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Fear generalization in humans: Impact of prior non-fearful experiences
Behaviour Research and Therapy 48 (2010) 1078e1084
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Fear generalization in humans: Impact of prior non-fearful experiences Bram Vervliet a, b, *, Merel Kindt a, Debora Vansteenwegen b, Dirk Hermans b a b
Department of Clinical Psychology, University of Amsterdam, Roetersstraat 15, 1018 WB, Amsterdam, The Netherlands Department of Psychology, University of Leuven, Belgium
a r t i c l e i n f o
a b s t r a c t
Article history: Received 15 December 2009 Received in revised form 23 June 2010 Accepted 8 July 2010
Fear generalization lies at the heart of many anxiety problems, and is therefore an important target for prevention and/or treatment. Here, we investigated whether fear generalization towards a specific stimulus can be weakened by prior non-fearful experiences with that stimulus. Using the standard human fear conditioning procedure, all participants received paired presentations of a geometric figure and an electric shock. This was followed by a test phase in which a similar but different figure was presented. Electrodermal responding and ratings of shock-expectancy measured the level of fear generalization towards this test stimulus. Crucially, half of the participants had been preexposed to that stimulus (without shock). The results show significantly less generalization in this group, suggesting that prior non-fearful experiences can protect against fear generalization. These results may inspire novel ways to prevent the development of clinical anxiety. Ó 2010 Published by Elsevier Ltd.
Keywords: Fear conditioning Latent inhibition Generalization Prevention Anxiety disorders
Introduction Prevention is better than cure, but little is known about effective prevention in the case of clinical anxiety. The conditioning model of anxiety has inspired one well-known technique e “latent inhibition” e that is aimed to reduce the rate of fear conditioning that can occur during a traumatic experience. This technique involves prior non-fearful experiences with the cues from the trauma context before the trauma has occurred. Animal conditioning research has shown that prior nonreinforced exposures to a to-be-conditioned stimulus delays the rate of fear conditioning with that stimulus, when it is later paired with an electric shock (“latent inhibition”, e.g., Lubow, 1973). However, it has proven cumbersome to replicate this finding in human experimental research; the phenomenon seems less robust and depends more on specific experimental parameters (Lubow, 1997; Lubow & Gerwitz, 1995; but see Vaitl & Lipp, 1997). Moreover, even animal research has shown that the latent inhibition effect is fragile: Changes in the perceptual features of the stimulus or the background context at the start of the conditioning phase seriously weaken the latent inhibition effect (Bouton, 1993; Lubow, 1973). Hence, the applicability of latent inhibition procedures is quite limited and probably only efficient in
* Corresponding author at: Department of Psychology, University of Leuven, Roetersstraat 15, 1018 WB, Amsterdam, The Netherlands. Tel.: þ31 20 525 67 68; fax: þ31 20 639 13 69. E-mail address: [email protected] (B. Vervliet). 0005-7967/$ e see front matter Ó 2010 Published by Elsevier Ltd. doi:10.1016/j.brat.2010.07.002
very stable contexts (e.g., for the prevention of dental phobia in children, Davey, 1989; Ten berge, Veerkamp, & Hoogstraten, 2002). The latent inhibition technique starts from the basic assumption that excessive fear learning is responsible for the development of clinical anxiety: By weakening the fear learning process, one reduces the chances of developing clinical anxiety. In itself, however, fear learning is a highly adaptive mechanism that can be crucial for survival. The conditioning process underlying the fear mechanism produces fear selectively to those cues that provide unique information about the occurrence of the threatening event (Rescorla & Wagner, 1972). The trauma context is inherently dangerous for the trauma victim, and the experience of fear (and the resulting avoidance) is therefore adaptive in that context. However, fear becomes irrational when it is overgeneralized to everyday contexts/stimuli that are intrinsically safe but share (some) similarity with the trauma context. In the case of posttraumatic stress disorder (PTSD), for example, patients often show an unbridled generalization of fear towards realistically nondangerous cues (see Feldner, Monson, & Friedman, 2007). This fear generalization is therefore an important target in some psychological treatments of PTSD (e.g., Ehlers & Clark, 2000). Hence, the transfer from normal to abnormal anxiety may be better understood by exacerbated fear generalization to related cues or situations (see also Lissek et al., 2005, 2008, 2009). This suggests that prevention strategies may benefit more from targeting fear generalization, rather than the fear learning itself. The question is how fear generalization might be reduced. A number of animal conditioning studies on contextual generalization provide interesting hints in this regard. These studies investigated the
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generalization of conditioned fear responses across contexts (with tests of the same conditioned stimulus, CS, but in a different context). Normally, the CS is perfectly capable of evoking the conditioned fear reaction in a novel test context (i.e., strong generalization). However, Bouton and Bolles (1979) demonstrated that when the CS had been preexposed in the test context, much less fear was observed to that CS during test (see Bouton, 1993, for an overview of related studies). This shows that the generalization from the conditioning to the test context can be reduced by prior non-fearful experiences with the CS in the test context. Hence, by slightly adapting the latent inhibition technique (preexposing to the test situation rather than to the conditioning situation), fear generalization might be targeted. This is remarkable, because it shows that fear conditioning and generalization do not simply override the effects from earlier non-fearful experiences, as one might expect. Instead, earlier non-fearful experiences seem to protect against conditioned fear generalization. This is in line with the idea that first experiences with a stimulus leave a stronger memory trace than subsequent, conflicting experiences (Bouton, 1993, 2002). The present study was set up to test this adapted preexposure technique on the level of stimulus generalization, as this is supposedly an important mechanism in anxiety disorders (e.g., PTSD). For that purpose, we selected a human differential fear conditioning procedure that was used before to investigate the generalization of fear conditioning and extinction (Vervliet, Vansteenwegen, & Eelen, 2004; Vervliet, Vansteenwegen, Baeyens, Hermans, & Eelen, 2005). The present study was simply a reversal of the basic design, so that now the effects of prior non-fearful experiences on fear generalization could be investigated. In the conditioning phase, all participants were differentially conditioned to two geometrical figures by presenting one figure (CS1) 4 times with the shock unconditioned stimulus (US), and the other figure (CS2) 4 times without shock. Next, all participants were tested with similar but different figures (GS1, GS2), 3 presentations each, without shock. The level of fear generalization was assessed via electrodermal responding and shock-expectancy ratings during test. Crucially, one group had received 4 preexposures to the test stimuli (GS1, GS2) during the first phase (group preexposure, PRE), without shock. The other group had received 4 exposures to completely different figures (group control, CONTR). Based on the animal conditioning studies, it was hypothesized that prior non-fearful experiences with the test stimuli would reduce fear generalization. Hence, we predicted that the level of differential fear responding during test would be lower in group PRE as compared to group CONTR. Methods Participants Thirty-eight students (12 females and 6 males in group CONTR, 11 females and 9 males in group PRE; mean age ¼ 23.4 years, SD ¼ 3.9) participated either to earn course credits or a small monetary award (7.5 euro). Participants were randomly assigned to the two experimental groups. They all gave informed consent and were informed that they could decline to participate at any time. Apparatus The stimuli were identical as in Vervliet et al. (2005), with the only exception that the geometrical figures were now presented on a computer screen in front of the participants (instead of projected on the wall). Four pictures of black outlines of geometrical shapes (two triangles and two parallelograms) served as experimental stimuli (see Vervliet et al., 2005, for a visualization of the stimuli). During the preexposure phase, group PRE received presentations of triangle 1 (isosceles; base: 75 mm, height: 60 mm) and parallelogram 1
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(base: 50 mm, height: 45 mm, oblique side: 60 mm), whereas group CONTR received presentations of two irrelevant figures (a circle and an arrow). The conditioning phase was identical for both groups, consisting of presentations of triangle 2 (a blunt version of Triangle 1; base: 80 mm, height: 45 mm) and parallelogram 2 (a blunt version of Parallelogram 1; base: 65 mm, height: 50 mm, oblique side: 55 mm). The final test phase was also identical for both groups, consisting of presentations of triangle 1 and parallelogram 1. The shock US was an electrocutaneous stimulus delivered by a Digitimer DS7A constant current stimulator (Hertfordshire, UK), via a costume built Ag plate on the left forearm of the participant. A conductive gel (Signa, Parker) was applied between the plate and the skin. Shock-expectancy ratings were measured online during each stimulus presentation. A scale was presented on the bottom of the screen that was labelled from “certainly no shock” (100) through “uncertain” (0) to “certainly shock” (þ100). Participants could move the pointer on the scale by using the mouse, and completed their rating by clicking on the left mouse button. The scale disappeared at the termination of each stimulus presentation. Electrodermal activity was measured as in Effting and Kindt (2007), by using an input device with a sine shaped excitation voltage (.5 V) of 50 Hz, which was derived from the mains frequency. The input device was connected to two Ag/AgCl electrodes. The use of an electrode gel was omitted to prevent the gel forming a capacitive load for the signal. Optimal electrode contact area was ensured by using preformed electrodes of 20 16 mm, which were attached with adhesive tape to the medial phalanges of the second and third fingers of the non-preferred hand. The signal from the input device was led through a signal-conditioning amplifier and the analogue output was digitzed at 100 Hz by a 16bit AD-converter (National Instruments, NI-6224). The experiment was run on a Pentium IV 3GHz PC. The software program Presentation controlled the presentations of the experimental stimuli (CSs) and the shock apparatus (US). Another software program (VSSRP98 v5.4) on a separate Pentium IV 3GHz PC was used to record and store the expectancy ratings and skin conductance during the entire experiment. Procedure The procedure was almost identical to Vervliet et al. (2005), the most important difference being the absence of shocks during the first but not second phase. Following informed consent and initial instructions about the experiment, electrodes were attached to the participant’s fingers and forearm and the level of shock was individually selected via a standard work-up procedure to a level described as “definitely uncomfortable, but not painful”. Next, the participants were instructed that they were about to see geometrical figures on the screen and that some of these pictures would be followed by the shock stimulus. They were also told that they would have to try to predict the occurrence of the shock on the basis of the classes of figures that they would see, and distinguish between ‘good’ and ‘bad’ classes of figures (cf. instructions in Vervliet et al., 2005).1 Next, the operation of the expectancy pointer was explained.
1 The exact instructions were (translated from Dutch): “During the experiment, you will see a number of stimuli on the screen. After some of these stimuli, you will feel the electrical stimulus, but not after others. It is your task to determine which stimuli are related to the electrical stimulus and which stimuli are not. It is important to know that the stimuli are geometrical figures: It is your task to learn to predict on the basis of the classes of these figures whether the electrical stimulus will follow or not. With “class” I mean the general terms that people use to describe figures, such as ‘triangle’, ‘square’ etc. In brief, it is your task to distinguish between good and bad classes of figures.”
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During preexposure, acquisition and test, the stimuli were presented for 8 s, with inter trial intervals of 15, 20, 25 s (randomized across trials, with the restriction that no more than two consecutive inter trial intervals were identical within each phase). During the preexposure phase, the two GSs (triangle 1 and parallelogram 1, counterbalanced) were each four times presented without shock (Group PRE). Presentations were divided into two blocks of two GS1 and two GS2 trials (randomized per block). In group CONTR, the GSs were replaced by two irrelevant stimuli (a circle and an arrow), but the manner of presenting was identical. From the acquisition phase on, the two groups did not differ. The two CSs (triangle 2 and parallelogram 2, counterbalanced) were each four times presented, of which CS1 co-terminated with the shock US. Presentations were divided into two blocks of two CS1 and two CS2 trials (randomized per block). Finally, the test phase consisted of three presentations of the GS1 and the GS2, in random order (with the restriction that no more than two consecutive presentations were identical). In addition, the first test trial was counterbalanced so that half of the participants in each group were first tested with the GS1 (versus the GS2 in the other half). After completion of the experiment, participants were asked to fill out some questions regarding the electrical stimulus. The first two questions were “How unpleasant [intense] was the electrical stimulus in general?”, and were rated on an 11-points scale ranging from “not unpleasant [intense]” over “unpleasant [intense]” to “very unpleasant [intense]”. The third question asked to what extent the electrical stimulus made them startle (“not”[1], “slightly”[2], “moderately”[3], “strongly”[4], “very strongly”[5]). Results Post-experimental questionnaire and shock level The selected level of shock was comparable in the two groups: M ¼ 11.22 mA, SD ¼ 8.44 in group CONTR and M ¼ 12.50 mA, SD ¼ 5.11 in group PRE (independent-samples t-test: t(36) ¼ .57, p ¼ .57). The rated unpleasantness was also comparable: M ¼ 6.33, SD ¼ 1.88 in group CONTR and M ¼ 5.90, SD ¼ 2.05 in group PRE (independent samples t-test: t(36) ¼ .68, p ¼ .50). The rated intensity was also comparable: M ¼ 5.33, SD ¼ 1.68 in group CONTR and M ¼ 4.58, 1.83 in group PRE (independent samples t-test: t(35) ¼ 1.30, p ¼ .20). Finally, the startling effects of electrical stimulus were not rated differently between the two groups: M ¼ 3.44, SD ¼ .78 in group CONTR and M ¼ 3.05, SD ¼ .69 in group PRE (independentsamples t-test: t(36) ¼ 1.65, p ¼ .11). On-line ratings of shock-expectancy Two participants (from group PRE) were not selected for statistical analyses of the shock-expectancy ratings, because they failed to expect the shock more to CS1 than to CS2 on the last acquisition trial. Preexposure The left panel of Fig. 1 suggests that the shock-expectancy ratings to both stimuli gradually decreased over the nonreinforced preexposure trials, and equally so in both groups. This was confirmed by an ANOVA with one between-subjects factor (Group, 2 levels), one within-subjects factor (Stimulus, 2 levels) and one repeated measures factor (Trial, 4 levels), of which only the main effect of Trial was significant, F(3,102) ¼ 52.31, p < .001, partial h2 ¼ .61 (all other Fs < 2.10).
Acquisition The middle panel of Fig. 1 suggests the development of the differential shock-expectancy in both groups. This was confirmed by an ANOVA with one between-subjects factor (Group, 2 levels), one within-subjects factor (Stimulus, 2 levels) and one repeated measures factor (Trial, 4 levels), revealing the significant Stimulus Trial interaction, F(3,102) ¼ 94.54, p < .001, partial h2 ¼ .74. Importantly, the Group Stimulus Trial interaction did not reach the level of significance, F(3,102) ¼ 1.52, p ¼ .21, nor did the Group Stimulus interaction, F(1,34) ¼ 2.39, p ¼ .13. Nevertheless, a main effect of Group was found, suggesting that there was a difference in the general level of shock-expectancy between the groups, F(1,34) ¼ 8.41, p < .01, partial h2 ¼ .20. In addition, a main effect of Trial, F(3,102) ¼ 2.77, p < .05, partial h2 ¼ .08, that subsumed under a Group Trial interaction was found, F(3,102) ¼ 3.09, p < .05, partial h2 ¼ .08. In order to reveal on which trials the groups differed, we calculated the mean expectancy per trial (over CS1 and CS2), and checked for Bonferroni-corrected differences between the groups per trial. This analysis revealed that the mean level of shock-expectancy differed on every trial, except the last one (trial 1: F(1,34) ¼ 9.74, p < .01, partial h2 ¼ .22; trial 2: F(1,34) ¼ 5.35, p < .05, partial h2 ¼ .14; trial 3: F(1,34) ¼ 4.58, p < .05, partial h2 ¼ .12, trial 4: F < 1). This shows that the preexposure with similar stimuli induced a generally lower level of shock-expectancy during conditioning, but also that the group differences disappeared with more conditioning trials. Test The right panel of Fig. 1 suggests that the generalization of conditioned shock-expectancy was weaker in group PRE as compared to group CONTR. This was confirmed by an ANOVA over the last acquisition and the first test trial, involving one betweensubjects factor (Group, 2 levels), one within-subjects factor (Stimulus, 2 levels) and one repeated measures factor (Trial, 2 levels). The results of this analysis revealed a main effect of Stimulus, F(1,34) ¼ 211.34, p < .001, partial h2 ¼ .86, and a significant Stimulus Trial interaction, F(1,34) ¼ 44.47, p < 001, partial h2 ¼ .57, which subsumed under a significant Group Stimulus Trial interaction, F(1,34) ¼ 4.64, p < .05, partial h2 ¼ .12. This interaction shows that the level of generalization differed between the groups. We further investigated this interaction by Bonferroni-corrected pairwise comparisons, which showed that the discrimination was still significant on test in group CONTR, F(1,34) ¼ 35.48, p < .001, partial h2 ¼ .512, but not in group PRE, F(1,34) ¼ 2.42, p ¼ .13. In order to investigate whether the interaction is driven by changes to GS1, we computed difference scores over the two trials for each stimulus per group. This was analysed in a separate ANOVA with one between-subjects factor (Group, 2 levels) and one within-subjects factor (Stimulus, 2 levels). The Bonferroni-corrected pairwise comparisons revealed a significant group difference for GS1, F(1,34) ¼ 18.07, p < .001, partial h2 ¼ .35, and not for GS2, F(1,34) ¼ 1.31, p ¼ .26. In sum, the prior nonfearful experiences produced a larger decrement of generalization, which resulted in the absence of a significant discrimination at test in group PRE. This effect was mainly due to differences in GS1. Finally, a separate ANOVA was conducted over the three test trials, with one between-subjects factor (Group, 2 levels), one withinsubjects factor (Stimulus, 2 levels) and one repeated measures factor (Test, 3 levels), which again showed a main effect of Stimulus, F(1,34) ¼ 44.12, p < .001, partial h2 ¼ .57, and, most importantly, a significant Group Stimulus interaction, F(1,34) ¼ 8.76, p < .01, partial h2 ¼ .21. Bonferroni-corrected post-hoc comparisons showed that the GSþ versus GS discrimination was significant in both groups, CONTR: F(1,34) ¼ 4.61, p < .001, PRE: F(1,34) ¼ 6.78, p < .05. This shows again that the prior non-fearful experiences with the generalization test stimuli in group PRE decreased differential expectancy at test, however, without completely abolishing it.
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Fig. 1. Mean shock-expectancy ratings per trial over the entire experiment. The upper graph represents the data from group CONTR, the lower graph represents the data from group PRE. The left panel shows the data from the preexposure phase (pre1epre4), with irrelevant stimuli (IRR) in group CONTR and the generalization test stimuli (GS) in group PRE. The middle panel shows the data from the acquisition phase (acq1eacq4) with the same stimuli (CS) in both groups. The right panel shows the data from the test phase with the same stimuli (GS) in both groups. CS1 was always followed by the shock, CS2 was never followed by the shock. GS1 and GS2 were perceptually similar to CS1 and CS2, respectively, and never followed by the shock. Error bars represent SEM.
Skin conductance responding Skin conductance responses elicited by the experimental stimuli were scored as first interval responses (F.I.R., cf. Prokasy & Raskin, 1973). Amplitudes were calculated as the difference between the peak value during 1e4 s after stimulus onset and a baseline value (averaged skin conductance level during the 2 s prior to stimulus onset). Negative outcomes were scored as zero and left in the analyses (cf. Vervliet et al., 2005). The resulting dataset was Z-transformed per participant, in order to minimize interindividual differences in the general amplitude of skin conductance responses. Prior to statistical analyses, data were averaged into blocks of two trials (preexposure, acquisition) or three trials (test), resulting in two preexposure blocks, two acquisition blocks and one test block. Preexposure The left panel of Fig. 2 suggests that the initial skin conductance response to both stimuli decreased over the two preexposure blocks, equally so in both groups. This was confirmed by an ANOVA with one between-subjects factor (Group, 2 levels), one withinsubjects factor (Stimulus, 2 levels) and one repeated measures factor (Block, 2 levels), of which only the main effect of Block reached the significance criterion, F(1,36) ¼ 6.01, p < .05, partial h2 ¼ .14 (all other Fs < 1).
Acquisition The middle panel of Fig. 2 suggests higher skin conductance responding to the CSþ versus the CS-. An ANOVA with one betweensubjects factor (Group, 2 levels), one within-subjects factor (CS, 2 levels) and one repeated measures factor (Block, 2 levels) did reveal a main effect of Stimulus, F(1,36) ¼ 4.16, p < .05, partial h2 ¼ .10, but the Stimulus Block interaction failed to reach significance, F < 1. All the effects with Group did not reach significance, Fs < 1, suggesting that the groups did not differ in the rate of fear conditioning. A separate ANOVA on the first block, with one between-groups factor (Group, 2 levels) and one within-subjects factor (CS, 2 levels) revealed the absence of a significant Group CS interaction, confirming that the conditioning was not delayed in group PRE (i.e., no latent inhibition effect). Test The right panel of Fig. 2 suggests that the conditioned discrimination at test was stronger in group CONTR as compared to group PRE. This was supported by an ANOVA with one betweensubjects factor (Group, 2 levels) and one within-subjects factor (Stimulus, 2 levels). Most importantly, the crucial Group Stimulus interaction approached significance with a moderate effect size, F(1,36) ¼ 3.59, p ¼ .066, partial h2 ¼ .09 (all other Fs < 1.7, ns). This suggests that the manipulation did influence the rate of generalization in the two groups. Indeed, a separate ANOVA in group CONTR, with one within-subjects factor (Stimulus, 2 levels) and one
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Fig. 2. Z-transformed first interval skin conductance responses per block of two/three trials over the entire experiment. The upper graph represents the data from group CONTR, the lower graph represents the data from group PRE. The left panel shows the data from the two preexposure blocks (pre1epre2), with irrelevant stimuli (IRR) in group CONTR and the generalization test stimuli (GS) in group PRE. The middle panel shows the data from the two acquisition blocks (acq1eacq2) with the same stimuli (CS) in both groups. The right panel shows the data from the test block with the same stimuli (GS) in both groups. CS1 was always followed by the shock, CS2 was never followed by the shock. GS1 and GS2 were perceptually similar to CS1 and CS2, respectively, and never followed by the shock. Error bars represent SEM.
repeated measures factor (Trial, 3 levels), showed a main effect of Stimulus, F(1,17) ¼ 5.24, p < .05, partial h2 ¼ .24, but the same ANOVA in group PRE did not, F < 1. We further investigated the Group Stimulus interaction by replicating the Group Stimulus ANOVA, while only including those participants that showed successful conditioning in the skin conductance measure (criterion: stronger responses to the CSþ versus the CS on the second acquisition block). Although this greatly reduced the number of participants per group (N ¼ 11 in group CONTR, N ¼ 12 in group PRE) 2, the crucial Group Stimulus interaction was significant in this subgroup, F(1,21) ¼ 5.51, p < .05, partial h2 ¼ .21.3 In order to compare this group difference with
2 The high level of interindividual variability and non-robust conditioning effect may be due to the fact that we did not measure respiratory activity during the experiment, and hence were not able to filter out respiration-induced fluctuations in the skin conductance. 3 The novel means in the subgroups were: Group PRE: Mgsþ: .29, Mgs: .24; Group CONTR: Mgsþ: .24, Mgs: .40.
acquisition, we calculated the means of the last 2 acquisition trials and the means over the three test trials. The resulting ANOVA, with one between-groups factor (Group, 2 levels), one within-groups factor (Phase, 2 levels) and one repeated-measures factor (Stimulus, 2 levels), revealed a marginally significant Group Phase Stimulus interaction, F(1,21) ¼ 4.19, p ¼ .053, partial h2 ¼ .17.4 These results support the hypothesis that prior nonfearful experiences with generalization test stimuli reduces the level of fear generalization to these stimuli. Fig. 2, however, also suggests that the difference between the groups is mainly driven by a difference in responding to the GS, rather than the GSþ. This was confirmed by Bonferroni-corrected pairwise comparisons in the overall ANOVA (see above), revealing a significant group difference for the GS, F(1,36) ¼ 5.32, p < .05, partial h2 ¼ .13, and not for the GSþ, F < 1. The same pattern was found with the selection criterion (see above), GS: F(1,21) ¼ 7.41,
4 The acquisition means (over the last 2 trials) in the subgroups were: Group PRE: Mcsþ: .15, Mcs: .37; Group CONTR: Mcsþ: .06, Mcs: .39.
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p < .05, partial h2 ¼ .26; GSþ: F(1,21) ¼ .12. This is an unexpected finding that complicates the interpretation of the skin conductance data. Discussion The present experiment was designed to test whether prior non-fearful experiences can protect a stimulus against fear generalization. One group of participants (PRE) was preexposed to the generalization test stimuli (GS1, GS2), whereas group CONTR was preexposed to irrelevant stimuli. Next, CS1 and CS2 were differentially fear conditioned and the amount of generalization to the test stimuli (GS1, GS2) was assessed in both groups. The shockexpectancy ratings clearly showed that prior non-fearful experiences reduced the level of shock-expectancy to the test GS1, as well as the size of the GS1/GS2 discrimination. Accordingly, the skin conductance data exhibited a smaller discrimination between GS1 and GS2 in group PRE, as compared to group CONTR. Taken together, these results suggest that prior non-fearful experiences can protect against fear generalization from another stimulus, which makes it an interesting strategy for the prevention of clinical anxiety. The skin conductance results showed the expected reduction in the generalization of the conditioned discrimination (group PRE). However, this was not so much due to a decrease of responding to GS1, but rather to an increase in responding to GS2. This seems strange and contrary to the hypothesis, but it also points to the interesting question of whether one should look at the responses to individual stimuli in a differential conditioning paradigm. Skin conductance is not a selective measure of fear; rather, it is a measure of general arousal that is very sensitive to orienting reflexes (Öhman, 1983). Thus, part of the arousal elicited by CS1 will result from its being associated with the shock, the other part will be based on non-associative processes (habituation, sensitization, etc.). The latter is equally captured by CS2, and hence it is the difference between CS1 and CS2 that reflects the genuine CR. From this perspective, one should focus exclusively on the discrimination, not on responding to the individual stimuli. If, as in our results, GS2 increases to such an extent that the discrimination is no longer significant, this indicates that GS1 does not add anything over and above the non-associative processes captured by GS2. Nevertheless, the fact that the response to GS2 does increase must reflect an increase in arousal, whatever its source. In the present study, the most plausible explanation is that the perceptual change from the CSs to the GSs caused this increased arousal. The fact that this didn’t occur in group CONTR, may relate to differences in learned discriminability between the two groups: To the extent that participants from group PRE had learned to attend more to the subtle differences between the shapes (sharp versus blunt triangle/ parallelogram), these differences would arguably lead to more orienting responding at test than in group CONTR (see below). Whatever the explanation, GS1 did not add arousal over and above GS2 in group PRE, which is in line with the hypothesis. The present study also provided an opportunity to look at the effect of the latent inhibition procedure (nonreinforced preexposures) on conditioning with a similar stimulus. The control group represented the “normal” rate of conditioning (because the preexposures occurred with irrelevant stimuli). The rating results show that there was a main group effect, but no interaction with stimulus. Hence, shock-expectancies were generally somewhat lower in group PRE, yet without affecting the size of the discrimination. No effect was found in the skin conductance measure. These results suggest that the preexposure manipulation produced a general delay in the acquisition of shock-expectancy during the conditioning phase. This shows that the current preexposure
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procedure may have a double impact on traumatic learning: weakening the acquisition of threat-expectancy and reducing the generalization of fear. This may eventually increase the clinical potential of the procedure. Two different processes may have contributed to the effect on generalization, in accordance with two processes that may also underlie latent inhibition. First, the effect can be caused by conditioned inattention (Lubow, 1997). This popular way to explain latent inhibition proposes that repeated exposures to a neutral stimulus produce a decrease in the attention for that stimulus, such that it becomes less effective when it enters the conditioning process (e.g., Mackintosh, 1975). Interestingly, when the stimulus is perceptually changed at the start of the conditioning phase, its novel perceptual features should receive relatively more attention than its preexposed features, and hence be more effective. Conditioning will thus proceed primarily with these novel features. When testing the original stimulus again, these conditioned features are removed and less generalization will be produced (see also the theories of McLaren & Mackintosh, 2000, and Hall, 2003, on the perceptual learning effect). The conditioned inattention hypothesis thus explains the generalization decrement by assuming that conditioning will accrue mainly to the unique features of the CS. An alternative explanation can be formulated in terms of conditioned inhibition (Pavlov, 1927). During the preexposure phase, the participants may actively learn that the stimulus (GS) is not followed by the shock US (note that participants were instructed beforehand that they would receive shocks following some stimulus presentations; the absence of shock was therefore meaningful, even before any shock had occurred). This is called inhibition learning (also “safety” learning in the context of fear conditioning). Most theories of associative learning assume that inhibition is the symmetrical opposite of excitation (e.g., Rescorla & Wagner, 1972, see also Lotz, Vervliet, & Lachnit, 2009). This means that prior learned inhibition to the test stimulus will counteract any generalized excitation that it receives from the CS. The result will be a lower level of CR evoked by the test stimulus (i.e., a generalization decrement). This hypothesis is supported by the shock-expectancy ratings in the first phase of the experiment. The ratings go in the direction of “Certainly no shock” (in both groups), which may be viewed as an index of inhibition learning (CS-noUS association). The conditioned inhibition hypothesis thus explains the generalization decrement by assuming that the GS will have acquired and maintained inhibitory powers that counteract generalized excitation from the CS. Taken together, the observed reduction in fear generalization may be the result of conditioned inattention (perceptual learning), conditioned inhibition (safety learning), or both. It will be interesting for future research to see whether the obtained reduction in fear generalization is specific to the preexposed stimulus, or whether the CS loses its ability to generalize fear to any other stimulus. Obviously, the clinical impact would be greatly enhanced in the latter case. The present study already makes interesting suggestions for the prevention of clinical anxiety, as it supports the idea that prior nonfearful experiences can protect against fear generalization from other stimuli. This process may create specific beacons of safety in the aftermath of a traumatic event, which is considered a highly important resilience factor that should be promoted in early interventions to prevent the development of post-traumatic stress disorder (e.g., Hobfoll et al., 2007). The present study may suggest that efforts to strengthen feelings of safety in people who are vulnerable for trauma exposure, may well contribute to a more positive course after traumatic experience. Importantly, these feelings of safety would not be related to the potential contexts of the trauma itself (as in the case of latent inhibition), but rather to
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clearly differentiated contexts that can produce a “protective shield” (Hobfoll et al., 2007) by blocking the fear generalization. Important first steps can consist of (1) developing screening instruments in order to identify persons with low feelings of safety, and (2) implementing strategies that promote feelings of safety in the selected group. These strategies may involve preexposure techniques that (a) enhance the discriminability between a protective context and the potential trauma context (perceptual learning, e.g., through conditioned inattention), and/or (b) augment the sense of safety in that protective context (safety learning, e.g., through conditioned inhibition). Acknowledgement Preparation of this paper was supported by a VENI-grant from the Netherlands Organisation for Scientific Research (NWO). We would like to thank Loek Wertwijn and Fleurtje van der Maaten for collecting the data. References Bouton, M. E., & Bolles, R. C. (1979). Contextual control of the extinction of conditioned fear. Learning and Motivation, 10, 445e466. Bouton, M. E. (1993). Context, time, and memory retrieval in the interference paradigms of pavlovian learning. Psychological Bulletin, 114(1), 80e99. Bouton, M. E. (2002). Context, ambiguity and unlearning: sources of relapse after behavioral extinction. Biological Psychiatry, 52(10), 976e986. Davey, G. C. (1989). Dental phobias and anxieties: evidence for conditioning processes in the acquisition and modulation of a learned fear. Behaviour Research and Therapy, 27(1), 51e58. Effting, M., & Kindt, M. (2007). Contextual control of human fear associations in a renewal paradigm. Behaviour Research and Therapy, 45(9), 2002e2018. Ehlers, A., & Clark, D. (2000). A cognitive model of posttraumatic stress disorder. Behaviour Research and Therapy, 38, 319e345. Feldner, M., Monson, C., & Friedman, M. (2007). A critical analysis of approaches to targeted PTSD prevention: current status and theoretically derived future directions. Behavior Modification, 31, 80e116. Hall, G. (2003). Learned changes in the sensitivity of stimulus representations: associative and nonassociative mechanisms. The Quarterly Journal of Experimental Psychology: Comparative and Physiological Psychology, 56B(1), 43e55.
Hobfoll, S. E., Watson, P., Bell, C. C., Bryant, R. A., Brymer, M. J., Friedman, M. J., et al. (2007). Five essential elements of immediate and mid-term mass trauma intervention: empirical evidence. Psychiatry, 70(4), 283e315. Lissek, S., Powers, A. S., McClure, E. B., Phelps, E. A., Woldehawariat, G., Grillon, C., et al. (2005). Classical fear conditioning in the anxiety disorders: a metaanalysis. Behaviour Research and Therapy, 43, 1391e1424. Lissek, S., Biggs, A. L., Rabin, S. J., Cornwell, B. R., Alvarez, R. P., Pine, D. S., et al. (2008). Generalization of conditioned fear-potentiated startle in humans: experimental validation and clinical relevance. Behaviour Research and Therapy, 46, 678e687. Lissek, S., Rabin, S., Heller, R., Lukenbaugh, D., Geraci, M., Pine, D., et al. (2009). Overgeneralization of conditioned fear as a pathogenic marker of panic disorder. American Journal of Psychiatry, 167(1), 47e55. Lotz, A., Vervliet, B., & Lachnit, H. (2009). Blocking of conditioned inhibition in human causal learning: no learning about the absence of outcomes. Experimental Psychology, 56(6), 381e385. Lubow, R. E. (1973). Latent inhibition. Psychological Bulletin, 79(6), 398e407. Lubow, R. E. (1997). Latent inhibition as a measure of learned inattention: some problems and solutions. Behavioural Brain Research, 88, 75e83. Lubow, R. E., & Gerwitz, J. C. (1995). Latent inhibition in humans: data, theory and implications for schizophrenia. Psychological Bulletin, 117(1), 87e103. Mackintosh, N. J. (1975). A theory of attention: variations in the associability of stimuli with reinforcement. Psychological Review, 82(4), 276e298. McLaren, I., & Mackintosh, N. (2000). An elemental model of associative learning: I. Latent inhibition and perceptual learning. Animal Learning & Behavior, 28, 211e246. Öhman, A. (1983). The orienting response during pavlovian conditioning. In D. Siddle (Ed.), Orienting and habituation: Perspectives in human research. New York: John Wiley & Sons Ltd. Pavlov, I. (1927). Conditioned reflexes. London: Oxford University Press. Prokasy, W. F., & Raskin, D. C. (1973). Electrodermal activity in psychological research. Oxford, England: Academic Press. Rescorla, R., & Wagner, A. (1972). A theory of pavlovian conditioning: variations in the effectiveness of rein forcement and nonreinforcement. In A. Black, & W. Prokasy (Eds.), Classical conditioning II (pp. 64e99). New York: Appleton Century Crofts. Ten Berge, M., Veerkamp, J. S. J., & Hoogstraten, J. (2002). The etiology of childhood dental fear: the role of dental and conditioning experiences. Journal of Anxiety Disorders, 16, 321e329. Vaitl, D., & Lipp, O. V. (1997). Latent inhibition and autonomic responses: a psychophysiological approach. Behavioral Brain Research, 88(1), 85e93. Vervliet, B., Vansteenwegen, D., & Eelen, P. (2004). Generalization of extinguished skin conductance responding in human fear conditioning. Learning & Memory, 11, 555e558. Vervliet, B., Vansteenwegen, D., Baeyens, F., Hermans, D., & Eelen, P. (2005). Return of fear in a human differential conditioning paradigm caused by a stimulus change after extinction. Behaviour Research and Therapy, 43(3), 357e371.
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Fear generalization in humans: Impact of prior non-fearful experiences Bram Vervliet a, b, *, Merel Kindt a, Debora Vansteenwegen b, Dirk Hermans b a b
Department of Clinical Psychology, University of Amsterdam, Roetersstraat 15, 1018 WB, Amsterdam, The Netherlands Department of Psychology, University of Leuven, Belgium
a r t i c l e i n f o
a b s t r a c t
Article history: Received 15 December 2009 Received in revised form 23 June 2010 Accepted 8 July 2010
Fear generalization lies at the heart of many anxiety problems, and is therefore an important target for prevention and/or treatment. Here, we investigated whether fear generalization towards a specific stimulus can be weakened by prior non-fearful experiences with that stimulus. Using the standard human fear conditioning procedure, all participants received paired presentations of a geometric figure and an electric shock. This was followed by a test phase in which a similar but different figure was presented. Electrodermal responding and ratings of shock-expectancy measured the level of fear generalization towards this test stimulus. Crucially, half of the participants had been preexposed to that stimulus (without shock). The results show significantly less generalization in this group, suggesting that prior non-fearful experiences can protect against fear generalization. These results may inspire novel ways to prevent the development of clinical anxiety. Ó 2010 Published by Elsevier Ltd.
Keywords: Fear conditioning Latent inhibition Generalization Prevention Anxiety disorders
Introduction Prevention is better than cure, but little is known about effective prevention in the case of clinical anxiety. The conditioning model of anxiety has inspired one well-known technique e “latent inhibition” e that is aimed to reduce the rate of fear conditioning that can occur during a traumatic experience. This technique involves prior non-fearful experiences with the cues from the trauma context before the trauma has occurred. Animal conditioning research has shown that prior nonreinforced exposures to a to-be-conditioned stimulus delays the rate of fear conditioning with that stimulus, when it is later paired with an electric shock (“latent inhibition”, e.g., Lubow, 1973). However, it has proven cumbersome to replicate this finding in human experimental research; the phenomenon seems less robust and depends more on specific experimental parameters (Lubow, 1997; Lubow & Gerwitz, 1995; but see Vaitl & Lipp, 1997). Moreover, even animal research has shown that the latent inhibition effect is fragile: Changes in the perceptual features of the stimulus or the background context at the start of the conditioning phase seriously weaken the latent inhibition effect (Bouton, 1993; Lubow, 1973). Hence, the applicability of latent inhibition procedures is quite limited and probably only efficient in
* Corresponding author at: Department of Psychology, University of Leuven, Roetersstraat 15, 1018 WB, Amsterdam, The Netherlands. Tel.: þ31 20 525 67 68; fax: þ31 20 639 13 69. E-mail address: [email protected] (B. Vervliet). 0005-7967/$ e see front matter Ó 2010 Published by Elsevier Ltd. doi:10.1016/j.brat.2010.07.002
very stable contexts (e.g., for the prevention of dental phobia in children, Davey, 1989; Ten berge, Veerkamp, & Hoogstraten, 2002). The latent inhibition technique starts from the basic assumption that excessive fear learning is responsible for the development of clinical anxiety: By weakening the fear learning process, one reduces the chances of developing clinical anxiety. In itself, however, fear learning is a highly adaptive mechanism that can be crucial for survival. The conditioning process underlying the fear mechanism produces fear selectively to those cues that provide unique information about the occurrence of the threatening event (Rescorla & Wagner, 1972). The trauma context is inherently dangerous for the trauma victim, and the experience of fear (and the resulting avoidance) is therefore adaptive in that context. However, fear becomes irrational when it is overgeneralized to everyday contexts/stimuli that are intrinsically safe but share (some) similarity with the trauma context. In the case of posttraumatic stress disorder (PTSD), for example, patients often show an unbridled generalization of fear towards realistically nondangerous cues (see Feldner, Monson, & Friedman, 2007). This fear generalization is therefore an important target in some psychological treatments of PTSD (e.g., Ehlers & Clark, 2000). Hence, the transfer from normal to abnormal anxiety may be better understood by exacerbated fear generalization to related cues or situations (see also Lissek et al., 2005, 2008, 2009). This suggests that prevention strategies may benefit more from targeting fear generalization, rather than the fear learning itself. The question is how fear generalization might be reduced. A number of animal conditioning studies on contextual generalization provide interesting hints in this regard. These studies investigated the
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generalization of conditioned fear responses across contexts (with tests of the same conditioned stimulus, CS, but in a different context). Normally, the CS is perfectly capable of evoking the conditioned fear reaction in a novel test context (i.e., strong generalization). However, Bouton and Bolles (1979) demonstrated that when the CS had been preexposed in the test context, much less fear was observed to that CS during test (see Bouton, 1993, for an overview of related studies). This shows that the generalization from the conditioning to the test context can be reduced by prior non-fearful experiences with the CS in the test context. Hence, by slightly adapting the latent inhibition technique (preexposing to the test situation rather than to the conditioning situation), fear generalization might be targeted. This is remarkable, because it shows that fear conditioning and generalization do not simply override the effects from earlier non-fearful experiences, as one might expect. Instead, earlier non-fearful experiences seem to protect against conditioned fear generalization. This is in line with the idea that first experiences with a stimulus leave a stronger memory trace than subsequent, conflicting experiences (Bouton, 1993, 2002). The present study was set up to test this adapted preexposure technique on the level of stimulus generalization, as this is supposedly an important mechanism in anxiety disorders (e.g., PTSD). For that purpose, we selected a human differential fear conditioning procedure that was used before to investigate the generalization of fear conditioning and extinction (Vervliet, Vansteenwegen, & Eelen, 2004; Vervliet, Vansteenwegen, Baeyens, Hermans, & Eelen, 2005). The present study was simply a reversal of the basic design, so that now the effects of prior non-fearful experiences on fear generalization could be investigated. In the conditioning phase, all participants were differentially conditioned to two geometrical figures by presenting one figure (CS1) 4 times with the shock unconditioned stimulus (US), and the other figure (CS2) 4 times without shock. Next, all participants were tested with similar but different figures (GS1, GS2), 3 presentations each, without shock. The level of fear generalization was assessed via electrodermal responding and shock-expectancy ratings during test. Crucially, one group had received 4 preexposures to the test stimuli (GS1, GS2) during the first phase (group preexposure, PRE), without shock. The other group had received 4 exposures to completely different figures (group control, CONTR). Based on the animal conditioning studies, it was hypothesized that prior non-fearful experiences with the test stimuli would reduce fear generalization. Hence, we predicted that the level of differential fear responding during test would be lower in group PRE as compared to group CONTR. Methods Participants Thirty-eight students (12 females and 6 males in group CONTR, 11 females and 9 males in group PRE; mean age ¼ 23.4 years, SD ¼ 3.9) participated either to earn course credits or a small monetary award (7.5 euro). Participants were randomly assigned to the two experimental groups. They all gave informed consent and were informed that they could decline to participate at any time. Apparatus The stimuli were identical as in Vervliet et al. (2005), with the only exception that the geometrical figures were now presented on a computer screen in front of the participants (instead of projected on the wall). Four pictures of black outlines of geometrical shapes (two triangles and two parallelograms) served as experimental stimuli (see Vervliet et al., 2005, for a visualization of the stimuli). During the preexposure phase, group PRE received presentations of triangle 1 (isosceles; base: 75 mm, height: 60 mm) and parallelogram 1
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(base: 50 mm, height: 45 mm, oblique side: 60 mm), whereas group CONTR received presentations of two irrelevant figures (a circle and an arrow). The conditioning phase was identical for both groups, consisting of presentations of triangle 2 (a blunt version of Triangle 1; base: 80 mm, height: 45 mm) and parallelogram 2 (a blunt version of Parallelogram 1; base: 65 mm, height: 50 mm, oblique side: 55 mm). The final test phase was also identical for both groups, consisting of presentations of triangle 1 and parallelogram 1. The shock US was an electrocutaneous stimulus delivered by a Digitimer DS7A constant current stimulator (Hertfordshire, UK), via a costume built Ag plate on the left forearm of the participant. A conductive gel (Signa, Parker) was applied between the plate and the skin. Shock-expectancy ratings were measured online during each stimulus presentation. A scale was presented on the bottom of the screen that was labelled from “certainly no shock” (100) through “uncertain” (0) to “certainly shock” (þ100). Participants could move the pointer on the scale by using the mouse, and completed their rating by clicking on the left mouse button. The scale disappeared at the termination of each stimulus presentation. Electrodermal activity was measured as in Effting and Kindt (2007), by using an input device with a sine shaped excitation voltage (.5 V) of 50 Hz, which was derived from the mains frequency. The input device was connected to two Ag/AgCl electrodes. The use of an electrode gel was omitted to prevent the gel forming a capacitive load for the signal. Optimal electrode contact area was ensured by using preformed electrodes of 20 16 mm, which were attached with adhesive tape to the medial phalanges of the second and third fingers of the non-preferred hand. The signal from the input device was led through a signal-conditioning amplifier and the analogue output was digitzed at 100 Hz by a 16bit AD-converter (National Instruments, NI-6224). The experiment was run on a Pentium IV 3GHz PC. The software program Presentation controlled the presentations of the experimental stimuli (CSs) and the shock apparatus (US). Another software program (VSSRP98 v5.4) on a separate Pentium IV 3GHz PC was used to record and store the expectancy ratings and skin conductance during the entire experiment. Procedure The procedure was almost identical to Vervliet et al. (2005), the most important difference being the absence of shocks during the first but not second phase. Following informed consent and initial instructions about the experiment, electrodes were attached to the participant’s fingers and forearm and the level of shock was individually selected via a standard work-up procedure to a level described as “definitely uncomfortable, but not painful”. Next, the participants were instructed that they were about to see geometrical figures on the screen and that some of these pictures would be followed by the shock stimulus. They were also told that they would have to try to predict the occurrence of the shock on the basis of the classes of figures that they would see, and distinguish between ‘good’ and ‘bad’ classes of figures (cf. instructions in Vervliet et al., 2005).1 Next, the operation of the expectancy pointer was explained.
1 The exact instructions were (translated from Dutch): “During the experiment, you will see a number of stimuli on the screen. After some of these stimuli, you will feel the electrical stimulus, but not after others. It is your task to determine which stimuli are related to the electrical stimulus and which stimuli are not. It is important to know that the stimuli are geometrical figures: It is your task to learn to predict on the basis of the classes of these figures whether the electrical stimulus will follow or not. With “class” I mean the general terms that people use to describe figures, such as ‘triangle’, ‘square’ etc. In brief, it is your task to distinguish between good and bad classes of figures.”
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During preexposure, acquisition and test, the stimuli were presented for 8 s, with inter trial intervals of 15, 20, 25 s (randomized across trials, with the restriction that no more than two consecutive inter trial intervals were identical within each phase). During the preexposure phase, the two GSs (triangle 1 and parallelogram 1, counterbalanced) were each four times presented without shock (Group PRE). Presentations were divided into two blocks of two GS1 and two GS2 trials (randomized per block). In group CONTR, the GSs were replaced by two irrelevant stimuli (a circle and an arrow), but the manner of presenting was identical. From the acquisition phase on, the two groups did not differ. The two CSs (triangle 2 and parallelogram 2, counterbalanced) were each four times presented, of which CS1 co-terminated with the shock US. Presentations were divided into two blocks of two CS1 and two CS2 trials (randomized per block). Finally, the test phase consisted of three presentations of the GS1 and the GS2, in random order (with the restriction that no more than two consecutive presentations were identical). In addition, the first test trial was counterbalanced so that half of the participants in each group were first tested with the GS1 (versus the GS2 in the other half). After completion of the experiment, participants were asked to fill out some questions regarding the electrical stimulus. The first two questions were “How unpleasant [intense] was the electrical stimulus in general?”, and were rated on an 11-points scale ranging from “not unpleasant [intense]” over “unpleasant [intense]” to “very unpleasant [intense]”. The third question asked to what extent the electrical stimulus made them startle (“not”[1], “slightly”[2], “moderately”[3], “strongly”[4], “very strongly”[5]). Results Post-experimental questionnaire and shock level The selected level of shock was comparable in the two groups: M ¼ 11.22 mA, SD ¼ 8.44 in group CONTR and M ¼ 12.50 mA, SD ¼ 5.11 in group PRE (independent-samples t-test: t(36) ¼ .57, p ¼ .57). The rated unpleasantness was also comparable: M ¼ 6.33, SD ¼ 1.88 in group CONTR and M ¼ 5.90, SD ¼ 2.05 in group PRE (independent samples t-test: t(36) ¼ .68, p ¼ .50). The rated intensity was also comparable: M ¼ 5.33, SD ¼ 1.68 in group CONTR and M ¼ 4.58, 1.83 in group PRE (independent samples t-test: t(35) ¼ 1.30, p ¼ .20). Finally, the startling effects of electrical stimulus were not rated differently between the two groups: M ¼ 3.44, SD ¼ .78 in group CONTR and M ¼ 3.05, SD ¼ .69 in group PRE (independentsamples t-test: t(36) ¼ 1.65, p ¼ .11). On-line ratings of shock-expectancy Two participants (from group PRE) were not selected for statistical analyses of the shock-expectancy ratings, because they failed to expect the shock more to CS1 than to CS2 on the last acquisition trial. Preexposure The left panel of Fig. 1 suggests that the shock-expectancy ratings to both stimuli gradually decreased over the nonreinforced preexposure trials, and equally so in both groups. This was confirmed by an ANOVA with one between-subjects factor (Group, 2 levels), one within-subjects factor (Stimulus, 2 levels) and one repeated measures factor (Trial, 4 levels), of which only the main effect of Trial was significant, F(3,102) ¼ 52.31, p < .001, partial h2 ¼ .61 (all other Fs < 2.10).
Acquisition The middle panel of Fig. 1 suggests the development of the differential shock-expectancy in both groups. This was confirmed by an ANOVA with one between-subjects factor (Group, 2 levels), one within-subjects factor (Stimulus, 2 levels) and one repeated measures factor (Trial, 4 levels), revealing the significant Stimulus Trial interaction, F(3,102) ¼ 94.54, p < .001, partial h2 ¼ .74. Importantly, the Group Stimulus Trial interaction did not reach the level of significance, F(3,102) ¼ 1.52, p ¼ .21, nor did the Group Stimulus interaction, F(1,34) ¼ 2.39, p ¼ .13. Nevertheless, a main effect of Group was found, suggesting that there was a difference in the general level of shock-expectancy between the groups, F(1,34) ¼ 8.41, p < .01, partial h2 ¼ .20. In addition, a main effect of Trial, F(3,102) ¼ 2.77, p < .05, partial h2 ¼ .08, that subsumed under a Group Trial interaction was found, F(3,102) ¼ 3.09, p < .05, partial h2 ¼ .08. In order to reveal on which trials the groups differed, we calculated the mean expectancy per trial (over CS1 and CS2), and checked for Bonferroni-corrected differences between the groups per trial. This analysis revealed that the mean level of shock-expectancy differed on every trial, except the last one (trial 1: F(1,34) ¼ 9.74, p < .01, partial h2 ¼ .22; trial 2: F(1,34) ¼ 5.35, p < .05, partial h2 ¼ .14; trial 3: F(1,34) ¼ 4.58, p < .05, partial h2 ¼ .12, trial 4: F < 1). This shows that the preexposure with similar stimuli induced a generally lower level of shock-expectancy during conditioning, but also that the group differences disappeared with more conditioning trials. Test The right panel of Fig. 1 suggests that the generalization of conditioned shock-expectancy was weaker in group PRE as compared to group CONTR. This was confirmed by an ANOVA over the last acquisition and the first test trial, involving one betweensubjects factor (Group, 2 levels), one within-subjects factor (Stimulus, 2 levels) and one repeated measures factor (Trial, 2 levels). The results of this analysis revealed a main effect of Stimulus, F(1,34) ¼ 211.34, p < .001, partial h2 ¼ .86, and a significant Stimulus Trial interaction, F(1,34) ¼ 44.47, p < 001, partial h2 ¼ .57, which subsumed under a significant Group Stimulus Trial interaction, F(1,34) ¼ 4.64, p < .05, partial h2 ¼ .12. This interaction shows that the level of generalization differed between the groups. We further investigated this interaction by Bonferroni-corrected pairwise comparisons, which showed that the discrimination was still significant on test in group CONTR, F(1,34) ¼ 35.48, p < .001, partial h2 ¼ .512, but not in group PRE, F(1,34) ¼ 2.42, p ¼ .13. In order to investigate whether the interaction is driven by changes to GS1, we computed difference scores over the two trials for each stimulus per group. This was analysed in a separate ANOVA with one between-subjects factor (Group, 2 levels) and one within-subjects factor (Stimulus, 2 levels). The Bonferroni-corrected pairwise comparisons revealed a significant group difference for GS1, F(1,34) ¼ 18.07, p < .001, partial h2 ¼ .35, and not for GS2, F(1,34) ¼ 1.31, p ¼ .26. In sum, the prior nonfearful experiences produced a larger decrement of generalization, which resulted in the absence of a significant discrimination at test in group PRE. This effect was mainly due to differences in GS1. Finally, a separate ANOVA was conducted over the three test trials, with one between-subjects factor (Group, 2 levels), one withinsubjects factor (Stimulus, 2 levels) and one repeated measures factor (Test, 3 levels), which again showed a main effect of Stimulus, F(1,34) ¼ 44.12, p < .001, partial h2 ¼ .57, and, most importantly, a significant Group Stimulus interaction, F(1,34) ¼ 8.76, p < .01, partial h2 ¼ .21. Bonferroni-corrected post-hoc comparisons showed that the GSþ versus GS discrimination was significant in both groups, CONTR: F(1,34) ¼ 4.61, p < .001, PRE: F(1,34) ¼ 6.78, p < .05. This shows again that the prior non-fearful experiences with the generalization test stimuli in group PRE decreased differential expectancy at test, however, without completely abolishing it.
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Fig. 1. Mean shock-expectancy ratings per trial over the entire experiment. The upper graph represents the data from group CONTR, the lower graph represents the data from group PRE. The left panel shows the data from the preexposure phase (pre1epre4), with irrelevant stimuli (IRR) in group CONTR and the generalization test stimuli (GS) in group PRE. The middle panel shows the data from the acquisition phase (acq1eacq4) with the same stimuli (CS) in both groups. The right panel shows the data from the test phase with the same stimuli (GS) in both groups. CS1 was always followed by the shock, CS2 was never followed by the shock. GS1 and GS2 were perceptually similar to CS1 and CS2, respectively, and never followed by the shock. Error bars represent SEM.
Skin conductance responding Skin conductance responses elicited by the experimental stimuli were scored as first interval responses (F.I.R., cf. Prokasy & Raskin, 1973). Amplitudes were calculated as the difference between the peak value during 1e4 s after stimulus onset and a baseline value (averaged skin conductance level during the 2 s prior to stimulus onset). Negative outcomes were scored as zero and left in the analyses (cf. Vervliet et al., 2005). The resulting dataset was Z-transformed per participant, in order to minimize interindividual differences in the general amplitude of skin conductance responses. Prior to statistical analyses, data were averaged into blocks of two trials (preexposure, acquisition) or three trials (test), resulting in two preexposure blocks, two acquisition blocks and one test block. Preexposure The left panel of Fig. 2 suggests that the initial skin conductance response to both stimuli decreased over the two preexposure blocks, equally so in both groups. This was confirmed by an ANOVA with one between-subjects factor (Group, 2 levels), one withinsubjects factor (Stimulus, 2 levels) and one repeated measures factor (Block, 2 levels), of which only the main effect of Block reached the significance criterion, F(1,36) ¼ 6.01, p < .05, partial h2 ¼ .14 (all other Fs < 1).
Acquisition The middle panel of Fig. 2 suggests higher skin conductance responding to the CSþ versus the CS-. An ANOVA with one betweensubjects factor (Group, 2 levels), one within-subjects factor (CS, 2 levels) and one repeated measures factor (Block, 2 levels) did reveal a main effect of Stimulus, F(1,36) ¼ 4.16, p < .05, partial h2 ¼ .10, but the Stimulus Block interaction failed to reach significance, F < 1. All the effects with Group did not reach significance, Fs < 1, suggesting that the groups did not differ in the rate of fear conditioning. A separate ANOVA on the first block, with one between-groups factor (Group, 2 levels) and one within-subjects factor (CS, 2 levels) revealed the absence of a significant Group CS interaction, confirming that the conditioning was not delayed in group PRE (i.e., no latent inhibition effect). Test The right panel of Fig. 2 suggests that the conditioned discrimination at test was stronger in group CONTR as compared to group PRE. This was supported by an ANOVA with one betweensubjects factor (Group, 2 levels) and one within-subjects factor (Stimulus, 2 levels). Most importantly, the crucial Group Stimulus interaction approached significance with a moderate effect size, F(1,36) ¼ 3.59, p ¼ .066, partial h2 ¼ .09 (all other Fs < 1.7, ns). This suggests that the manipulation did influence the rate of generalization in the two groups. Indeed, a separate ANOVA in group CONTR, with one within-subjects factor (Stimulus, 2 levels) and one
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Fig. 2. Z-transformed first interval skin conductance responses per block of two/three trials over the entire experiment. The upper graph represents the data from group CONTR, the lower graph represents the data from group PRE. The left panel shows the data from the two preexposure blocks (pre1epre2), with irrelevant stimuli (IRR) in group CONTR and the generalization test stimuli (GS) in group PRE. The middle panel shows the data from the two acquisition blocks (acq1eacq2) with the same stimuli (CS) in both groups. The right panel shows the data from the test block with the same stimuli (GS) in both groups. CS1 was always followed by the shock, CS2 was never followed by the shock. GS1 and GS2 were perceptually similar to CS1 and CS2, respectively, and never followed by the shock. Error bars represent SEM.
repeated measures factor (Trial, 3 levels), showed a main effect of Stimulus, F(1,17) ¼ 5.24, p < .05, partial h2 ¼ .24, but the same ANOVA in group PRE did not, F < 1. We further investigated the Group Stimulus interaction by replicating the Group Stimulus ANOVA, while only including those participants that showed successful conditioning in the skin conductance measure (criterion: stronger responses to the CSþ versus the CS on the second acquisition block). Although this greatly reduced the number of participants per group (N ¼ 11 in group CONTR, N ¼ 12 in group PRE) 2, the crucial Group Stimulus interaction was significant in this subgroup, F(1,21) ¼ 5.51, p < .05, partial h2 ¼ .21.3 In order to compare this group difference with
2 The high level of interindividual variability and non-robust conditioning effect may be due to the fact that we did not measure respiratory activity during the experiment, and hence were not able to filter out respiration-induced fluctuations in the skin conductance. 3 The novel means in the subgroups were: Group PRE: Mgsþ: .29, Mgs: .24; Group CONTR: Mgsþ: .24, Mgs: .40.
acquisition, we calculated the means of the last 2 acquisition trials and the means over the three test trials. The resulting ANOVA, with one between-groups factor (Group, 2 levels), one within-groups factor (Phase, 2 levels) and one repeated-measures factor (Stimulus, 2 levels), revealed a marginally significant Group Phase Stimulus interaction, F(1,21) ¼ 4.19, p ¼ .053, partial h2 ¼ .17.4 These results support the hypothesis that prior nonfearful experiences with generalization test stimuli reduces the level of fear generalization to these stimuli. Fig. 2, however, also suggests that the difference between the groups is mainly driven by a difference in responding to the GS, rather than the GSþ. This was confirmed by Bonferroni-corrected pairwise comparisons in the overall ANOVA (see above), revealing a significant group difference for the GS, F(1,36) ¼ 5.32, p < .05, partial h2 ¼ .13, and not for the GSþ, F < 1. The same pattern was found with the selection criterion (see above), GS: F(1,21) ¼ 7.41,
4 The acquisition means (over the last 2 trials) in the subgroups were: Group PRE: Mcsþ: .15, Mcs: .37; Group CONTR: Mcsþ: .06, Mcs: .39.
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p < .05, partial h2 ¼ .26; GSþ: F(1,21) ¼ .12. This is an unexpected finding that complicates the interpretation of the skin conductance data. Discussion The present experiment was designed to test whether prior non-fearful experiences can protect a stimulus against fear generalization. One group of participants (PRE) was preexposed to the generalization test stimuli (GS1, GS2), whereas group CONTR was preexposed to irrelevant stimuli. Next, CS1 and CS2 were differentially fear conditioned and the amount of generalization to the test stimuli (GS1, GS2) was assessed in both groups. The shockexpectancy ratings clearly showed that prior non-fearful experiences reduced the level of shock-expectancy to the test GS1, as well as the size of the GS1/GS2 discrimination. Accordingly, the skin conductance data exhibited a smaller discrimination between GS1 and GS2 in group PRE, as compared to group CONTR. Taken together, these results suggest that prior non-fearful experiences can protect against fear generalization from another stimulus, which makes it an interesting strategy for the prevention of clinical anxiety. The skin conductance results showed the expected reduction in the generalization of the conditioned discrimination (group PRE). However, this was not so much due to a decrease of responding to GS1, but rather to an increase in responding to GS2. This seems strange and contrary to the hypothesis, but it also points to the interesting question of whether one should look at the responses to individual stimuli in a differential conditioning paradigm. Skin conductance is not a selective measure of fear; rather, it is a measure of general arousal that is very sensitive to orienting reflexes (Öhman, 1983). Thus, part of the arousal elicited by CS1 will result from its being associated with the shock, the other part will be based on non-associative processes (habituation, sensitization, etc.). The latter is equally captured by CS2, and hence it is the difference between CS1 and CS2 that reflects the genuine CR. From this perspective, one should focus exclusively on the discrimination, not on responding to the individual stimuli. If, as in our results, GS2 increases to such an extent that the discrimination is no longer significant, this indicates that GS1 does not add anything over and above the non-associative processes captured by GS2. Nevertheless, the fact that the response to GS2 does increase must reflect an increase in arousal, whatever its source. In the present study, the most plausible explanation is that the perceptual change from the CSs to the GSs caused this increased arousal. The fact that this didn’t occur in group CONTR, may relate to differences in learned discriminability between the two groups: To the extent that participants from group PRE had learned to attend more to the subtle differences between the shapes (sharp versus blunt triangle/ parallelogram), these differences would arguably lead to more orienting responding at test than in group CONTR (see below). Whatever the explanation, GS1 did not add arousal over and above GS2 in group PRE, which is in line with the hypothesis. The present study also provided an opportunity to look at the effect of the latent inhibition procedure (nonreinforced preexposures) on conditioning with a similar stimulus. The control group represented the “normal” rate of conditioning (because the preexposures occurred with irrelevant stimuli). The rating results show that there was a main group effect, but no interaction with stimulus. Hence, shock-expectancies were generally somewhat lower in group PRE, yet without affecting the size of the discrimination. No effect was found in the skin conductance measure. These results suggest that the preexposure manipulation produced a general delay in the acquisition of shock-expectancy during the conditioning phase. This shows that the current preexposure
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procedure may have a double impact on traumatic learning: weakening the acquisition of threat-expectancy and reducing the generalization of fear. This may eventually increase the clinical potential of the procedure. Two different processes may have contributed to the effect on generalization, in accordance with two processes that may also underlie latent inhibition. First, the effect can be caused by conditioned inattention (Lubow, 1997). This popular way to explain latent inhibition proposes that repeated exposures to a neutral stimulus produce a decrease in the attention for that stimulus, such that it becomes less effective when it enters the conditioning process (e.g., Mackintosh, 1975). Interestingly, when the stimulus is perceptually changed at the start of the conditioning phase, its novel perceptual features should receive relatively more attention than its preexposed features, and hence be more effective. Conditioning will thus proceed primarily with these novel features. When testing the original stimulus again, these conditioned features are removed and less generalization will be produced (see also the theories of McLaren & Mackintosh, 2000, and Hall, 2003, on the perceptual learning effect). The conditioned inattention hypothesis thus explains the generalization decrement by assuming that conditioning will accrue mainly to the unique features of the CS. An alternative explanation can be formulated in terms of conditioned inhibition (Pavlov, 1927). During the preexposure phase, the participants may actively learn that the stimulus (GS) is not followed by the shock US (note that participants were instructed beforehand that they would receive shocks following some stimulus presentations; the absence of shock was therefore meaningful, even before any shock had occurred). This is called inhibition learning (also “safety” learning in the context of fear conditioning). Most theories of associative learning assume that inhibition is the symmetrical opposite of excitation (e.g., Rescorla & Wagner, 1972, see also Lotz, Vervliet, & Lachnit, 2009). This means that prior learned inhibition to the test stimulus will counteract any generalized excitation that it receives from the CS. The result will be a lower level of CR evoked by the test stimulus (i.e., a generalization decrement). This hypothesis is supported by the shock-expectancy ratings in the first phase of the experiment. The ratings go in the direction of “Certainly no shock” (in both groups), which may be viewed as an index of inhibition learning (CS-noUS association). The conditioned inhibition hypothesis thus explains the generalization decrement by assuming that the GS will have acquired and maintained inhibitory powers that counteract generalized excitation from the CS. Taken together, the observed reduction in fear generalization may be the result of conditioned inattention (perceptual learning), conditioned inhibition (safety learning), or both. It will be interesting for future research to see whether the obtained reduction in fear generalization is specific to the preexposed stimulus, or whether the CS loses its ability to generalize fear to any other stimulus. Obviously, the clinical impact would be greatly enhanced in the latter case. The present study already makes interesting suggestions for the prevention of clinical anxiety, as it supports the idea that prior nonfearful experiences can protect against fear generalization from other stimuli. This process may create specific beacons of safety in the aftermath of a traumatic event, which is considered a highly important resilience factor that should be promoted in early interventions to prevent the development of post-traumatic stress disorder (e.g., Hobfoll et al., 2007). The present study may suggest that efforts to strengthen feelings of safety in people who are vulnerable for trauma exposure, may well contribute to a more positive course after traumatic experience. Importantly, these feelings of safety would not be related to the potential contexts of the trauma itself (as in the case of latent inhibition), but rather to
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clearly differentiated contexts that can produce a “protective shield” (Hobfoll et al., 2007) by blocking the fear generalization. Important first steps can consist of (1) developing screening instruments in order to identify persons with low feelings of safety, and (2) implementing strategies that promote feelings of safety in the selected group. These strategies may involve preexposure techniques that (a) enhance the discriminability between a protective context and the potential trauma context (perceptual learning, e.g., through conditioned inattention), and/or (b) augment the sense of safety in that protective context (safety learning, e.g., through conditioned inhibition). Acknowledgement Preparation of this paper was supported by a VENI-grant from the Netherlands Organisation for Scientific Research (NWO). We would like to thank Loek Wertwijn and Fleurtje van der Maaten for collecting the data. References Bouton, M. E., & Bolles, R. C. (1979). Contextual control of the extinction of conditioned fear. Learning and Motivation, 10, 445e466. Bouton, M. E. (1993). Context, time, and memory retrieval in the interference paradigms of pavlovian learning. Psychological Bulletin, 114(1), 80e99. Bouton, M. E. (2002). Context, ambiguity and unlearning: sources of relapse after behavioral extinction. Biological Psychiatry, 52(10), 976e986. Davey, G. C. (1989). Dental phobias and anxieties: evidence for conditioning processes in the acquisition and modulation of a learned fear. Behaviour Research and Therapy, 27(1), 51e58. Effting, M., & Kindt, M. (2007). Contextual control of human fear associations in a renewal paradigm. Behaviour Research and Therapy, 45(9), 2002e2018. Ehlers, A., & Clark, D. (2000). A cognitive model of posttraumatic stress disorder. Behaviour Research and Therapy, 38, 319e345. Feldner, M., Monson, C., & Friedman, M. (2007). A critical analysis of approaches to targeted PTSD prevention: current status and theoretically derived future directions. Behavior Modification, 31, 80e116. Hall, G. (2003). Learned changes in the sensitivity of stimulus representations: associative and nonassociative mechanisms. The Quarterly Journal of Experimental Psychology: Comparative and Physiological Psychology, 56B(1), 43e55.
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