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.