critical for learning that is sensitive to outcome devaluation (basolateral amygdala and orbitofrontal cortex Holland & Gallagher, 2004), in regions related to the display of TR responses (accumbens shell Reynolds & Berridge, 2002), and in regions related to processing of taste information (gustatory cortex Kiefer & Orr, 1992). These last observations are especially interesting from our earlier suggestion that conditioning may endow CSs with the ability to activate perceptual processing of absent USs. If as a result of tone-sucrose pairings, the tone aroused the perception of sweetness, making the plain water taste sweet, rats in both the Devalue and Maintain conditions might be expected to show enhanced FOS activity in gustatory cortex, which they did. Furthermore, because rats in the Maintain condition would respond to sweet with appetitive taste-reactivity responses, the tone alone would also elicit those responses and FOS activity in a portion of the accumbens shell correlated with such responses. By contrast, because rats in the Devalue condition would respond to sweet with aversive responses, the tone would provoke aversive responses and FOS in another subregion of accumbens shell correlated with aversive TR responses. All of these outcomes were observed. Given Holland et al.'s (2008) findings, it would be intriguing to determine if a more extensively-trained CS, which fails to elicit appetitive TR responses in training or evoke negative TR responses after devaluation, and which does not support mediated taste-aversion learning, would also fail to induce FOS in the accumbens shell or gustatory cortex.

Interestingly, although Kerfoot et al. (2007) found conditioning-dependent FOS expression in the central nucleus of the amygdala (CeA), this expression was unaffected by devaluation condition (devalued or maintained). This observation is notable for three reasons. First, it suggests that associatively-activated taste memories are not completely interchangeable with the tastes themselves. Taste and illness information converge in this region (Bernstein & Koh, 2007 Yamamoto, 2007), and CeA is known to be important in many aspects of the learning and expression of taste aversions (Lamprecht and Dudai, 2000 Yamamoto, 2007). However, if an associatively-activated taste memory instigated these aspects of taste processing, we would have observed differential CeA activity in Maintain and Devalue conditions. Second, lesions of CeA do not affect devaluation performance (Hatfield et al., 1996). Third, CeA function is critical for the acquisition of conditioned ORs, which in other circumstances Holland and Straub (1979) found to be relatively insensitive to devaluation by food-LiCl pairings. Taken together, these last two observations suggest converging evidence that relates differences in the sensitivity of conditioned ORs and food-related CRs to LiCl-based devaluation procedures (Holland & Straub, 1979) to differences in brain circuitry subserving those learned responses. Differences in operating characteristics of those systems may determine the differential sensitivity of different behavioral systems to parameters of devaluation.

These neural systems studies of devaluation and related phenomena make it clear that questions of the contents of learning are complex. Even in apparently simple behavioral systems such as the eyeblink reflex, opportunities for plastic change abound in the neural systems that subserve them. The consequences of experimental manipulations of environmental stimuli for learning may vary considerably across these systems and their components. It has been increasingly difficult to distinguish between S-S and S-R associations with any confidence on the basis of any single behavioral assay or aspect of neural processing. Characterization of multiple behavioral and neural consequences of variations in associative learning procedures should lead to richer, if perhaps less fathomable, descriptions of the nature of learning.


Acknowledgements

We thank B. Werner, N. Kaouane, and the Next Generation Sequencing (NGS) Core at Vienna Biocenter Core Facilities GmbH (VBCF) for neuronal population sequencing and S. Rumpel for scientific discussion and advice. We thank M. Pasieka of the Scientific Computing Unit at the Vienna Bio Campus (VBC), the Facility for Advanced Microscopy at the Vienna Bio Campus (VBC), and in particular, P. Pasierbek and T. Lendl for help with confocal microscopy. We further thank the Facility for Preclinical Phenotyping at the Vienna Biocenter Core Facilities GmbH (VBCF), M. al Banchaabouchi, the IMP animal facility, and A. Stepanek for help with behavioral assays and animal research. We thank HistoPathology at the VBCF for expertise and histological services. B. Ferger (Boehringer Ingelheim, Germany) and G. Filk (Brains On-Line LLC, San Francisco, USA) provided valuable discussions and microdialysis data, and L. Piszczek set up and analyzed FACS control experiments for D1R knockdown. We thank M. Roth and J. Jude for advice in RNAi experiments. W.H. was supported by a grant from the European Community’s Seventh Framework Programme (FP/2007-2013)/ERC grant agreement no. 311701, the Research Institute of Molecular Pathology (IMP), Boehringer Ingelheim, and the Austrian Research Promotion Agency (FFG). S.M., T.M., and V.L. were supported by the DFG (TP B06 of SFB 779). The Vienna Biocenter Core Facilities GmgH (VBCF) Preclinical Phenotyping Facility acknowledges funding from the Austrian Federal Ministry of Science, Research & Economy and from the City of Vienna.


Affiliations

Laboratory for Behavioral Neurology and Imaging of Cognition, Department of Neuroscience, University of Geneva, 1202, Geneva, Switzerland

E. Meaux, V. Sterpenich & P. Vuilleumier

Laboratory of Cognitive Neurosciences (LNC²), UMR INSERM U960, Ecole Normale Supérieure, PSL Research University, 75005, Paris, France

Department of Clinical Neurology, University Hospital of Geneva, 1206, Geneva, Switzerland

Swiss Center for Affective Sciences, University of Geneva, 1202, Geneva, Switzerland


Involvement of the amygdala in stimulus-reward associations: Interaction with the ventral striatum

The involvement of the amygdala in the potentiation of responding for conditioned reinforcers following intra-accumbens amphetamine injections has been studied. Thirsty rats were trained to associate a light-noise compound stimulus with water and then implanted with guide cannulae in the nucleus accumbens. Half of these rats received excitotoxic lesions of the basolateral region of the amygdala by infusingN-methyl- d -aspartate, whereas the other half received infusions of the vehicle. In the test phase, water was no longer presented but responding on one of two novel levers produced the light-noise compound (the conditioned reinforcer) whereas responding on the other lever had no effect. The two groups received four counterbalanced intra-accumbens infusions of amphetamine (3, 10 and 30 μg/μl) or vehicle over four test days. Intra-accumbens amphetamine infusions dose-dependently increased responding on the lever providing a conditioned reinforcer but had no significant effect on responding on the lever which did not produce the conditioned reinforcer. Compared with controls, the lesioned group exhibited a significant, selective reduction in responding on the lever providing a conditioned reinforcer. with no change on the lever on which responding had no consequence, irrespective of drug or control treatment. Control experiments showed that the amygdala lesioned animals were not hypodipsic and exhibited similar levels of hyperactivity following intra-accumbens infusions of d -amphetamine. Furthermore, the capacity to discriminate the conditioned stimulus as well as to acquire a new motor task was not altered by the lesion.

These results indicate a role for the amygdala in mediating the effects of stimulus-reward associations on behaviour, via an action on dopamine-dependent mechanisms of the ventral striatum.


III. Can neural systems analysis help us understand the contents of learning?

In section I, I noted that Spence disparaged physiologizing, even Hull's, as more likely to be misleading than useful in characterizing mathematical and behavioral aspects of habit learning. However, the results of the devaluation tasks I've described imply that associative learning can engage a variety of levels of neural processing. Plasticity is not unique to any of the circles in Figure 1b . For example, studies of neural plasticity in eyelid conditioning (e.g., Medina et al., 2000 Steinmetz et al., 1989 Thompson et al., 1998) have identified cerebellar sites of plasticity that are characterizable as being within “output” paths and hence more “S-R”, as well as other sites earlier in the processing stream. A reasonable research program might imagine the circumstances under which cues come to control processing in different brain systems, which preferentially control different aspects of behavior. Understanding information flow in the brain may help us understand why, for example, some products of learning, such as the control of TR responses and the ability to support mediated learning, are related in their rapid bitonic acquisition functions, why others seem to maintain sensitivity to devaluation over extensive training, and still others seem to lose such sensitivity over training.

A variety of neurobiological techniques have been harnessed to provide information relevant to understanding the contents of learning. The methods of brain stimulation have gone far beyond the crude stimulation of motor cortex, as in Loucks's (1935) experiments. For example, in the neural systems analysis of eyelid conditioning, the replacement of real events such as CS and US (or both, e.g., Steinmetz et al., 1989) with brain stimulation has revealed events critical for eyelid conditioning. Similarly, patterned stimulation of amygdala has helped elucidate the mechanisms of acquisition and extinction of fear conditioning (Vidal-Gonzalez et al., 2006).

Precise, pharmacologically selective lesions and reversible inactivations of various cell groups can selectivity alter rats' sensitivity to devaluation, without affecting other aspects of performance. For example, damage to components of circuitry including the basolateral amygdala (BLA), orbitofrontal cortex (OFC), subregions of the medialprefrontal cortex, and in some situations the mediodorsal thalamus, interfere with rats' Pavlovian devaluation performance without affecting the acquisition of food-cup CRs or taste aversions (Gallagher et al., 1999 Hatfield et al., 1996 Maddux & Holland, 2007 Pickens, 2008 Pickens et al., 2003). Furthermore, these studies indicate that different portions of that circuitry have specialized functions within the devaluation task. For example, for rats to display devaluation effects with single-reinforcer procedures, BLA function is needed during initial CS-food pairings, but not thereafter. That is, if rats acquired CS-food associations while BLA function is intact, then subsequent lesions do not impair performance on this form of devaluation, as if BLA function is needed for rats to acquire S-S rather than S-R associations, but not to use previously-established S-S associations to control behavior (Pickens et al., 2003). By contrast, OFC function appears to be critical for the expression as well as the acquisition of such associations in devaluation tasks. Lesions of OFC disrupt devaluation performance (that is, rats fail to spontaneously reduce responding to the CS after US devaluation) whether they are performed prior to CS-food, food aversion, or final test phases (Pickens et al., 2003, 2005). Finally, involvement of these brain regions may vary with variations in task demands. For example, although when a single cue-reinforcer combination is used, BLA function is not required once cue-reinforcer associations are established, when two or more cues and reinforcers are used, BLA function must also be intact at the time of taste aversion training and/or devaluation testing (Johnson et al., 2007). Similarly, Pickens (2008) found that function of mediodorsal thalamus was important for performance on a Pavlovian devaluation task only if that task required a strategy shift from a previous task.

The results of recent electrophysiological recording studies also suggest that conditioning procedures may establish a variety of types of associations, both within and across interconnected brain regions. For example, using an odor-cued discrimination task, Schoenbaum, Chiba, and Gallagher (1998) found neurons in BLA and OFC that might be characterized as reflecting S-S and response-stimulus (R-S) associations. These neurons initially responded selectively to one of the two reinforcers used in the task, but over the course of training their activity came under the control of either a particular odor cue or a particular response. Later studies showed that the nature of neuronal coding of stimulus- or response-outcome information in these two brain regions depended on communication between them (e.g., Saddoris, Gallagher, & Schoenbaum, 2005 Schoenbaum, et al., 2003). Most recently, Furuyashiki, Holland, and Gallagher (2008) also contrasted the activity of OFC neurons that coded outcome information with those that coded response information. These latter neurons responded specifically to particular responses but not to particular reinforcers. Although these latter neurons cannot be construed as a substrate for S-R associations, because they increased their activity only after performance of the coded response, their existence shows that at least in some brain regions, individual neurons may code a variety of kinds of task information.

Finally, we have been using techniques of immediate-early gene expression to relate brain function to performance in simple devaluation (and other) tasks. Our intent is to relate variations in performance under different conditions to differences in brain systems engaged under those conditions. Post-mortem tissue analysis can reveal detailed information about individual neurons that were active (Lee et al., 2005) or undergoing plastic change (Guzowski & Worley, 2001 Petrovich et al., 2005) during fairly restricted time intervals, such as a particular behavioral test episode, before sacrifice. For example, after assessing TR responses to a minimally-trained tone CS, in the absence of sucrose, Kerfoot et al. (2007 Figure 5 ) sacrificed their rats to examine the expression of FOS, the protein product of the activity-dependent immediate-early gene c-fos. They found learning- and devaluation-dependent FOS expression in a number of brain regions known from lesion experiments (just described) to be critical for learning that is sensitive to outcome devaluation (basolateral amygdala and orbitofrontal cortex Holland & Gallagher, 2004), in regions related to the display of TR responses (accumbens shell Reynolds & Berridge, 2002), and in regions related to processing of taste information (gustatory cortex Kiefer & Orr, 1992). These last observations are especially interesting from our earlier suggestion that conditioning may endow CSs with the ability to activate perceptual processing of absent USs. If as a result of tone-sucrose pairings, the tone aroused the perception of sweetness, making the plain water taste sweet, rats in both the Devalue and Maintain conditions might be expected to show enhanced FOS activity in gustatory cortex, which they did. Furthermore, because rats in the Maintain condition would respond to sweet with appetitive taste-reactivity responses, the tone alone would also elicit those responses and FOS activity in a portion of the accumbens shell correlated with such responses. By contrast, because rats in the Devalue condition would respond to sweet with aversive responses, the tone would provoke aversive responses and FOS in another subregion of accumbens shell correlated with aversive TR responses. All of these outcomes were observed. Given Holland et al.'s (2008) findings, it would be intriguing to determine if a more extensively-trained CS, which fails to elicit appetitive TR responses in training or evoke negative TR responses after devaluation, and which does not support mediated taste-aversion learning, would also fail to induce FOS in the accumbens shell or gustatory cortex.

Interestingly, although Kerfoot et al. (2007) found conditioning-dependent FOS expression in the central nucleus of the amygdala (CeA), this expression was unaffected by devaluation condition (devalued or maintained). This observation is notable for three reasons. First, it suggests that associatively-activated taste memories are not completely interchangeable with the tastes themselves. Taste and illness information converge in this region (Bernstein & Koh, 2007 Yamamoto, 2007), and CeA is known to be important in many aspects of the learning and expression of taste aversions (Lamprecht and Dudai, 2000 Yamamoto, 2007). However, if an associatively-activated taste memory instigated these aspects of taste processing, we would have observed differential CeA activity in Maintain and Devalue conditions. Second, lesions of CeA do not affect devaluation performance (Hatfield et al., 1996). Third, CeA function is critical for the acquisition of conditioned ORs, which in other circumstances Holland and Straub (1979) found to be relatively insensitive to devaluation by food-LiCl pairings. Taken together, these last two observations suggest converging evidence that relates differences in the sensitivity of conditioned ORs and food-related CRs to LiCl-based devaluation procedures (Holland & Straub, 1979) to differences in brain circuitry subserving those learned responses. Differences in operating characteristics of those systems may determine the differential sensitivity of different behavioral systems to parameters of devaluation.

These neural systems studies of devaluation and related phenomena make it clear that questions of the contents of learning are complex. Even in apparently simple behavioral systems such as the eyeblink reflex, opportunities for plastic change abound in the neural systems that subserve them. The consequences of experimental manipulations of environmental stimuli for learning may vary considerably across these systems and their components. It has been increasingly difficult to distinguish between S-S and S-R associations with any confidence on the basis of any single behavioral assay or aspect of neural processing. Characterization of multiple behavioral and neural consequences of variations in associative learning procedures should lead to richer, if perhaps less fathomable, descriptions of the nature of learning.


Role of sensory input distribution and intrinsic connectivity in lateral amygdala during auditory fear conditioning: A computational study

We propose a novel reduced-order neuronal network modeling framework that includes an enhanced firing rate model and a corresponding synaptic calcium-based synaptic learning rule. Specifically, we propose enhancements to the Wilson–Cowan firing-rate neuron model that permit full spike-frequency adaptation seen in biological lateral amygdala (LA) neurons, while being sufficiently general to accommodate other spike-frequency patterns. We also report a technique to incorporate calcium-dependent plasticity in the synapses of the network using a regression scheme to link firing rate to postsynaptic calcium. Together, the single-cell model and the synaptic learning scheme constitute a general framework to develop computationally efficient neuronal networks that employ biologically realistic synaptic learning. The reduced-order modeling framework was validated using a previously reported biophysical conductance-based neuronal network model of a rodent LA that modeled features of Pavlovian conditioning and extinction of auditory fear (Li et al., 2009). The framework was then used to develop a larger LA network model to investigate the roles of tone and shock distributions and of intrinsic connectivity in auditory fear learning. The model suggested combinations of tone and shock densities that would provide experimental estimates of tone responsive and conditioned cell proportions. Furthermore, it provided several insights including how intrinsic connectivity might help distribute sensory inputs to produce conditioned responses in cells that do not directly receive both tone and shock inputs, and how a balance between potentiation of excitation and inhibition prevents stimulus generalization during fear learning.

Highlights

► New firing rate model with full spike-frequency adaptation and non-zero rheobase. ► Calcium-based learning rule implementation for networks of firing rate neurons. ► Framework to study possible tone-shock distributions in LA for learning fear. ► Tone-interneuron connectivity should be >60% to match experimental data. ► Model shows how impairment in inhibitory LTP might cause fear generalization.


Intranasal oxytocin decreases fear generalization in males, but does not modulate discrimination threshold

A previously acquired fear response often spreads to perceptually or conceptually close stimuli or contexts. This process, known as fear generalization, facilitates the avoidance of danger, and dysregulations in this process play an important role in anxiety disorders. Oxytocin (OT) has been shown to modulate fear learning, yet effects on fear generalization remain unknown.

Methods

We employed a randomized, placebo-controlled, double-blind, between-subject design during which healthy male participants received either intranasal OT or placebo (PLC) following fear acquisition and before fear generalization with concomitant acquisition of skin conductance responses (SCRs). Twenty-four to 72 h before the fear learning and immediately after the fear generalization task, participants additionally complete a discrimination threshold task.

Results

Relative to PLC, OT significantly reduced perceived risk and SCRs towards the CS+ and GS1 (the generalization stimulus that is most similar to CS+) during fear generalization, whereas the discrimination threshold was not affected.

Conclusions

Together, the results suggest that OT can attenuate fear generalization in the absence of effects on discrimination threshold. This study provides the first evidence for effects of OT on fear generalization in humans and suggests that OT may have therapeutic potential in anxiety disorders characterized by dysregulated fear generalization.


Experiment 1

The experimental series reported here was designed to confirm and extend Robinson et al.’s (2010) demonstration of familiarity-based stimulus generalization in a conditioned suppression procedure with rat subjects. Experiment 1 was intended merely to confirm the reliability of Robinson et al.’s basic procedure before its further examination in the remainder of the experimental series. Robinson et al.’s demonstration of familiarity-based generalization comes from two groups of rats that had received sham brain surgery to permit comparison with a separate pair of rats that had received excitotoxic cortical lesions. It is unlikely, though possible, that the rats’ sham surgery had some unintended collateral effect on familiarity-based generalization finding. Experiment 1’s demonstration employed rats that had not received surgery of any type and should, thus, yield fully generalizable findings.

Experiment 1 employed a conditioned suppression procedure in rats and its design is summarized in Figure 1 . During conditioning, Group CT and Group T, received pairings of a clicker (C) and a brief footshock. During testing, generalization of responding, established to C, was assessed to a tone (T). Before those stages, both groups of rats received preexposure to T but only Group CT was given presentations of C. Thus, during the test, for Group CT, both C and T would be familiar but for Group T, only T would be familiar. Pairings of C and the shock during conditioning may also make C familiar. To limit the extent of C’s familiarity for Group T, only four pairings of C and the shock were given. If generalization from C to T were based only on physical stimulus features (i.e., those common to C and T), there would be no difference in the generalized response during test. However, if Robinson et al.’s (2010 see also, Best & Batson, 1977 Iordanova & Honey, 2012 Honey, 1990) finding is replicable, Group CT’s responding to T should be of greater magnitude than Group T’s.

Top: Experimental design of Experiment 1. C = 10 Hz clicker, T = 2-kHz tone, + = 0.5-s, 1.0-mA shock. During preexposure, rats in Group CT received, separately and irregularly sequenced, nonreinforced preexposure to T and to C. Rats in Group T received a similar preexposure treatment except that stimulus C was omitted. The two groups of rats received identical treatments during conditioning and test. During conditioning, rats received C + pairings. During the test rats were presented with T. See text for complete details. Bottom: Mean instrumental response rates during T in the test of Experiment 1 expressed as responses per minute (RPM). Error bars indicate one standard error of their mean.

Method

Subjects and apparatus

Experimentally naïve, male, Lister hooded rats (Rattus norvegicus Charles River, UK) served as subjects. When experimentation was not occurring (see Procedure below), rats were held in an air-conditioned vivarium that was illuminated by fluorescent strip lights between 0700�. Temperatures were maintained between 20 and 23 ଌ. Rats were housed in acrylic cages. To provide rats with environmental enrichment, each cage contained a large cardboard cylinder, and all rats were pair housed. Cages contained fresh wood-chip bedding and tap water was always available. Rats received free access to food (Harlan Teklad, Bicester, UK) in the cages until one week before the experiment began. At that time, rats’ weights were recorded (mean: 247g range: 229�g) and food access was thenceforth restricted. Measured amounts of food were given once daily to reduce gradually rats’ weights to between 80% and 90% of their baseline weight. To promote healthy growth increase during the experiment, rats’ target weight was increased each week. The rate of that increase was based on the mean weekly weight change of a separate group of rats that had been allowed unrestricted access to food and water in our vivarium. Sixteen rats began the experiment but due to a failure of the lever in one Skinner box, it was necessary to exclude one rat from each group, (i.e., ns = 7).

Eight identically specified Skinner boxes (MED Associates, St Albans, VT) were used (30.0 cm 24.0 cm × 20.5 cm high), which were normally not illuminated. Each was individually housed in a sound- and light-attenuating shell. The ceiling and 30.0-cm Skinner box walls (one of which served as a door) were constructed from clear polycarbonate. The 24.0-cm walls were constructed from metal plates. One wall was equipped with a recessed tray to which 45-mg food pellets (Noyes, Lancaster, NH) could be delivered. An infrared beam was sent from one lateral side of the food tray and received on another. Beam interruption could be recorded as a response (henceforth, food-tray activity). A lever was located to the left of the food tray, depression of which actuated a switch that could also be used to record responding (henceforth, lever pressing). The lever could be retracted into the wall to prevent lever pressing. Two lamps, whose 2.5-cm diameter, circular covers were composed of opaque plastic, were located symmetrically adjacent to the food tray (10.5 cm from the floor and 16.0 cm apart, center-to-center). A third lamp was located on the opposite metal wall, centrally and 17.5 cm above the floor. The lamp was shrouded in a metal hood that could direct light toward the ceiling. None of the lamps were operated in any of the experiments reported here.

A heavy-duty relay, located on the outer side of the wall, could be operated at 10 Hz to produce an 80-dB (re. Scale A) train of clicks (henceforth, C). A loud speaker, located on the wall opposite the food tray, could be used to present a 2-kHz and 㲅-dB pure tone (henceforth, T). Background noise (principally provided by an exhaust fan located in the shell) was 65 dB. C and T were of 30-s duration.

The floor was constructed from 19, 4.8-mm diameter, stainless steel rods that ran parallel to the metal walls. Rods were spaced 1.6 cm apart, center-to-center. The floor could be electrified by a scrambled 0.5-s, 1.0-mA current (MED Associates, St Albans, VT, ENV-414SA) to produce a footshock. Experimental events were controlled and recorded with a Microsoft Windows-based personal computer that used the MED PC programming language. All apparatus was held in a quiet laboratory illuminated by ceiling-mounted fluorescent lamps.

Procedure

The procedure comprised three main stages: preexposure, conditioning, and test (see Figure 1 ). The treatment between groups differed only during preexposure.

Baseline training

Lever pressing was established to assess the fear responding (suppression of responding) during the test. Initially the lever was retracted and rats were given response-independent food pellets according to a 60-s, fixed-interval schedule. On the following session, the lever was extended into the box and rats could earn pellets according to variable-interval (VI) schedules. By the end of Baseline Training, rats’ lever pressing was reinforced according to a VI-60 schedule but richer schedules were used earlier in training. The lever pressing VI-60 schedule was operational throughout the remainder of the experiment. Rats received three 1-hr sessions of VI-60 Baseline Training sessions before progression to the preexposure stage.

Preexposure

Rats were divided into two groups, Group CT and Group T that were matched according to their response rates from Baseline Training. During each of six sessions Group CT was exposed to C and T each eight times. On the 1st, 4th and 5th sessions the sequence was T C C T T C C T T C C T T C C T on the other three sessions the sequence was C T T C C T T C C T T C C T T C. Group T’s treatment differed from Group CT’s only in that C was deleted. Group CT and Group T were run on separate sessions to prevent Group T inadvertently hearing C. On half the preexposure days, Group CT was run before Group T. The session duration was around 80 min. Intertrial intervals (ITIs) varied around means of 280 s and 560 s for, respectively, Group CT and Group T.

Conditioning

Conditioning was intended to establish a response (suppression of lever-press responding) to C. Two 1-hr sessions were given during the conditioning stage. In each, C was presented twice, coterminally with the shock. Trials began 570 s and 2370 s from the session’s beginning. A session was subsequently given to allow responding to recover food pellets were earned on the VI-60 schedule but no other stimuli were scheduled to occur.

The test stage was intended to examine differences in the (generalized) responding exhibited to T by Group T and Group CT. T was presented three times in a single session. The intertribal interval (ITI) varied around a mean of 280 s.

Data treatment

A variety of appropriate parametric analyses were used for null-hypothesis testing. Tests evaluated two-tailed hypotheses and α = .050. A Bayesian analysis supplemented the interpretation of a key null result (JASP (Version 0.7.5.5), Amsterdam, the Netherlands). Partial eta squared (ηp 2 ) was used to represent main effect and interaction effect sizes. Standardized 90% confidence intervals for ηp 2 were computed using the methods described by Kelley (2007).

Results and Discussion

Baseline training proceeded successfully. Responding during the first four trials of preexposure is summarized in Table 1 . The introduction of C to Group CT during preexposure resulted in some transitory suppression. Analysis of variance (ANOVA) yielded a significant trial main effect, F(3, 18) = 10.3 p < .001 ηp 2 > .631, 90% CI [.29, .72]. For both groups, the introduction of T during preexposure resulted in a similar disruption of responding. ANOVA yielded a significant trial main effect, F(3, 36) = 3.4 p < .030 ηp 2 > .219, 90% CI [.01, .35], but no group main effect nor Group x Trial interaction, both Fs < 1. A notable implication of this evidence of unconditioned suppression, and its habituation, is that it may modify the conditioned suppression seen during the subsequent conditioning and test stages.

Table 1

Trial/block
CT
GroupStatistic12341234
Note. The leftmost and rightmost quartets of columns summarize responding to the clicker (C) and to the tone (T) respectively. An em dash indicates that a group did not receive preexposure to either stimulus.
Experiment 1
CTM8.015.111.122.66.010.99.711.1
T 4.68.66.911.4
CTSEM2.02.92.22.22.12.41.71.9
T 1.42.22.32.3
Experiment 2
CTM10.826.329.325.05.010.820.320.8
T 4.012.330.521.3
C 20.811.535.823.0
0
CTSEM3.53.95.03.31.32.43.42.4
T 1.42.56.53.6
C 4.82.95.33.4
0
Experiment 3
CT 420M2.38.310.312.37.512.311.310.0
CT 280 3.011.815.017.811.818.513.516.3
CT 140 .57.513.513.86.315.011.312.5
0
T 6.08.814.313.0
CT 420SEM1.51.81.51.62.32.11.41.8
CT 280 1.82.82.32.02.31.71.62.3
CT 140 .32.51.61.62.52.62.11.3
0
T 1.92.02.01.5

Responding to C during its four conditioning pairings with the shock was almost completely suppressed by the end of that stage but, earlier in that stage, suppression to C was less marked in Group CT (mean rpm rates: 22, 23, 4, 2 SEMs: 2.6, 1.8, 1.2, 0.9) than in Group T (mean rpm rates: 14, 1, 1, 0 SEMs: 2.6, 1.8, 1.2, 0.9). ANOVA yielded main effects of both trial, F(3, 36) = 42.3 p < .001 ηp 2 > .779, 90% CI [.64, .83], and group, F(1, 12) = 47.3 p < .001 ηp 2 > .798, 90% CI [.53, .87], and an interaction between those variables, F(3, 36) = 13.6 p < .001 ηp 2 > .530, 90% CI [.29, .63]. Between-groups simple main effect (SME) analysis, which used the common error-term, yielded reliable group differences at Trials 1 and 2, smaller F(1, 48) = 11.3 p < .010, but at neither Trial 3 nor Trial 4, larger F(1, 48) = 2.3 p > .050. The pattern of results is most simply understood as reflecting Group T’s initial unconditioned suppression to C, like that seen during preexposure to C by Group CT, and its gradual replacement by conditioned suppression. For Group CT, preexposure to C allowed unconditioned suppression to habituate and its changes reflect only the acquisition of conditioned suppression.

The data of principle interest, those of the test of T, are summarized in Figure 1 . Suppression was relatively great on the first trial in both groups but decreased over the course of testing. However, the level of suppression throughout the test was more marked in Group CT than in Group T. That impression was confirmed using ANOVA that yielded main effects of group, F(1, 12) = 5.9 p < .033 ηp 2 > .328, 90% CI [.02, .56], trial, F(2, 24) = 9.4 p < .001 ηp 2 > .439, 90% CI [.15, .58], but no interaction between those factors, F(2, 24) = 1.4 p > .273. An estimate of baseline response rates was made using the response rates during the 30-s period immediately preceding each of the tone presentation and these data are summarized in Table 2 . ANOVA on these data, having the same format as that of the test data, yielded a main effect of trial, F(2, 24) = 4.5 p < .023 ηp 2 > .272, 90% CI [.02, .44] but no main effect of group nor Group x Trial interaction, Fs < 1.

Table 2

GroupStatisticTrial/Block
1234
Note.𠀼 = clicker T = tone.
Experiment 1
CTM8.38.03.1
T 8.914.04.9
CTSEM3.43.41.2
T 2.23.81.3
Experiment 2
CTM49.132.360.634.8
T 67.047.859.539.8
C 40.838.853.336.9
0 50.432.853.032.6
CTSEM4.93.36.83.1
T 7.05.98.14.2
C 7.04.27.04.7
0 9.52.54.34.9
Experiment 3
CT 420M11.09.510.88.0
CT 280 9.813.09.812.0
CT 140 11.813.011.310.3
0 12.013.011.58.3
T 9.59.815.512.3
CT 420SEM1.80.91.21.5
CT 280 2.22.62.52.3
CT 140 2.73.43.42.5
0 3.42.72.42.5
T 1.71.82.81.3

The results of Experiment 1 provide a replication of Robinson et al.’s (2010) demonstration of familiarity-based generalization in surgically naive rats. This procedure parallels findings in conditioned taste aversion (Best & Batson, 1977) and appetitive conditioning (Honey, 1990). Group CT’s preexposure treatment involved presentation of both C and T and was designed to ensure those stimuli were both encoded as familiar. In contrast, Group T’s preexposure treatment was designed to make C’s and T’s coding incongruent that is, with T familiar and C novel. Based on standard assumptions, C and T will have a set of common representational elements that govern stimulus generalization to the same extent in both groups. The fact that Group CT’s level of suppression was greater than Group T’s suggests that, if standard assumptions are correct, some additional process was occurring to enhance generalization from C to T in Group CT—that process could be the result of generalization based upon novelty or familiarity coding. However, several other factors that could affect test performance to T will be considered before accepting that interpretation. First, unconditioned suppression to T was detected during preexposure, which could have certainly have affected test performance to T (i.e., the generalized fear response could be contaminated by unconditioned suppression see, e.g., Robinson, Sanderson, Aggleton, & Jenkins, 2009 Jones, Whitt, & Robinson, 2012). But because both groups received preexposure to T, and because the course of habituation of unconditioned suppression was similar, this seems unlikely to generate the crucial group difference. One might anticipate that Group CT’s habituation of unconditioned suppression to C might generalize to T, being mediated by a subset (x) of shared representational elements, and reduce suppression relative to Group T. If such a process did occur, we did not detect it during preexposure and, of course, that process would have worked against—not in favor of—the obtained group difference. Neither account based on unconditioned suppression appears to provide a suitable account of the results.

Second, any account based upon latent inhibition (e.g., Lubow & Moore, 1959), either of C or of the subset of features (x) shared by C and T, appears similarly inadequate in explaining the results. Group CT’s preexposure to C might reduce C’s capacity to govern responding in that group but that would act against the observed group difference. Here, the set of x features that mediate generalization may lose more associability in Group CT than in Group T𠅍uring preexposure x was presented twice as often in Group CT than in Group T (cf. Bennett, Wills, Wells, & Mackintosh, 1994 McLaren & Mackintosh, 2002). Thus, like the habituation account, this latent inhibition account fails to produce a realistic alternative account of the main findings because it predicts the opposite result to our findings.


Conclusion

Our results demonstrate the importance of contingency awareness for contextual fear conditioning. There were striking differences between subjects classified as aware and those classified as unaware. Furthermore, these differences not only showed that contingency awareness is necessary for contextual conditioning, but also shed light on potential mechanisms for contingency learning. Hence, our study contributes to the current debate on the necessity of contingency awareness during associative learning and extends it to contextual conditioning paradigms.


Watch the video: Classical conditioning: Neutral, conditioned, and unconditioned stimuli and responses. Khan Academy (January 2022).