A theoretical analysis of the PAN ambiguous-cue problem

The PAN ambiguous-cue problem consists of three stimuli: P, the positive (consistently rewarded) cue; N, the negative (consistently nonrewarded) cue; and A, the ambiguous cue which is negative (nonrewarded) when paired with P, but positive (rewarded) when paired with N. This paper demonstrates how the finding of superior performance on the NA trials as compared to the PA trials (with stereometric objects) can be rigorously derived from a recent extension of Hull-Spence discrimination learning theory, the Stimulus Interaction Hypothesis. It is also shown how this theory can account for the converse outcome of better performance on PA than on NA trials when planometric plaques are used as stimuli. Finally, alternative explanations of the findings are described and evaluated.     

An analysis of the solution of PAN ambiguous-cue problems by rhesus monkeys

Twenty-four monkeys were given 2-choice discrimination problems composed of three planometric plaque stimuli: P, the rewarded stimulus; N, the nonrewarded stimulus; and A, the ambiguous stimulus which was negative when paired with P, but positive when paired with N. When both pair of stimuli, PA and NA, were presented within a given session S was forced either to approach or to avoid the A plaque depending upon the stimulus with which it was paired. The results corroborated previous reports for plaque stimuli by showing PA performance to be superior to NA. The data also revealed that when plaque stimuli with distinctive cues were employed, NA performance exceeded PA as previously reported for stereometric object stimuli. Pretraining Ss with plaque stimuli possessing distinctive cues, then switching to plaques with less distinctive cues, also resulted in superior NA performance. These findings are discussed in the context of an interference-cue theory.     

Complex Visual Learning by Rats

Rats’ learning about visual patterns was studied in a computerized Y-maze where wide-angle stimuli were viewed from a distance. Many patterns were available; some were spatially complex and others were more homogeneous figures. Experiment 1 used a discrimination paradigm in which a single S⁺could be paired with any one of 15 different S⁻s. Hooded rats learned successively six such discrimination problems. Their learning rate improved across the series, and comparison with controls suggested that the learning-set did not merely reflect simple habituation. Experiments 2 and 3 employed Dark Agouti rats, again learning many discrimination problems. Each problem comprised a constant stimulus which was paired with stimuli which varied in trial-unique fashion. The version in which the constant stimulus was nonrewarded (S⁻) and the varying stimuli rewarded was performed better than the converse, constant S⁺and varying nonrewarded, reflecting rats’ preference for relatively unfamiliar stimuli. In the constant S⁻task, rats showed substantial within-problem learning when three novel problems were given per day for 20 trials each. Rats are capable of rapid learning about complex visual displays if we engage their natural dispositions to use vision for distal stimuli and to approach relatively unfamiliar cues.     

Control of instrumental behavior by deprivation stimuli

In Experiment 1, rats were given one trial per day in a straight alley under food deprivation on half of the trials and under water deprivation on the other half. Wet mash was available in the goal box under food deprivation for Group H and under water deprivation for Group T, the other deprivation being nonrewarded for each group. After 15--18 trials both groups ran significantly faster on their rewarded than on their nonrewarded deprivation days. A third group showed that random variation of alley color retarded formation of the discrimination. A fourth group was run in a conditional discrimination in which under food deprivation wet mash was available in a black alley, nonreward in a white alley, and vice versa under water deprivation. This group took 114 trials to begin running significantly faster in their rewarded than in their nonrewarded alley under each deprivation. In Experiment 2, it was shown that prior learning about deprivation cues "blocks" learning about alley color when alley color is subsequently presented in compound with the deprivation cue but that when both alley color and deprivation cues are relevant from the start of training, the rat learns about both cues. It is suggested that previous studies have underestimated the importance of deprivation cues by using conditional discrimination designs, choice measures rather than speeds, and parameters that are not optimal for discrimination learning.     

Visuospatial attention and redundancy gain

Two experiments investigated the effect of visuospatial attention on redundancy gain in simple reaction time tasks. In each trial participants were given a central arrow cue indicating where a stimulus would most likely be presented (i.e., upper or lower half of the display in Experiment 1; left or right half of the display in Experiment 2). Then, a single stimulus or two redundant stimuli could be presented in either expected or unexpected locations. Replicating previous findings, responses were faster when stimuli appeared in expected rather than unexpected locations, and they were also faster when two redundant stimuli were presented than when only one was. Critically, redundancy gain was statistically equivalent for stimuli in expected and unexpected locations, suggesting that the effect of redundancy gain arises after the perceptual processes influenced by the allocation of visuospatial attention.

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Immediate reinforcement in delayed reward learning in pigeons

Pigeons were trained on simultaneous red-green discrimination procedures with delayed reward and sequences of stimuli during the delay. In Experiment 1, three stimuli appeared during the 60-second intervals between the correct responses and reward, and the incorrect responses and nonreward. The stimulus that immediately followed a correct response also preceded nonreward, and the stimulus that followed an incorrect response preceded reward. These stimuli were 10 or .33 second in duration for different groups. Stimuli during the remainder of the delay interval differed following correct and incorrect responses. Group 10 initially persisted in the nonrewarded choice, but shifted to a preponderance of rewarded responses after further training. Group .33 rapidly acquired the correct response. Similar results were obtained in Experiment 2 where delay intervals consisted of opposite sequences of two stimuli of equal duration and total delays were 6, 20, or 60 seconds. Early in training, generalization of differential conditioned-reinforcing properties from the conditions preceding reward and nonreward to postchoice conditions had a greater effect relative to backchaining than it did later. It was concluded that delayed-reward learning is best analyzed in terms of the conditioned-reinforcing value of the patterns of cues that follow immediately after rewarded and nonrewarded responses.     

Does test-enhanced learning transfer for triple associates?

Test-enhanced learning and transfer for triple-associate word stimuli was assessed in three experiments. In each experiment, training and final-test trials involved the presentation of two words per triple associate (triplet), with the third word having to be retrieved. In agreement with the prior literature on different stimuli, training through testing with feedback yielded markedly better final-test performance than did restudy. However, in contrast to the positive transfer reported for paired associate stimuli, minimal or no positive transfer was observed, relative to a restudy control, from a trained cue combination (e.g., A, B, ?) to other cue combinations from the same triplet that required a different response (e.g., B, C, ?). That result also held when two unique cue combinations per triplet were tested during training, and for triplets with low and high average associative strengths. Supplementary analyses provided insight into the overall transfer effect: An incorrect response during training appears to yield positive transfer relative to restudy, whereas a correct response appears to yield no, or even negative, transfer. Cross-experiment analyses indicated that test-enhanced learning is not diminished when two or three cue combinations are presented during training. Thus, even though learning through testing is highly specific, testing on all possible stimulus–response combinations remains the most efficient strategy for the learning of triple associates.     

Do top and bottom contribute to object perception more than left and right?

To examine whether the top–bottom axis has an inherent advantage in object perception over the left–right one, three experiments were conducted. In all of them, on each trial one of two alternative stimuli, identical in shape but opposite in direction (viz, related by reflection), was presented. Both reflection about the vertical axis and reflection about the horizontal axis were applied, in different blocks. In Experiment 1, objects with an orientation-free definition (arrows, incomplete squares) were presented. Subjects were to respond when the stimulus pointed in a specific direction, and to refrain from responding when it was reflected, namely pointed in the opposite direction. Axis of reflection (vertical, horizontal) was varied between blocks. In Experiment 2, the object was a Hebrew character asymmetric on both axes, presented either in its normal appearance or reflected. Subjects were to respond only when the stimulus was normal. Both axis of reflection (vertical, horizontal) and orientation angle (upright, tilted by 90°) were varied between blocks. In Experiment 3, stimuli were the same as in Experiment 2, but the task explicitly asked for a binary reflection judgment (normal vs. reflected). No sign for the presence of an axis effect was observed in any of those experiments, which seems incompatible with the hypothesis of vertical advantage in object perception. It is suggested that most vertical advantage observed before is due to extra-perceptual processing.

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Response-specifying cue for action interferes with perception of feature-sharing stimuli

Perceiving a visual stimulus is more difficult when a to-be-executed action is compatible with that stimulus, which is known as blindness to response-compatible stimuli. The present study explored how the factors constituting the action event (i.e., response-specifying cue, response intention, and response feature) affect the occurrence of this blindness effect. The response-specifying cue varied along the horizontal and vertical dimensions, while the response buttons were arranged diagonally. Participants responded based on one dimension randomly determined in a trial-by-trial manner. The response intention varied along a single dimension, whereas the response location and the response-specifying cue varied within both vertical and horizontal dimensions simultaneously. Moreover, the compatibility between the visual stimulus and the response location and the compatibility between that stimulus and the response-specifying cue was separately determined. The blindness effect emerged exclusively based on the feature correspondence between the response-specifying cue of the action task and the visual target of the perceptual task. The size of this stimulus–stimulus (S–S) blindness effect did not differ significantly across conditions, showing no effect of response intention and response location. This finding emphasizes the effect of stimulus factors, rather than response factors, of the action event as a source of the blindness to response-compatible stimuli.     

Prior experience with negative spectral correlations promotes information integration during auditory category learning

Complex sounds vary along a number of acoustic dimensions. These dimensions may exhibit correlations that are familiar to listeners due to their frequent occurrence in natural sounds—namely, speech. However, the precise mechanisms that enable the integration of these dimensions are not well understood. In this study, we examined the categorization of novel auditory stimuli that differed in the correlations of their acoustic dimensions, using decision bound theory. Decision bound theory assumes that stimuli are categorized on the basis of either a single dimension (rule based) or the combination of more than one dimension (information integration) and provides tools for assessing successful integration across multiple acoustic dimensions. In two experiments, we manipulated the stimulus distributions such that in Experiment 1, optimal categorization could be accomplished by either a rule-based or an information integration strategy, while in Experiment 2, optimal categorization was possible only by using an information integration strategy. In both experiments, the pattern of results demonstrated that unidimensional strategies were strongly preferred. Listeners focused on the acoustic dimension most closely related to pitch, suggesting that pitch-based categorization was given preference over timbre-based categorization. Importantly, in Experiment 2, listeners also relied on a two-dimensional information integration strategy, if there was immediate feedback. Furthermore, this strategy was used more often for distributions defined by a negative spectral correlation between stimulus dimensions, as compared with distributions with a positive correlation. These results suggest that prior experience with such correlations might shape short-term auditory category learning.     

Context effects in evaluative conditioning of implicit evaluations

Propositional models of evaluative conditioning postulate that the impact of stimulus pairings on liking should depend not on the pairings themselves but on what the pairings imply about the relation between stimuli. Hence, context manipulations that change the implications of stimulus pairings should moderate evaluative conditioning. We manipulated context by varying the way in which context cues were paired with affective outcomes while keeping the pairings between target cues and affective outcomes constant. All participants saw one target cue compound that was followed by a positive outcome (XF+) and another target cue compound that was followed by a negative outcome (YG?). In condition Same, each context cue was consistently paired with a positive or negative outcome, regardless of whether it was presented alone or in compound with another cue (A+, B+, AB+; C?, D?, CD?). In condition Opposite, however, a context cue was paired with a certain outcome when presented alone and with an outcome of the opposite valence when presented in a compound with another cue (A+, B+, AB?; C?, D?, CD+). Employing several implicit measures, we assessed the implicit evaluations of the target cues X and Y. In all three studies, the outcome of the measurement procedure differed between conditions. In condition Same, the positively paired cue X was evaluated more positively than the negatively paired cue Y. In condition Opposite, however, this preference was not present. This pattern of results suggests that EC is determined not only by the objective pairings but also by the context in which these pairings occur. Implications for models of evaluative conditioning are discussed.     

The glass is not yet half empty: agitation but not <Emphasis Type="Italic">Varroa</Emphasis> treatment causes cognitive bias in honey bees

Honey bees (Apis mellifera) are prone to judge an ambiguous stimulus negatively if they had been agitated through shaking which simulates a predator attack. Such a cognitive bias has been suggested to reflect an internal emotional state analogous to humans who judge more pessimistically when they do not feel well. In order to test cognitive bias experimentally, an animal is conditioned to respond to two different stimuli, where one is punished while the other is rewarded. Subsequently a third, ambiguous stimulus is presented and it is measured whether the subject responds as if it expects a reward or a punishment. Generally, it is assumed that negative experiences lower future expectations, rendering the animals more pessimistic. Here we tested whether a most likely negatively experienced formic acid treatment against the parasitic mite Varroa destructor also affects future expectations of honey bees. We applied an olfactory learning paradigm (i.e., conditioned proboscis extension response) using two odorants and blends of these odorants as the ambiguous stimuli. Unlike agitating honey bees, exposure to formic acid did not significantly change the response to the ambiguous stimuli in comparison with untreated bees. Overall evidence suggests that the commonest treatment against one of the most harmful bee pests has no detrimental effects on cognitive bias in honey bees.     

Multiple attentional control settings at distinct locations without the confounding of repetition priming

An attentional control setting (ACS), which is based on the task goal, induces involuntary attentional capture by a stimulus possessing a target-defining feature. It is unclear whether ACSs are maintained for multiple targets defined as conjunctions of a color and location. In the present study we examined the possibility of local ACSs for dual targets defined as combinations of color and location, using different paradigms: visual search in Experiment 1, and spatial cueing in Experiment 2. In Experiment 1, a distractor captured attention only when its features matched the ACSs. Likewise, in Experiment 2, a significant attentional capture effect was found only with a matching cue, whose color and location were in line with the conjunction of the target definition. Importantly, the identical pattern of attentional capture was also obtained for a neutral-color target, which was unlikely to be primed by any color of the cue. Thus, these findings imply that the attentional bias depending on the match between the cue and target did not result from cue–target repetition priming. The present study highlights that top-down attentional control can be set flexibly to accomplish a complex task goal efficiently.     

I don't like it because it eats sprouts: conditioning preferences in children

Although little is known about how preferences develop in childhood, work in adults suggests that evaluative responses to stimuli can be acquired through classical conditioning. In two experiments children were exposed to novel cartoon characters, that were either consistently paired with a picture of a disliked food (Brussels sprouts) or a liked food (ice cream). Relative preferences for these stimuli (and others) were measured before and after these paired presentations (Experiment 1): preferences for the cartoon character paired with Brussels sprouts decreased, whereas preferences for the character paired with ice cream increased. These preferences persisted after 10 un-reinforced trials. Experiment 2 replicated this finding using affective priming as an index of preference for the cartoon characters. These findings demonstrate that preferences to novel stimuli can be conditioned in children and result from associations formed between the stimulus and a stimulus possessing positive or negative valence.     

Exposure effects and associative learning

The contributions of initial stimulus affect and of associative learning to the effects of repeated stimulus exposures were examined in two experiments. Stimuli that were initially positive and stimuli that were initially negative were presented for different number of times, and subjects rated these stimuli afterward on a number of affective dimensions. In all cases, except when negative affect was associatively paired with every stimulus exposure, affective responses became increasingly more positive with increasing exposures. The results were taken to indicate that the exposure effect can overcome an initially negative stimulus affect when the conditions of the mere exposure hypothesis are satisfied. Initial stimulus affect and associative learning of affect were shown to be independent factors, the first influencing the intercept of the exposure function, the second its slope.     

Sequential effects on discrimination reversal

In Experiment 1 the sequence of trials to the positive (S+) and negative (S?) discriminanda was varied between groups during acquisition and reversal of a successive brightness discrimination. In Experiments 2 and 3, groups received different reward sequences in Phase 1 within S+. In general, groups given transitions from nonrewarded trials to rewarded trials (N-R transitions) in Phase 1 learned both the original discrimination and its reversal more slowly than groups given schedules devoid of N-R transitions. The results were discussed in relation to previously reported effects of partial reinforcement on acquisition and reversal of a discrimination and the role of sequential variables and internal, reward-produced cues in discrimination learning, reversal learning, and nonreversal shifts.     

Modality-specific interference with overt mediation by pigeons in a delayed discrimination task

Pigeons were trained on a delayed discrimination task in which they were rewarded for pecking a white terminal stimulus (TS) presented 5 sec after a green initial stimulus (IS) and for not pecking the white TS when it followed a red IS. Each bird bridged the memory interval (MI) with overt mediational behaviors. Nevertheless, sustained retroactive interference (RI) effects were produced by houselight illumination (Experiments 1 and 3), and mild shock pulses (Experiment 5) but not white noise (Experiment 2) presented during the MI. Although the magnitude of the light-induced RI effect was proportional to the duration of houselight illumination (Experiment 4), the beginning-end effect described by W. A. Roberts and D. S. Grant (Journal of Experimental Psychology: Animal Behavior Processes, 1978, 4, 219–236) was not observed. These results not only attest to the between-task robustness of both light-induced RI and modality-specific effects with pigeons, but also support the hypothesis that RI effects result from the disruption of mediational activities possibly analogous to rehearsal. The results further demonstrate that an event interpolated within the MI need not be unexpected or novel to produce RI. Furthermore, the interpolated event can produce modality-specific RI effects even though it effects a different sense than do the IS and TS.     

The effect of pretraining and feedback on the reasoning of young children

Three experiments are reported in which kindergarten and first-grade children were given one-trial multidimensional reasoning tasks that were modifications of those used by T. C. Toppino (1980, Journal of Experimental Child Psychology, 30, 496–512). In the first two experiments, the nature of the stimulus compounds (partitioned or unitary) was varied in a series of tasks of increasing complexity. First-grade children (Experiment 1) and kindergarten children (Experiment 2) performed extremely well on all of the tasks presented. Experiment 3 was designed to identify factors that contribute to these high levels of performance, relative to those obtained under the conditions used by Toppino (1980). The results indicated that a combination of feedback information and preliminary experience with simple forms of the tasks are sufficient to produce the high performance levels, and that the verbal labeling of stimulus components is not an essential constituent of the training.     

Automatic stimulus‐goal comparisons: Support from motivational affective priming studies

In three studies, we found that responses to positive targets were facilitated when the preceding prime was an exemplar belonging to the semantic category (i.e., animal or profession) that was rewarded on that particular trial, whereas responses to negative targets were facilitated when the prime belonged to the nonrewarded category. These findings indicate that the match between an actual (the prime) and a desired state (the rewarded category) can be determined automatically at the time of stimulus presentation, as is assumed in several appraisal theories of emotion (e.g., Frijda, 1986, 1993; Lazarus, 1991; Scherer, 1993).     

Generalization of conditioned fear along a dimension of increasing fear intensity

The present study investigated the extent to which fear generalization in humans is determined by the amount of fear intensity in nonconditioned stimuli relative to a perceptually similar conditioned stimulus. Stimuli consisted of graded emotionally expressive faces of the same identity morphed between neutral and fearful endpoints. Two experimental groups underwent discriminative fear conditioning between a face stimulus of 55% fear intensity (conditioned stimulus, CS+), reinforced with an electric shock, and a second stimulus that was unreinforced (CS−). In Experiment 1 the CS− was a relatively neutral face stimulus, while in Experiment 2 the CS− was the most fear-intense stimulus. Before and following fear conditioning, skin conductance responses (SCR) were recorded to different morph values along the neutral-to-fear dimension. Both experimental groups showed gradients of generalization following fear conditioning that increased with the fear intensity of the stimulus. In Experiment 1 a peak shift in SCRs extended to the most fear-intense stimulus. In contrast, generalization to the most fear-intense stimulus was reduced in Experiment 2, suggesting that discriminative fear learning procedures can attenuate fear generalization. Together, the findings indicate that fear generalization is broadly tuned and sensitive to the amount of fear intensity in nonconditioned stimuli, but that fear generalization can come under stimulus control. These results reveal a novel form of fear generalization in humans that is not merely based on physical similarity to a conditioned exemplar, and may have implications for understanding generalization processes in anxiety disorders characterized by heightened sensitivity to nonthreatening stimuli.Fear generalization occurs when a fear response acquired to a particular stimulus transfers to another stimulus. Generalization is often an adaptive function that allows an organism to rapidly respond to novel stimuli that are related in some way to a previously learned stimulus. Fear generalization, however, can be maladaptive when nonthreatening stimuli are inappropriately treated as harmful, based on similarity to a known threat. For example, an individual may acquire fear of all dogs after an aversive experience with a single vicious dog. In this case, recognizing that a novel animal is related to a feared (or fear-conditioned) animal is made possible in part by shared physical features to the fear exemplar, such as four legs and a tail. On the other hand, fear generalization may be selective for those features that are associated with natural categories of threat; a harmless dog may not pose a threat, but possesses naturally threatening features common to other threatening animals, such as sharp teeth and claws. Moreover, the degree to which an individual fearful of dogs responds with fear may be related to either the physical similarity to the originally feared animal (e.g., from a threatening black dog to another black dog), or the intensity of those threatening features relative to the originally feared animal (e.g., sharp teeth from one animal to sharp teeth of another animal). Therefore, fear generalization based on perceptual information may occur via two routes—similarity to a learned fear exemplar along nonthreatening physical dimensions or along dimensions of fear relevance. Given that fear generalization often emerges as a consequence of conditioning or observational learning, it is important to determine which characteristics of novel stimuli facilitate fear generalization and the extent to which generalization processes can be controlled.Early explanations of stimulus generalization emphasized that an organism''s ability to generalize to nonconditioned stimuli is related to both the similarity and discriminability to a previously conditioned stimulus (CS) (Hull 1943; Lashley and Wade 1946). While Lashley and Wade (1946) argued that generalization was simply a failure of discriminating between a nonconditioned stimulus (CS−) and the reinforced CS (CS+), contemporary views contend that generalization enables learning to extend to stimuli that are readily perceptually distinguished from the CS (Pearce 1987; Shepard 1987; McLaren and Mackintosh 2002). This latter view has been supported by empirical studies of stimulus generalization in laboratory animals (Guttman and Kalish 1956; Honig and Urcuioli 1981). In these studies, animals were reinforced for responding to a CS of a specific physical quality such as color, and then tested with several different values along the same stimulus dimension as the CS (e.g., at various wavelengths along the color spectrum). Orderly gradients of responses are often reported that peak at or near the reinforced value and decrease as a function of physical similarity to the CS along the stimulus dimension (Honig and Urcuioli 1981). Further generalization was shown to extend from the CS+ to discriminable nonconditioned stimuli, suggesting that generalization is not bound to the organism''s ability to discriminate stimuli (Guttman and Kalish 1956, 1958; Shepard 1987).Interestingly, when animals learn to distinguish between a CS+ and a CS−, the peak of behavioral responses often shift to a new value along the dimension that is further away from the CS− (Hanson 1959). For instance, when being trained to discriminate a green CS+ and an orange CS−, pigeons will key peck more to a greenish-blue color than the actual CS+ hue. Intradimensional generalization of this sort is reduced when animals are trained to discriminate between two or more stimulus values that are relatively close during conditioning (e.g., discriminating a green-yellow CS+ from a green-blue CS−), suggesting that the extent of generalization can come under stimulus control through reinforcement learning (Jenkins and Harrison 1962). Spence (1937) described the transposition of response magnitude as an effect of interacting gradients of excitation and inhibition formed around the CS+ and CS−, respectively, which summate to shift responses to values further from the inhibitory CS− gradient. In all, early theoretical and empirical treatments of stimulus generalization in nonhuman animals revealed that behavior transfers to stimuli that are physically similar, but can be discriminated from a CS, and that differential reinforcement training can both sharpen the stimulus gradient and shift the peak of responses to a nonreinforced value.Although this rich literature has revealed principles of generalization in nonhuman animals, few studies of fear generalization have been conducted in humans (for review, see Honig and Urcuioli 1981; Ghirlanda and Enquist 2003). Moreover, the existing human studies have yet to consider the second route through which fear responses may generalize—via gradients of fear relevance. While a wide range of neutral stimuli, such as tones or geometric figures, can acquire fear relevance through conditioning processes, other stimuli, such as threatening faces or spiders, are biologically prepared to be fear relevant (Lanzetta and Orr 1980; Dimberg and Öhman 1996; Whalen et al. 1998; Öhman and Mineka 2001). Compared with fear-irrelevant CSs, biologically prepared stimuli capture attention (Öhman et al. 2001), are conditioned without awareness (Öhman et al. 1995; Öhman and Soares 1998), increase brain activity in visual and emotional processing regions (Sabatinelli et al. 2005), and become more resistant to extinction when paired with an aversive unconditioned stimulus (US) (Öhman et al. 1975). Although the qualitative nature of the CS influences acquisition and expression of conditioned fear, it is unknown how generalization proceeds along a gradient of natural threat. For instance, human studies to date have all tested variations of a CS along physically neutral stimulus dimensions, such as tone frequency (Hovland 1937), geometric shape (Vervliet et al. 2006), and physical size (Lissek et al. 2008). These investigations implicitly assume that the generalization gradient is independent of the conditioned value (equipotentiality principle). In other words, since the stimuli are all equally neutral prior to fear learning, fear generalization operates solely as a function of similarity along the reinforced physical dimension. However, since fear learning is predisposed toward fear-relevant stimuli, generalization may be selective to those shared features between a CS+ and CS− that are associated with natural categories of threat. Examining generalization using fear-relevant stimuli is thus important to gain better ecological validity and to develop a model system for studying maladaptive fear generalization in individuals who may express exaggerated fear responses to nonthreatening stimuli following a highly charged aversive experience (i.e., post-traumatic stress disorder or specific phobias).To address this issue, the present study examined generalization to fearful faces along an intradimensional gradient of fear intensity. A fearful face is considered a biologically prepared stimulus that recruits sensory systems automatically for rapid motor responses (Öhman and Mineka 2001), and detecting fearful faces may be evolutionarily selected as an adaptive response to social signals of impending danger (Lanzetta and Orr 1980; Dimberg and Öhman 1996). During conditioning, an ambiguous face containing 55% fear intensity (CS+) was paired with an electric shock US, while a relatively neutral face (11% fear intensity) was explicitly unreinforced (CS−) (Experiment 1). Skin conductance responses (SCR) were recorded as a dependent measure of fear conditioning. Before and following fear conditioning, SCRs were recorded in response to face morphs of the same actor expressing several values of increasing fear intensity (from 11% to 100%; see Fig. 1). A total of five values along the continuum were used: 11% fear/88% neutral, 33% fear/66% neutral, 55% fear/44% neutral, 77% fear/22% neutral, and 100% fear. For clarity, these stimuli are herein after labeled as S1, S2, S3, S4, and S5, respectively.Open in a separate windowFigure 1.Experimental design. (A) Pre-conditioning included six presentations of all five stimulus values without the US. (B) Fear conditioning involved discriminative fear learning between the S3, paired with the US (CS+), and either the unreinforced S1 (Experiment 1) or the unreinforced S5 (Experiment 2) (CS−). (C) The generalization test included nine presentations of all five stimuli (45 total), with three out of nine S3 trials reinforced with the US. Stimuli are not drawn to scale.Testing generalization along an intradimensional gradient of emotional expression intensity allows for an examination of the relative contributions of fear intensity and physical similarity on the magnitude of generalized fear responses. If fear generalization is determined purely by the perceptual overlap between the CS+ and other morph values, without regard to fear intensity, then we would expect a bell-shaped generalization function with the maximum SCR centered on the reinforced (intermediate) CS+ value (S3), less responding to the directly adjacent, but most perceptually similar values (S2 and S4), and the least amount of responding to the most distal and least perceptually similar morph values (S1 and S5). This finding would be in line with stimulus generalization reported along fear-irrelevant dimensions (Lissek et al. 2008) and in stimulus generalization studies using appetitive instrumental learning procedures (Guttman and Kalish 1956). If, however, fear generalization is biased toward nonconditioned stimuli of high fear intensity, then an asymmetric generalization function should result with maximal responding to the most fear-intense nonconditioned stimuli. This finding would suggest that fear generalization is selective to the degree of fear intensity in stimuli, similar to studies of physical intensity generalization gradients in nonhuman animals (Ghirlanda and Enquist 2003). We predicted that the latter effect would be observed, such that the magnitude of SCRs will disproportionately generalize to stimuli possessing a greater degree of fear intensity than the CS+ (Experiment 1). A secondary goal was to determine whether fear generalization to nonconditioned stimuli can be reduced through discriminative fear learning processes. Therefore, a second group of participants was run for whom the CS− was the 100% fearful face (Experiment 2). In this case, we predicted that discriminative fear conditioning between the CS+ (55% intensity) and the most fear-intense nonconditioned stimulus would sharpen the generalization gradient around the reinforced CS+ value, and that responses to the most fear-intense stimulus would decrease relative to Experiment 1. Moreover, this discriminative fear-learning process may provide evidence that fear generalization is influenced by associative learning processes and is not exclusively driven by selective sensitization to stimuli of high fear relevance (Lovibond et al. 1993). Finally, we were interested to discover whether generalization processes would yield subsequent false memory for the intensity of the CS+ in a post-experimental retrospective report. In sum, the present study has implications for understanding how fear generalization is related to the degree of fear intensity of a nonconditioned stimulus, the extent to which discrimination training efforts can thwart the generalization process, and how fear generalization affects stimulus recognition.