Developmental Psychobiology

Miriam Liora Den1 Bronwyn M. Graham1 Carol Newall2 Rick Richardson1 1 School of Psychology The University of New South Wales Sydney 2052, Australia 2

Institute of Early Childhood Macquarie University Sydney 2109, Australia

Teens That Fear Screams: A Comparison of Fear Conditioning, Extinction, and Reinstatement in Adolescents and Adults ABSTRACT: This study investigated differences between adolescents and adults on fear conditioning, extinction, and reinstatement (i.e., the recovery of conditioned fear following re-exposure to the unconditioned stimulus [US] post-extinction). Participants underwent differential conditioning (i.e., the Screaming Lady) where one neutral face (CSþ) was followed by the same face expressing fear and a loud scream (US) while another neutral face (CS) remained neutral. Extinction involved non-reinforced presentations of both CSs, after which participants were reinstated (2xUSs) or not. On two selfreport measures, both ages showed conditioning, good extinction learning and retention, and reinstatement-induced relapse. However, only adolescents showed conditioning, extinction, and reinstatement on the eye tracking measure; relapse on this measure could not be assessed in adults given they did not show initial conditioning. Lastly, higher levels of depression predicted stronger conditioning and weaker extinction in adolescents only. These findings are discussed in terms of their implications for adolescent anxiety disorders. © 2015 Wiley Periodicals, Inc. Dev Psychobiol 57:818–832, 2015. Keywords: adolescence; depression

INTRODUCTION Laboratory-based studies on fear conditioning and extinction have provided a useful conceptual framework for understanding the etiology, maintenance, and treatment of human anxiety disorders. Typically, human studies utilize a discriminative fear conditioning procedure involving the pairing of one neutral conditioned Manuscript Received: 10 February 2015 Manuscript Accepted: 8 May 2015 Correspondence to: Miriam Liora Den E-mail: [email protected] Contract grant sponsor: Australian Post Graduate Award Contract grant sponsor: National Health and Medical Research Council of Australia Contract grant number: 455431 Article first published online in Wiley Online Library (wileyonlinelibrary.com): 27 June 2015 DOI 10.1002/dev.21330  © 2015 Wiley Periodicals, Inc.

fear;

conditioning;

extinction;

reinstatement;

stimulus (CSþ) with an aversive unconditioned stimulus (US) and a second neutral CS (the CS) that never co-occurs with the US. This type of procedure leads to the formation of a threat CSþ memory (i.e., CS–US) and a safety CS memory (i.e., CS-noUS), with several studies suggesting that elevated fear to cues that signal threat and a failure to inhibit fear to cues that signal safety both contribute to the pathogenesis of anxiety disorders in adults (for review, see Christianson et al., 2012; Lissek et al., 2005). Following conditioning, extinction training involves unreinforced presentations of both CSs, leading to a reduction in the fear conditioned response (CR) elicited by the CSþ. Extinction forms the basis of exposure therapy, which involves repeated exposure to objects that the patient fears in the absence of adverse consequences and which is the most widely used and empirically validated treatment for anxiety disorders (Graham &

Developmental Psychobiology

Milad, 2011; McNally, 2007). However, most studies of fear conditioning and extinction have been done in adults, with very little empirical research examining these processes in adolescents. The lack of research on fear learning and inhibition in adolescent humans is surprising for several reasons. First, evidence suggests that the prevalence of anxiety disorders peaks during adolescence (Kessler et al., 2012; Kim-Cohen et al., 2003). In an analysis of data from the 2003 Australian Burden of Disease and Injury Study, mental disorders including both anxiety and depression were the largest contributor to disability in youth aged 10–24 years (Mathews, Hall, Vos, Patton, & Degenhardt, 2011). Second, preclinical rodent findings have revealed clear and substantial differences in fear conditioning and extinction during adolescence (for review, see Baker, Den, Graham, & Richardson, 2014). For example, unlike juvenile (postnatal day 23; P23) and adult (P90) rats, adolescent rats (P35) learn and remember fear associations when there is a large temporal gap (i.e., 20- or 40-s) separating CS offset and US onset (Den & Richardson, 2013). In addition, McCallum, Kim, and Richardson (2010) showed that adolescent rats exhibited poorer extinction retention (i.e., elevated fear at test 24 hr after extinction training) compared to juvenile and adult rats (replicated in Kim, Li, & Richardson, 2011; also see Pattwell et al., 2012 for a similar finding in mice). Enhanced fear learning and impaired fear inhibition in adolescent rodents is mediated by changes to the neural circuitry underlying emotion regulation (for reviews, see Baker et al., 2014; Casey, Duhoux, & Cohen, 2010; Somerville, Jones, & Casey, 2010). Research identifying changes to this neural circuitry in adolescence has led to the development of the “imbalance” model, which posits that early-maturing subcortical structures (i.e., amygdala and hippocampus) are hyperactive whereas late-maturing cortical structures (i.e., PFC) are hypoactive during emotion regulation tasks at this developmental stage (Casey, Giedd, & Thomas, 2000; Somerville et al., 2010). In support of this model, Lau et al. (2011) used functional magnetic resonance imaging (fMRI) to demonstrate that threat/ safety discrimination learning in adolescence was mediated by relatively greater involvement of subcortical compared to cortical structures. In contrast, better discrimination between threat and safety cues in adults was correlated with greater dorsolateral prefrontal cortical activity (DLPFC). In that study, the Screaming Lady procedure was used whereby all subjects (i.e., adolescents aged 10–17 years and adults aged 18–50 years) were conditioned with one CSþ (i.e., a neutral face) paired with an aversive US (i.e., a loud scream and fearful facial expression—the threat cue) and a

Teens That Fear Screams

819

second stimulus that was not reinforced by a subsequent US (CS; i.e., a different neutral face—the safety cue). After each conditioning trial, subjects were asked to rate their level of fear to the CSþ and CS. Although there were no differences in fear ratings of the CSþ (i.e., the threat cue that actually predicted the aversive US) between the two age groups, adolescents had higher fear ratings to the CS (i.e., the safety cue that did not predict the aversive US) than did the adults. Lau et al. (2011) concluded that overgeneralization of fear from the CSþ to the CS in adolescents was driven by greater subcortical relative to cortical activity, providing support for the “imbalance” model. Combining evidence that adolescent humans show impaired threat/safety discrimination relative to adults (Lau et al., 2011), and adolescent rodents exhibit deficits in within-session extinction (Pattwell et al., 2012) and extinction retention (Kim et al., 2011; McCallum et al., 2010) relative to both juveniles and adults, it might be expected that adolescent humans exhibit a unique profile of impaired extinction learning and retention. However, there are very few studies examining fear extinction in healthy adolescents, and the findings have been mixed. In a study by Neumann, Waters, Westbury, and Henry (2008), 13–17-year-old subjects were conditioned with shapes (CSþ) paired with an unpleasant sound of metal scraping on a slate (US). Across several dependent measures including fear potentiated startle, skin conductance responses (SCRs), and self-report ratings of US expectancy, adolescents showed robust fear conditioning and within-session extinction. In contrast, using a social threat cue task, Haddad, Lissek, Pine, and Lau (2011) found that while adolescents aged 12–15 years old exhibited normal conditioning, they did not exhibit within-session extinction. Both Neumann et al. (2008) and Haddad et al.’s (2011) studies examined fear conditioning and extinction in healthy adolescents. In an earlier study conducted by Lau et al. (2008) using the Screaming Lady procedure described above, fear conditioning and extinction were compared in anxious versus healthy adolescents. Following conditioning, both anxious and healthy adolescents rated the CSþ as more fear provoking than the CS and the size of this difference was comparable across the two groups. Interestingly, both healthy and anxious adolescents showed little reduction in fear of the CSþ across the course of extinction. In all of the studies described in the paragraph above, adolescents were the only age group tested which meant that developmental comparisons of within-session extinction could not be made. To address this, Pattwell et al. (2012) employed a discriminative fear conditioning procedure and reported that adolescents (12–17 years

820

Den et al.

Developmental Psychobiology

old) showed poorer extinction learning as evidenced by attenuated differential SCRs to the CSþ versus CS when compared to children (5–11 years old) and a trend (p ¼ .078) toward poorer extinction learning compared to adults (18–28 years old). In contrast, a study by Britton et al. (2013) that compared anxious and healthy adolescents and adults on conditioning, extinction, and a follow-up threat/safety discrimination task revealed no age or diagnostic differences on physiological responses (i.e., startle and skin conductance) or subjective fear ratings (apart from anxious adolescents and adults rating both the CSþ and CS as more fearful after conditioning than healthy participants). As neither Pattwell et al. (2012) nor Britton et al. (2013) assessed extinction retention, it remains unclear whether adolescent humans show higher levels of fear relative to adults when tested after a delay (i.e., poor extinction retention), as has been found in adolescent rodents (e.g., Kim et al., 2011; McCallum et al., 2010). Studying the return of fear after extinction is clinically important because it partly explains relapse of successfully treated anxiety disorders. Another way to assess the return of fear in associative learning procedures is through reinstatement, which refers to the recovery of conditioned responses following exposure to the US after extinction (e.g., Rescorla & Heth, 1975). Reinstatement studies can be thought of as a model for stressinduced relapse of a treated anxiety disorder, and are also important in paving the way for the development of pharmacological or behavioral strategies to minimize relapse in a clinical setting (Haaker, Golkar, Hermans, & Lonsdorf, 2014). Although several studies have demonstrated reinstatement in adult subjects (for review, see Hermans et al., 2005), to date no study has compared adolescents and adults on fear reinstatement after extinction. Therefore, the first aim of the current study was to examine whether fear conditioning, extinction, extinction retention, and reinstatement differs between

adolescents and their parents, using the Screaming Lady procedure developed by Lau et al. (2008, 2011). We used two self-report measures: (1) scary ratings and (2) outcome expectancy ratings. In addition, using an eye tracker to assess attentional focus, we measured the latency of first fixation to the CSþ. Although eye tracking is a relatively novel procedure, the few studies conducted in adults suggest that individuals should orient faster toward a fearful cue relative to a neutral cue (Mogg, Millar, & Bradley, 2000; Onnis, Dadds, & Bryant, 2011). Furthermore, given that past research in adults has shown that fear conditioning and extinction are influenced by emotional disorders (reviewed in Lissek et al., 2005), a second aim of the current study was to determine whether symptoms of depression and anxiety impact fear conditioning, extinction, extinction retention, and reinstatement differently in adolescents and adults.

METHODS Subjects Forty-seven adults (38–57 years of age) and 70 adolescents (12–17 years of age) were recruited for the study through flyer distributions at local libraries, community centers, and doctor’s surgeries. Each participant was reimbursed for travel costs and time. Parents were used as adult controls to reduce the influence of extraneous variables that could explain developmental cohort differences beyond age, such as socioeconomic factors, family environment, and ethnicity (see Table 1). The study was approved by both the University of New South Wales ethics committee and the Macquarie University ethics review board, and all participants provided written informed consent. Parental assent for adolescent participation was also obtained, even if parents chose not to participate themselves. Participants were phoned within a few days after the study to ensure that there was no significant enduring distress. Of the adolescents tested, there were eight

Table 1. Demographics for Self-Report Data Demographic Gender (% female) Age in years (SD) Ethnicity (%) Australian Asian Other1 Family make-up (%) Two parent Single parent Step/blended 1

Adult Group Reinstated n ¼ 25

Adult Group Non-Reinstated n ¼ 21

Adolescent Group Reinstated n ¼ 30

Adolescent Group Non-Reinstated n ¼ 29

80.0 46.84 (5.17)

81.0 48.76 (6.36)

63.3 15.27 (1.44)

58.6 14.38 (1.61)

76.0 8.0 16.0

76.2 9.5 14.3

73.3 10.0 16.7

72.4 10.3 17.2

76.0 24.0 0

52.4 28.6 19.0

70.0 23.3 6.7

68.9 13.8 17.2

“Other” included Middle-Eastern, European, and South American descent.

Teens That Fear Screams

Developmental Psychobiology pairs of siblings, three of which were of the same sex. In two of these same sex sibling pairs, each member of the pair was allocated to a different experimental condition (i.e., reinstated and non-reinstated groups). However, one pair of same-sex siblings was randomly assigned to the same condition (i.e., both Group Reinstated). To account for this, an average of the scores from these two siblings was calculated and separate analyses with one less degree of freedom were carried out. The analyses yielded an identical pattern of results to the analysis including both siblings as independent subjects. Thus, the results reported here include the individual data from each member of the sibling pair rather than the average of the two. Design All participants underwent a differential conditioning procedure in which two faces, both with neutral expressions, were individually presented. One face (CSþ) was followed by the same face now expressing fear and a loud scream; the other face (CS) was not followed by anything. Extinction involved non-reinforced presentations of both CSs. Participants were randomly assigned to one of two conditions: Group Reinstated or Group Non-Reinstated. This resulted in four groups: (1) Adult Group Reinstated, (2) Adult Group Non-Reinstated, (3) Adolescent Group Reinstated, and (4) Adolescent Group Non-Reinstated. Materials and Apparatus Participants’ eye movements were recorded on a Tobii TX300 eye tracker, with the experimental task delivered using Tobii Studio (Version 3.1) software. All visual stimuli were presented on a 23 inch LCD monitor with screen resolution set to 1,920  1,080 pixels. Black and white photos of two female faces were counterbalanced as CSþ and CS (from the NimStim Face Stimulus Set; Tottenham et al., 2009). The duration of each CS presentation throughout the study was 8 s. The same face used as the CSþ, but now with a fearful expression, was used as the US, and lasted for 3 s in duration. This 3 s visual US was presented simultaneously with a 75 dB scream delivered through computer speakers located on either side of the monitor. All participants completed the Depression Anxiety Stress Scale (DASS-21; Lovibond & Lovibond, 1995). The DASS21 is a short questionnaire requiring individuals to rate on a 4-point scale ranging from 0 (never) to 3 (almost always) how often each statement has applied to them over the past week (e.g., “I couldn’t seem to experience any positive feelings at all” etc.) across three areas: depression, anxiety, and stress. The DASS-21 is a reliable and valid measure in both non-clinical and clinical adult samples (e.g., Henry & Crawford, 2005; Taylor, Lovibond, Nicholas, Cayley, & Wilson, 2005). While the depression subscale of the DASS21 is well-validated in adolescents (Szab
o, 2010), evidence suggests that the DASS-21 anxiety and stress subscales are poorly differentiated in adolescents relative to adults (Duffy, Cunningham, & Moore, 2005; Szab
o, 2010). Thus, in the current study, only scores from the depression subscale of the

821

DASS-21 were evaluated for their impact on conditioning, extinction, and relapse at test in adolescent participants. In contrast, scores from all three subscales of the DASS-21 were included when analyzing data for the adult participants. As an alternative to the anxiety subscale on the DASS-21 for the adolescents, the Spence Children’s Anxiety Scale (SCAS; Spence, 1998) was administered. The SCAS consists of 45 items assessing the presence of different anxiety disorders (e.g., separation anxiety disorder, social phobia, panics attacks etc.). On this measure, the individual is asked to rate the extent to which the statement (e.g., “I worry about things”) applies to them generally on a 4-point scale ranging from 0 (never) to 3 (always). Studies administering the SCAS to youth ranging from 7 to 19 years have reported high internal consistency (Essau, Olaya, Pasha, O’Callaghan, & Bray, 2012; Spence, 1998; Zhao, Xing, & Wang, 2012), good convergent validity (Muris, Schmidt, & Merckelbach, 2000; Orgil
es, Spence, Marzo, M
endez, & Espada, 2014), and good discriminant validity (Whiteside & Brown, 2008). Procedure Participants attended a single session at The University of New South Wales. Following a brief orientation to the experimental room and the eye tracking equipment, participants were told that if they felt excessively anxious at any point in time they were free to terminate the experiment without penalty. The study was described as an experiment investigating differences in the way adolescents and adults learn and unlearn fear. Participants signed consent forms, after which they completed the DASS-21; adolescent participants also completed the SCAS. After completing the questionnaires, participants were taken into the experimental room and instructed on how to complete the self-report rating scales that would appear on the computer monitor. The experimenter then told each participant that they would see faces on the computer screen and their task was to figure out which face would be followed by something “surprising”. At the start of each experimental phase, a calibration trial occurred whereby participants were asked to follow a moving dot with both eyes on the computer screen to ensure that their eye movements were detected at nine different locations. This process was repeated if sufficient eye movements were not detected as determined by the Tobii Studio (Version 3.1) Software. There were four experimental phases of the study: preacquisition, conditioning, extinction, and test. Eye tracking data were collected immediately after each phase, followed by self-report ratings. Phases

Preacquisition. Eight trials of non-reinforced CS presentations (four CSþ and four CS) occurred during this stage so that participants habituated to the faces. Preacquisition trials were separated by an inter-trial interval (ITI) of 4 s. Conditioning. Conditioning began immediately after preacquisition. There were 14 acquisition trials: 7 CSþ trials and 7

822

Den et al.

CS trials (ITI ¼ 10 s). The trial order was pseudo-randomized, with the restriction that no more than three of the same CS type occurred in a row. During acquisition, one face (CSþ) was followed by the US on 5 out of the 7 trials (i.e., on 2 of the trials, the CSþ was not followed by a US). At the end of conditioning, the experimenter entered the room and had a discussion with the participant (lasting 2-3 min) asking several questions about the computer program (e.g., “did you notice a pattern?” and “what did the two faces look like?”). Participants were also asked if they were feeling comfortable enough to continue with the experiment.

Extinction. There were 10 non-reinforced trials during extinction. Specifically, each CS was presented 5 times without the US (ITI ¼ 8 s) in a pseudo-randomised order. At the end of extinction, participants were taken out of the experimental room and asked to wait in another room for 10 min. During this time, participants completed a demographics questionnaire.

Developmental Psychobiology screen was blank. CS location was counterbalanced across the two trials. Only data for the first side-by-side trial is reported.

Latency of First Fixation to the CSþ. This measure was used to assess how rapidly participants oriented to the CSþ relative to the CS. A difference score was calculated at each experimental phase to compare the latency of first fixation (defined as looking for  10 ms) to the CSþ relative to the CS: Difference score ¼ (Latency of first fixation to [CSþ]) – (Latency of first fixation to [CS]) On this measure, low scores indicate faster orientation to the CSþ relative to the CS. In order to determine the change in latency of first fixation to the CSþ relative to the CS from extinction to test, a relapse score was calculated using the following formula: Relapse at test ¼ (Difference score at test) – (Difference score at extinction) Lower values on this measure indicate greater reinstatement (i.e., faster orienting towards to the CSþ).

Test for Relapse. Participants were then taken back to the testing room where those in Group Reinstated received two 3 s USs, separated by an ITI of 8 s, immediately followed by the 2 side-by-side images of the CSþ and CS- faces, and then the self-report rating questions. For participants in Group Non-Reinstated, the test was identical apart from a blank screen being presented instead of the USs. Measures

Self-Report Ratings. A small referent picture of the CS appeared above questions which asked the participants to provide scary ratings (“How scary is this face?”), and outcome expectancy ratings (“How likely will this face be followed by a scream?”), which ranged from 0 (not at all) to 8 (very much so). Both questions were asked after each phase regarding the CSþ and CS-, with the exception that the outcome expectancy question did not occur after the preacquisition session in order to maintain the surprisingness of the scream US. Across all experimental phases and for all self-report ratings, difference scores were obtained and analyzed using the following formula: Difference Score ¼ ([CSþ] rating) – ([CS] rating) To determine the change in scary and outcome expectancy ratings from extinction to test in both Group Reinstated and Group Non-Reinstated, a relapse score was calculated using the difference scores from test and extinction: Relapse at test ¼ (Difference score at test) – (Difference score at extinction) High scores on the relapse at test measure indicate reinstatement on both the scary and outcome expectancy selfreport measures.

Eye Tracking. Immediately after each experimental phase, a central fixation point (a white cross) appeared in the middle of the computer screen. The two faces used as CSs then appeared on the screen side-by-side. Two such trials occurred, each lasting 8 s, separated by a 4 s ITI during which the

Exclusions and Statistical Analyses

Exclusions for Self-Report Data. Of the 117 participants, 10 adolescents withdrew from the study due to aversion to the scream; no adults withdrew from the study for this reason. Data from one adolescent and one adult were also excluded due to equipment malfunction, resulting in a total of 105 participants (59 adolescents and 46 adults). Three additional participants (two adults and one adolescent) were unable to provide ratings for the outcome expectancy measure at extinction and test due to software problems; however, their scores on scary self-report measures, as well as their outcome expectancy rating at the end of conditioning, were included in the analysis. The final sample sizes for each experimental group are presented in Table 1.

Exclusions for Eye Tracking Data. When assessing changes in the latency of first fixation to the CSþ, participants were excluded if they failed to look at the CSþ or CS for the first side-by-side image presented during any of the experimental phases (i.e., output from the eye tracker equal to “8 s”). A total of 23 participants were excluded from the analysis for this reason, with the number of exclusions for each group as follows: Adult Group Reinstated, n ¼ 1; Adult Group Non-Reinstated, n ¼ 2; Adolescent Group Reinstated, n ¼ 11; Adolescent Group Non-Reinstated, n ¼ 9. Separate analyses were conducted for the two self-report measures (i.e., scary and outcome expectancy), and latency of first fixation to the CSþ. Given that conditioning and extinction took place prior to the reinstatement manipulation, analyses concerning these phases were averaged across the reinstatement condition factor (further, analyses did not yield any significant effect of condition for these phases). Also, while the effects of gender were not examined in adults due to the limited number of males in the sample, an analysis of the adolescents showed that gender did not have any significant effects on self-report ratings at conditioning,

Teens That Fear Screams

Developmental Psychobiology extinction, or test (largest F1, 57 ¼ 3.00, p > .08, hp ¼ .05). Similarly, no gender differences emerged on the latency of first fixation to the CSþ measure at any of the experimental phases (largest F1, 37 ¼ 2.39, p ¼ .13, hp2 ¼ .06). As such, gender was not included as a between-subject factor in any analyses. To assess whether program version (i.e., which face was allocated to the CSþ) affected the self-report ratings, separate 2  2 factorial analyses were conducted on scary ratings at preacquisition, with the first factor being age (adolescents vs. adults) and the second factor being program version (version 1 [i.e., brunette lady as CSþ and blonde lady as CS] or version 2 [i.e., blonde lady as CSþ and brunette lady as CS]). Surprisingly, there was a significant age x program interaction for the scary difference scores, F1, 101 ¼ 8.38, p ¼ .005, hp2 ¼ .077. This interaction was driven by adults exhibiting higher scary ratings of the “blonde lady” relative to the “brunette lady” at preacquisition, with the majority of these adults coming from the group in which the blonde lady would later scream (i.e., the CSþ). Therefore, across all analyses of self-report data, program version was included as a co-variate, and ANCOVAs are reported. In contrast, there were no significant program version effects on the eye tracking measure, largest F1, 78 ¼ .16, p > .69, hp2 ¼ .002. As such, ANOVAs rather than ANCOVAs are reported for the latency of first fixation to the CSþ measure. 2

Conditioning and Extinction. For all self-report data, separate mixed-design ANCOVAs were done with program version as the co-variate, age as the between-subject factor (i.e., adolescents vs. adults), and phase as the repeated measure. Only two phases were analyzed at any one time— that is, separate analyses were carried out from preacquisition to conditioning and from conditioning to extinction. The analysis of eye tracking data was identical to that of selfreport data apart from program version not being used as a co-variate.

Test for Extinction Retention and Reinstatement. For self-report data, a 2  2 factorial ANCOVA on relapse at test (i.e., test difference minus extinction difference) was done with the first factor being age (i.e., adolescents vs. adults), the second factor being condition (i.e., reinstatement vs. no reinstatement), and the co-variate being program version. As before, program version was not used as a co-variate in the analysis of relapse on the eye tracking measure.

Regression of Anxiety and Depression on Self-Report Ratings. We also examined whether symptoms of anxiety and depression in both age groups predicted changes in selfreport ratings at each of the different experimental phases. In adults, scores on the depression, anxiety, and stress subscales of the DASS-21 did not predict changes in self-report ratings at any of the experimental phases, and as such, the hierarchical regression data for adults are presented in the supplementary analyses section (see Appendix B for bivariate correlations and Appendix C for hierarchical regression analyses). In the adolescent sample, hierarchical multiple regression was used

823

to assess the contribution of depression (i.e., scores on the DASS-21 depression subscale) and anxiety (i.e., scores on the SCAS) to scary and outcome expectancy ratings across conditioning, extinction, and test (guided by a correlational analysis; see Appendix A). When analyzing the impacts of depression and anxiety on self-report ratings at conditioning, scores at preacquisition were entered at Step 1, with depression and anxiety scores entered simultaneously at Step 2 (see Table 2). Note that for the analysis of outcome expectancy ratings at conditioning, depression and anxiety scores were entered simultaneously at Step 1, with no earlier step entered given that participants did not rate outcome expectancies at preacquisition. For the regression analysis at extinction, selfreport ratings at conditioning were entered at Step 1 and depression and anxiety at Step 2 (see Table 2). To assess relapse at test, the dichotomous variable of condition (i.e., Group Reinstated or Group Non-Reinstated) was entered at Step 1, with depression and anxiety scores entered at Step 2 (extinction was not entered as an earlier step given that the relapse score is a difference score which already accounts for extinction ratings; see Table 2).

Association Between Anxiety, Depression, and Latency of First Fixation to the CSþ. Given adults did not show changes on the eye tracking measure, hierarchical regression analyses were carried out in adolescents only to assess whether scores on the DASS-21 and SCAS affected latency of first fixation to the CSþ. A summary of these data are presented in the supplementary analyses section (see Appendices D and E).

RESULTS Scary Self-Report Ratings Preacquisition to Conditioning. Mean scary ratings are shown in Figure 1. There was a significant main effect of phase, F1, 102 ¼ 62.49, p < .001, hp2 ¼ .38, indicating an increase in self-reported scary ratings from preacquisition to conditioning. The main effect of age was not significant, F1, 102 ¼ .10, p ¼ .75, hp2 ¼ .001, but there was a significant phase x age interaction, F1, 102 ¼ 4.23, p ¼ .042, hp2 ¼ .04. Despite the significant interaction, follow-up independent t-tests failed to reveal significant age differences in scary ratings at either preacquisition or conditioning, largest t103 ¼ .85, p > .39. Furthermore, paired samples t-tests confirmed an increase in scary ratings from preacquisition to conditioning in adolescents, t58 ¼ 6.92, p < .001, and adults, t45¼ 4.26, p < .001. Conditioning to Extinction. There was a significant main effect of phase, F1, 102 ¼ 14.74, p < .001, hp2 ¼ .126, with a reduction in self-reported scary ratings from conditioning to extinction, indicative of good

824

Den et al.

Developmental Psychobiology

Table 2. Hierarchical Regression Findings Examining the Prediction of Self-Report Ratings in Adolescents Based on Anxiety and Depression Scores Outcome Scary ratings Conditioning

Extinction

Relapse at test

Outcome expectancy ratings Conditioning Extinction

Relapse at test

DR2

Predictors

B

SE B

b

R2

Step 1: Preacquisition rating Step 2: DASS-depression score Total SCAS score Step 1: Conditioning rating Step 2: DASS-depression score Total SCAS score Step 1: Condition (reinstated/non-reinstated) Step 2: DASS-depression score Total SCAS score

.420 .008 .035 .375 .096 .003 .310 .010 .021

.134 .047 .023 .094 .034 .017 .486 .046 .023

.385 .023 .205 .471 .344 .025 .085 .033 .143

.148 .195

.148 .047

.221 .346

.221  .125

.007 .024

.007 .017

Step 1: DASS-depression score Total SCAS score Step 1: Conditioning rating Step 2: DASS-depression score Total SCAS score Step 1: Condition (reinstated/non-reinstated) Step 2: DASS-depression score Total SCAS score

.043 .018 .031 .117 .015 2.331 .012 .006

.060 .029 .087 .036 .018 .623 .060 .029

.106 .088 .047 .444 .141 .450 .028 .031

.012

.012

.002 .171

.002  .169

.203 .205

.203 .002

p-Values







.003 .861 .130 .001 .006 .835 .526 .829 .351 .472 .548 .728 .002 .409 .001 .845 .824

Note: p < .05.  p < .01.

extinction learning (see Fig. 1). Neither the main effect of age nor the phase x age interaction was significant, largest F1, 102 ¼ .78, p > .37, hp2 ¼ .008.

Outcome Expectancy Self-Report Ratings

Relapse at Test. Scary relapse scores (test minus extinction) are presented in Figure 2. Neither the main effect of age nor the age x condition interaction were significant, largest F1, 100 ¼ 1.56, p ¼ .21, hp2 ¼ .015. The main effect of condition was significant, F1, 2 100 ¼ 5.14, p ¼ .02, hp ¼ .049, with those participants in Group Reinstated giving higher scary ratings of the CSþ than those in Group Non-Reinstated.

Conditioning to Extinction. There was a significant main effect of phase, F1, 99 ¼ 57.47, p < .001, hp2 ¼ .367, with self-reported outcome expectancies decreasing from conditioning to extinction (i.e., extinction learning; see Fig. 3). There was also a significant main effect of age, F1, 99 ¼ 7.57, p ¼ .007, hp2 ¼ .071, due to adolescents exhibiting lower outcome expectancy scores than adults. The lower outcome expectancies reflect poorer discrimination between the CSþ and CS in adolescents relative to adults (see the

FIGURE 1 Mean (SEM) scary self-report ratings at preacquisition, conditioning, and extinction for adolescents (open circle) and adults (closed circle).

FIGURE 2 Mean (SEM) scary self-report ratings at test in adolescents and adults exposed to either two reinstating USs (Group Reinstated) or a blank screen for the equivalent amount of time (Group Non-Reinstated).

Developmental Psychobiology

FIGURE 3 Mean (SEM) outcome expectancy self-report ratings at conditioning and extinction for adolescents (open circle) and adults (closed circle).

General Discussion for further exploratory analysis of this age difference). Relapse at Test. Mean relapse scores (test minus extinction) are shown in Figure 4. The main effect of age and the age x condition interaction were not significant, largest F1, 97 ¼ 1.43, p > .23, hp2 ¼ .015, but the main effect of condition was, F1, 97 ¼ 13.94, p < .001, hp2 ¼ .126, with Group Reinstated exhibiting significantly higher outcome expectancy ratings than Group Non-Reinstated (i.e., the reinstatement effect was observed).

Latency of First Fixation to the CSþ Preacquisition to Conditioning. Mean difference scores for latency of first fixation to the CSþ at

Teens That Fear Screams

825

FIGURE 5 Mean (SEM) latencies of first fixation to the CSþ relative to the CS in adolescents (open circle) and adults (closed circle) at preacquisition, conditioning, and extinction.

preacquisition and conditioning are presented in Figure 5. The main effect of phase was not significant, F1, 2 80 ¼ .46, p ¼ .50, hp ¼ .006, although the main effect of age was, F1, 80 ¼ 5.21, p ¼ .025, hp2 ¼ .061, indicating that averaged across preacquisition and conditioning, adolescents oriented faster to the CSþ relative to the CS than adults. There was a trend toward a phase x age interaction, F1, 80 ¼ 3.27, p ¼ .074, hp2 ¼ .039. Follow-up independent samples t-tests confirmed faster orientation toward the CSþ in adolescents compared to adults at conditioning, t80 ¼ 2.31, p ¼ .02, but not preacquisition, t80 ¼ .096, p > .92. Furthermore, posthoc paired samples t-tests showed a significant decrease in latencies from preacquisition to conditioning in adolescents, t38 ¼ 2.24, p ¼ .03, but not in adults, t42 ¼ .70, p > .48. Thus, only the adolescents showed conditioning on this measure. Conditioning to Extinction. Mean difference scores for latency of first fixation to the CSþ at conditioning and extinction are presented in Figure 5. The main effect of age and the phase x age interaction were not significant, largest F1, 80 ¼ 2.30, p > .13, but there was a significant main effect of phase, F1, 80 ¼ 11.19, p ¼ .001, hp2 ¼ .123, with an increase in the latency of first fixation to the CSþ relative to the CS from conditioning to extinction. In other words, orienting to the CSþ was slower at extinction than conditioning, indicating reduced hypervigilance to the CSþ.

FIGURE 4 Mean (SEM) outcome expectancy self-report ratings at test in adolescents and adults exposed to either two reinstating USs (Group Reinstated) or a blank screen for the equivalent amount of time (Group Non-Reinstated).

Relapse at Test. Given that adults did not show conditioning on this measure (i.e., latencies did not differ from preacquisition to conditioning), reinstatement could not be assessed in the adults. Therefore, only the mean relapse scores (test minus extinction) for adolescents are presented in Figure 6. Adolescents in

826

Den et al.

FIGURE 6 Mean (SEM) relapse difference scores (i.e., test minus extinction) for latency of first fixation to the CSþ relative to the CS in adolescents exposed to either two reinstating USs (Group Reinstated) or a blank screen for the equivalent amount of time (Group Non-Reinstated). Lower scores indicate greater relapse (i.e., faster orientation to the CSþ at test compared to extinction).

Developmental Psychobiology

association between DASS-21 depression scores and outcome expectancy at extinction (p ¼ .002). Specifically, an increase of one standardized unit on the depression subscale predicted an increase of .44 units at extinction on the outcome expectancy score. Thus, adolescents with elevated depressive symptoms showed poorer extinction as they continued to rate the CSþ as more likely to scream than the CS, despite numerous trials in which the CSþ was not reinforced by the US during extinction. Lastly, although the condition factor (i.e., reinstatement or non-reinstatement) significantly predicted outcome expectancy at test with reinstated participants rating outcome expectancy as .45 standardized units higher than non-reinstated participants (p < .001), neither depression nor anxiety scores predicted relapse over and above condition (smallest p ¼ .82).

Additional Analyses the reinstated group showed significantly more relapse (i.e., a greater reduction in latency indicating faster orientation to the CSþ from extinction to test) than those in the non-reinstated group, t37 ¼ 2.05, p ¼ .047. Therefore, exposing adolescent participants to two reinstating USs after extinction led to greater attention towards the CSþ.

Regression of Anxiety and Depression on SelfReport Ratings in Adolescents Scary Ratings. Neither depression nor anxiety scores predicted scary ratings at conditioning (all ps > .13; see Table 2), but depression scores significantly predicted scary ratings at extinction over and above scary ratings at conditioning (p < .001). That is, an increase of one standardized unit on the DASS-21 depression subscale led to an increase of .34 standardized units on the scary self-report measure at extinction, indicating poorer extinction on this measure in adolescents with elevated depressive symptoms. In contrast, anxiety scores failed to predict any unique variance on scary ratings at extinction (p ¼ .83). At test, none of the variables entered into the model (i.e., condition, depression, or anxiety) significantly predicted changes in relapse (all ps > .35). Outcome Expectancy Ratings. Anxiety and depression scores did not predict any unique variance in outcome expectancies at conditioning (all ps > .47; see Table 2). Neither outcome expectancy at conditioning nor anxiety as measured on the SCAS predicted outcome expectancy at extinction (all ps > .40). However, once again, depression was a significant predictor, with an

Additional hierarchical analyses were performed to explore whether depression, anxiety, and stress symptoms as measured on the DASS-21 predicted self-report ratings in adults (with the bivariate correlations [Appendix B] guiding hierarchical regression analysis [Appendix C]). Scores on these subscales failed to predict any unique variance on scary or outcome expectancy ratings across conditioning, extinction, and relapse at test, although there was a trend toward increased anxiety scores on the DASS-21 being associated with increased scary ratings of the CSþ relative to the CS at test (p ¼ .06, an increase of one standardized unit on the anxiety subscale predicted an increase of .11 units on the scary relapse score at test; see Appendix C). Hierarchical regression analyses were also carried out on the eye tracking measure in adolescents (presented below, see Appendices D and E). The same output for adults is not presented in the Appendix given that adults showed no changes in latency of first fixation to the CSþ from preacquisition to conditioning. In adolescents, scores on the depression subscale of the DASS-21 significantly predicted latency of first fixation to the CSþ at conditioning, over and above preacquisition latencies and SCAS scores (p ¼ .015; see Appendix E). That is, an increase of one standardized unit on the depression subscale was associated with a decrease of .407 s in time taken to look at the CSþ relative to the CS at conditioning (i.e., depressive symptoms predicted faster orienting to the CSþ at conditioning). In contrast, neither depression nor anxiety scores predicted changes in latency of first fixation to the CSþ at extinction or relapse at test in adolescent participants (all ps > .38).

Developmental Psychobiology

GENERAL DISCUSSION In this study, we compared adolescents and adults on fear conditioning, extinction, extinction retention, and reinstatement using subjective self-report and a physiological eye tracking measure. Adolescents showed stronger conditioning than adults on the latency of first fixation to the CSþ measure. There were no age differences in extinction learning on either of the selfreport measures, and no developmental comparisons of extinction could be made on the eye tracking measure as adults did not show evidence of acquisition. There were no age differences in extinction retention or reinstatement on the self-report measures, and once again, no developmental comparisons on the eye tracking measure could be made at test. However, adolescent reinstated participants oriented faster to the CSþ than non-reinstated participants at test suggesting greater hypervigilance toward threat following postextinction US exposures. A novel finding of this study was that in adolescents, depression scores on the DASS-21 uniquely predicted self-report and eye tracking responses at conditioning and extinction, over and above anxiety scores on the SCAS. The finding that adolescents showed stronger conditioning relative to adults on the latency of first fixation to the CSþ measure is consistent with previous studies reporting elevated threat responding during adolescence (Den & Richardson, 2013; Lau et al., 2011). Specifically, in the present study, adolescents showed a decrease in the latency of first fixation to the CSþ from preacquisition to conditioning. Interestingly, this same pattern of attentional biases toward threat has been well-documented in clinically anxious adult populations (Bar-Haim, Lamy, Pergamin, BakermansKranenburg, & Van Ijzendoorn, 2007). In contrast, nonanxious adults exhibit no attentional biases toward threat (Bar-Haim et al., 2007), and this is consistent with the findings of the current study in which a community sample of adults did not orient faster toward the CSþ from preacquisition to conditioning. Another similarity can be drawn between clinically anxious adults and the community sample of adolescents used in the current study. That is, we found a main effect of age on the outcome expectancy measure from conditioning to extinction with adolescents showing lower outcome expectancies than adults. Post-hoc t-tests revealed that although there were no differences in CSþ expectancy ratings between adolescents and adults at conditioning (M ¼ 5.88, SD ¼ 1.25 for adolescents, and M ¼ 6.07, SD ¼ 1.70 for adults; t103 ¼ .61, p > .54), or extinction (M ¼ 2.60, SD ¼ 2.03 for adolescents, and M ¼ 3.18, SD ¼ 2.07 for adults; t100 ¼ 1.41, p > .16), adolescents rated the CS as significantly

Teens That Fear Screams

827

more likely to be followed by a scream at the end of conditioning (M ¼ 1.78, SD ¼ 1.97 for adolescents, M ¼ 1.07, SD ¼ 1.48 for adults; t103 ¼ 2.05, p ¼ .043), although this difference was not significant at the end of extinction (M ¼ 1.59, SD ¼ 1.92 for adolescents, M ¼ 1.20, SD ¼ 1.82 for adults; t100 ¼ 1.02, p > .31; see the Introduction Section for a similar finding by Lau et al. (2011) in which non-anxious adolescents exhibited overgeneralization of fear ratings from the CSþ to the CS after conditioning). Similarly, in a study by Dibbets, van den Broek, and Evers (2014), adults with high levels of self-reported anxiety symptoms showed overgeneralization of outcome expectancies from the CSþ to the CS at the end of a differential fear conditioning task. Taken together, the similarities between the community sample of adolescents in the current study and anxious adults in previous studies provide a potential explanation for why the majority of anxiety disorders emerge during adolescence. That is, greater attention to threat, as well as difficulty discriminating between cues signaling safety and threat (i.e., overgeneralization), may play a causal role in the development of adolescent anxiety disorders. There are a number of discrepancies between the results of this study and previous studies examining fear conditioning and extinction in adolescence. For example, Pattwell et al. (2012) found no age differences in conditioning but reported impaired extinction learning in adolescents relative to children and adults. Furthermore, Neumann et al. (2008) and Lau et al. (2008) reported that adolescents did not show withinsession extinction. In contrast, in the present study, adolescents showed signs of stronger conditioning (on the eye tracking measure) and comparable extinction learning relative to adults. One explanation for why adolescents did not show impaired extinction relative to adults in this study is that the effect observed by Pattwell et al. (2012) was small (i.e., a trend of p ¼ .078). Small effects are more difficult to replicate and rely on specific parameters. Notably, a later study by Britton et al. (2013) also failed to replicate the age difference in extinction learning between adolescents and adults. Given these mixed findings on extinction learning, more research is required in order to clarify whether human adolescents do indeed show poorer extinction relative to adults. In addition to comparing adolescents and adults on extinction learning, we also assessed whether there might be age differences in extinction retention after a delay. As described earlier, McCallum et al. (2010) reported extinction retention deficits in adolescent relative to juvenile and adult rats. In contrast, in the present study, follow-up analyses examining extinction retention in Group Non-Reinstated revealed no significant differences

828

Den et al.

between adolescents and adults on any measure (data not reported here, largest t48 ¼ 1.17, p > .24). One potential explanation for this finding is that whereas the test in McCallum et al. occurred after a 24 hr delay, in the present study there was only a 10-min delay separating extinction and test. We selected a short interval between extinction and test in the current study for two reasons. First, it was important to minimize attrition in the adolescent participants given that previous studies have shown an increase in drop-out rates when participants are requested to return for a second session at a later date (Grillon, 2002; Lau et al., 2008). Second, evidence suggests that testing for relapse 24 hr after extinction increases spontaneous recovery (reviewed in Haaker et al., 2014), which would have made it more difficult to observe a reinstatement effect. Therefore, to assess developmental differences in long-term extinction retention in humans, future studies using a delay of at least 24 hr between extinction and test are needed. On the self-report measures, both adolescents and adults showed reinstatement. However, it is worth noting that upon closer inspection of Figures 2 and 4 (i.e., scary and outcome expectancy relapse at test scores, respectively), adolescents in both the reinstated and non-reinstated condition showed an increase in ratings from extinction to test. In contrast, although adults in the reinstated condition showed an increase in scary and outcome expectancy ratings from extinction to test, adults in the non-reinstated condition showed a slight reduction in scary and outcome expectancy ratings, suggesting that their fear toward the CSþ, as well as their expectancy that a scream would follow, decreased over the temporal interval separating extinction and test. Thus, in the present case, it may be that the adolescents begin to exhibit spontaneous recovery from extinction at shorter intervals than adults, although more systematic comparisons are needed to conclusively support this possibility. We are unable to make any conclusions regarding developmental differences in reinstatement on the latency of first fixation to the CSþ measure as adults failed to show changes across conditioning and extinction. It may have been the case that individual differences in whether adult participants engaged in threat hypervigilance (i.e., faster orientation to the CSþ from preacquisition to conditioning) or threat avoidance (i.e., slower orientation to the CSþ from preacquisition to conditioning) masked overall changes on this eye tracking measure (for review, see Hofmann, Ellard, & Siegle, 2012; MacLeod, Mathews, & Tata, 1986; Zvielli, Bernstein, & Koster, 2014). Indeed, in one study by Zvielli et al. examining attention biases to numerous types of threatening stimuli (e.g., angry faces, attacking dogs, and violent scenes) on a visual

Developmental Psychobiology

dot probe task, 34% of participants exhibited an attention bias toward threat for all categories, 20.8% exhibited an attention bias away from threat for all categories, and 34% displayed an attention bias toward threat for some categories and away from threat for others. Zvielli et al.’s study used a sample of anxious adults, yet this same variability may apply to the community sample of adults used in the current study. Therefore, to assess whether individual differences might have masked changes in eye tracking responses, we divided adult participants into those who showed a decrease (i.e., Group Decrease, n ¼ 20) versus those who showed an increase (i.e., Group Increase, n ¼ 22) in the latency of first fixation to the CSþ from preacquisition to conditioning (with one participant excluded for showing a 0% change in latency from preacquisition to conditioning). Group Decrease exhibited greater hypervigilance toward threat from preacquisition to conditioning (i.e., faster orientation to the CSþ from preacquisition to conditioning) and a reduction in threat hypervigilance by the end of extinction (i.e., slower orientation to the CSþ from conditioning to extinction), whereas Group Increase showed greater threat avoidance from preacquisition to conditioning (i.e., slower orientation to the CSþ from preacquisition to conditioning), although this did not change from conditioning to extinction (for statistical analyses and graphs, see Appendix F). However, there were no group or condition (i.e., reinstated vs. nonreinstated) differences in extinction retention after a delay or reinstatement on the latency measure. In contrast to this nearly bi-modal pattern of responding in the adults, adolescents exhibited attention biases consistent with the adult “decrease” group (i.e., threat hypervigilance and faster orientation to the CSþ from preacquisition to conditioning). Adolescent subjects also clearly showed a reinstatement effect on this latency measure (i.e., faster orientation to the CSþ in reinstated participants). Thus, based on the eye tracking results of this study, adolescents exhibit a greater propensity toward threat hypervigilance, possibly reflecting a distinctive feature of fear learning in adolescence that may uniquely contribute to relapse at this age. To date, only a few studies have examined the effects of anxiety on fear conditioning and extinction in adolescence. Specifically, Lau et al. (2008) and Britton et al. (2013) reported that adolescents with a clinical diagnosis of an anxiety disorder had higher fear ratings of both the CSþ and CS during conditioning and extinction, relative to healthy controls. In both of those studies, however, there were no differences between healthy and anxious adolescents in the rates of fear conditioning or extinction. Similarly, in Pattwell et al.’s

Developmental Psychobiology

(2012) study using a nonclinical sample of adolescents, trait anxiety measured on the Spielberger State-Trait Anxiety Inventory-Trait (STAI-T; Spielberger, Gorsuch, & Lushene, 1970) was not correlated with fear conditioning or extinction. Consistent with these studies, anxiety symptoms measured on the SCAS (Spence, 1998) failed to predict any differences on subjective self-report or eye tracking measures at conditioning, extinction, or test in the present study (see Table 2 for self-report measures; see Appendixes D and E for eye tracking measures). Surprisingly however, increases in depressive symptoms (based on DASS-21 depression subscale scores) in adolescent subjects predicted faster orientation towards the CSþ at conditioning. Furthermore, depressive symptoms predicted poorer extinction learning on the scary and outcome expectancy measures (although depressive symptoms did not predict changes in extinction retention after a delay or reinstatement, indicating that these effects on conditioning may be transient rather than long lasting). One explanation for why depression predicted changes in conditioning and extinction can be extrapolated from Baune, Fuhr, Air, and Hering’s (2014) review summarizing a variety of deficits in depressed adolescents completing executive functioning tasks. Executive functioning is a neuropsychological construct used to describe the regulation of cognitive processes such as flexibility, inhibition, and problem solving (reviewed in Chan, Shum, Toulopoulou, & Chen, 2008). There is considerable overlap between the neural structures mediating executive functioning and emotion regulation (reviewed in Rogers et al., 2004); that is, both rely on activity in several parts of the PFC (Britton et al., 2013; Lau et al., 2011; reviewed in Rogers et al., 2004), suggesting that executive functioning and emotion regulation are related abilities. Given that the PFC continues to mature and is reorganized during adolescence, and PFC damage is associated with elevated symptoms of depression (reviewed in George, Ketter, & Post, 1994), adolescents may be more vulnerable to depression and subsequent impairments on tasks requiring executive functioning and/or emotion regulation. These findings, alongside reports that adolescents often present with heterogeneous symptoms of mental illness (Kessler & Wang, 2008), support the need for future studies to compare fear conditioning and extinction in adolescents with anxiety disorders, major depressive disorders, or mixed anxiety–depressive disorders. Interestingly however, adult self-report ratings in the present study were unaffected by symptoms of depression (see Appendixes B and C). Consistent with this result, Jovanovic et al. (2010) reported that trauma-exposed adults meeting the diagnostic criteria for major depressive disorder (MDD) did not differ from non-depressed

Teens That Fear Screams

829

controls on a discriminative fear conditioning task, with both groups expressing fear to the threat CSþ and inhibiting fear to the safe CS. Depressed individuals were also able to inhibit fear on a safety transfer test where the CSþ and CS were presented simultaneously, and once again did not differ from non-depressed controls. In contrast, patients in that same study with a diagnosis of post-traumatic stress disorder (PTSD) failed to discriminate between threat and safety cues (i.e., exhibited comparably high levels of fear potentiated startle to the CSþ and CS), and showed little safety transfer relative to controls. From these results, Jovanovic et al. concluded that deficits in fear inhibition are specific to PTSD and not MDD (although participants meeting criteria for both disorders showed the greatest deficits). In the current study, symptoms of anxiety as measured on the DASS-21 did not predict any unique variance in fear learning or inhibition in adults, but this failure to observe an effect of anxiety may reflect reduced symptom severity in the community sample used (i.e., less severe symptoms of anxiety than would be expected in the sample of individuals diagnosed with PTSD in Jovanovic et al.’s study). It is important to acknowledge that there are a number of limitations to the current study. Firstly, the screaming lady procedure was poorly tolerated by the adolescent participants. Specifically, 10 participants withdrew because the US was too fear-provoking, and 20 did not yield good eye tracking data due to movement. These exclusions call into question whether the included participants reflected the general adolescent population, or whether there was an unmeasured third variable that could have produced a sample that was non-representative of adolescents. One possible candidate for this variable could be pre-existing levels of anxiety or depression, and it may have been the case that adolescent participants with higher scores on either the DASS-21 depression subscale or SCAS were more likely to drop-out or avoid looking at the monitor. However, follow-up t-tests comparing included versus excluded participants revealed no significant differences in DASS-21 depression or SCAS scores (all ps > .27). Although it appears as though the included versus excluded distinction is not based on anxiety or depressive symptoms, it is worth noting that we did not assess several other important factors such as psychiatric history, strength of parent/caregiver attachment, or cognitive ability, making it difficult to determine the degree to which our sample was representative of the general population. To address this issue in the future, it would be useful to conduct a structured clinical interview prior to commencing the study to allow for an assessment of whether the factors described above might alter fear conditioning and extinction in adolescents.

830

Den et al.

A second limitation was the large stimulus effect for adults who expressed greater fear toward one stimulus over the other during the preacquisition phase. This difference may have influenced conditioning, extinction, and reinstatement, and to compensate for this difference, we included program version (i.e., whether the “blonde” or “brunette” lady screamed) as a covariate when analyzing all self-report data. Furthermore, to ensure that this stimulus effect was not driving the developmental differences reported, we performed several additional analyses whereby participants were excluded for having a scary rating difference score that was greater than an absolute value of 4 at preacquisition. The results of this analysis, presented in Appendix G, suggest that differences in scary ratings between adolescents and adults at preacquisition did not account for the majority of results reported here. Despite these limitations, the findings presented in this study support the growing body of evidence that adolescents show a unique profile of fear learning, characterized by greater generalization and increased attentional biases toward threat. There is also evidence that adolescents found the US in this study much more aversive than did adults. First, 10 adolescents discontinued the study after the first scream US whereas no adults dropped out for this reason. Second, as a group, the adolescents showed threat hypervigilance on the eye tracking measure from preacquisition to conditioning whereas adults did not. This age difference is clinically important as it suggests that exposure to the same “trauma” may have more adverse consequences for adolescents compared to adults. In other words, exaggerated fear responding and threat hypervigilance in adolescence may partly contribute to the increased prevalence of anxiety disorders at this age (Browning, Holmes, Murphy, Goodwin, & Harmer, 2010). There is evidence to suggest that attention bias modification training, which involves shifting attention away from threat, leads to reduced anxiety in adult and child clinical populations (Amir, Beard, Burns, & Bomyea, 2009; Bar-Haim, Morag, & Glickman, 2011; Schmidt, Richey, Buckner, & Timpano, 2009). Furthermore, attention retraining away from threat has been shown to result in greater prefrontal cortical regulation of amygdala responses to emotional stimuli in healthy adults (Browning et al., 2010). Given that heightened fear learning in adolescence reflects neural changes within the corticolimbic circuitry mediating emotion regulation (Lau et al., 2011), attention retraining in adolescence may be an effective intervention strategy targeting both neural and behavioral mediators of anxiety. Although no differences in extinction learning were observed in the present study, there was suggestive evidence indicating stronger reinstatement

Developmental Psychobiology

in adolescents (on the latency of first fixation measure). However, future research is required to validate these findings and explore more fully potential differences in reinstatement and other relapse phenomena between adolescents and adults. A particularly striking finding in the current study was that symptoms of depression but not anxiety predicted stronger conditioning and weaker extinction in adolescents, with these symptoms having no impact on either conditioning or extinction in adults. It will be interesting to determine whether these results can be replicated in future studies using clinical samples. Although no study has been designed to specifically test differences in the efficacy of exposure therapy in anxious and depressed adolescents and adults, a recent reanalysis of data from studies examining cognitive behavioral therapy (CBT) efficacy across development showed a trend toward poorer treatment responses in adolescence (Drysdale et al., 2014). Poorer treatment response may reflect fundamental differences in emotion regulation, and future studies linking these changes in associative learning to the onset and course of anxiety disorders during adolescence will aid the development of effective treatments for such vulnerable populations.

ACKNOWLEDGMENTS We thank Jennifer Britton, Daniel Pine, Jennifer Lau, and Christopher Grillon for generously sharing the Screaming Lady Paradigm and allowing us to use it. M.L.D. was supported by an Australian Post Graduate Award, and this research was supported by a grant from the National Health and Medical Research Council of Australia (project #455431).

REFERENCES Amir, N., Beard, C., Burns, M., & Bomyea, J. (2009). Attention modification program in individuals with generalized anxiety disorder. Journal of Abnormal Psychology, 118, 28–33. Baker, K. D., Den, M. L., Graham, B. M., & Richardson, R. (2014). A window of vulnerability: Impaired fear extinction in adolescence. Neurobiology of Learning and Memory, 113, 90–100. Balderston, N. L., & Helmstetter, F. J. (2010). Conditioning with masked stimuli affects the timecourse of skin conductance responses. Behavioral Neuroscience, 124, 478–489. Bar-Haim, Y., Lamy, D., Pergamin, L., Bakermans-Kranenburg, M. J., & Van Ijzendoorn, M. H. (2007). Threat-related attentional bias in anxious and nonanxious individuals: A meta-analytic study. Psychological Bulletin, 133, 1–24.

Developmental Psychobiology Bar-Haim, Y., Morag, I., & Glickman, S. (2011). Training anxious children to disengage attention from threat: A randomized controlled trial. Journal of Child Psychology and Psychiatry and Allied Disciplines, 52, 861–869. Baune, B. T., Fuhr, M., Air, T., & Hering, C. (2014). Neuropsychological functioning in adolescents and young adults with major depressive disorder - A review. Psychiatry Research, 218, 261–271. Britton, J. C., Grillon, C., Lissek, S., Norcross, M. A., Szuhany, K. L., Chen, G., . . . Pine, D. S. (2013). Response to learned threat: An fMRI study in adolescent and adult anxiety. American Journal of Psychiatry, 170, 1195–1204. Browning, M., Holmes, E. A., Murphy, S. E., Goodwin, G. M., & Harmer, C. J. (2010). Lateral prefrontal cortex mediates the cognitive modification of attentional bias. Biological Psychiatry, 67, 919–925. Casey, B. J., Duhoux, S., & Cohen, M. M. (2010). Adolescence: What do transmission, transition, and translation have to do with it? Neuron, 67, 749–760. Casey, B. J., Giedd, J. N., & Thomas, K. M. (2000). Structural and functional brain development and its relation to cognitive development. Biological Psychology, 54, 241–257. Chan, R. C. K., Shum, D., Toulopoulou, T., & Chen, E. Y. H. (2008). Assessment of executive functions: Review of instruments and identification of critical issues. Archives of Clinical Neuropsychology, 23, 201–216. Christianson, J. P., Fernando, A. B. P., Kazama, A. M., Jovanovic, T., Ostroff, L. E., & Sangha, S. (2012). Inhibition of fear by learned safety signals: A minisymposium review. Journal of Neuroscience, 32, 14118– 14124. Den, M. L., & Richardson, R. (2013). Enhanced sensitivity to learning fearful associations during adolescence. Neurobiology of Learning and Memory, 92–102. Dibbets, P., van den Broek, A., & Evers, E. A. T. (2014). Fear conditioning and extinction in anxiety- and depressionprone persons. Memory. Drysdale, A. T., Hartley, C. A., Pattwell, S. S., Ruberry, E. J., Somerville, L. H., Compton, S. N., . . . Walkup, J. T. (2014). Fear and anxiety from principle to practice: Implications for when to treat youth with anxiety disorders. Biological Psychiatry, 75:e19–e20. Duffy, C. J., Cunningham, E. G., & Moore, S. M. (2005). Brief report: The factor structure of mood states in an early adolescent sample. Journal of Adolescence, 28, 677–680. Essau, C. A., Olaya, B., Pasha, G., O’Callaghan, J., & Bray, D. (2012). The structure of anxiety symptoms among adolescents in Iran: A confirmatory factor analytic study of the Spence Children’s Anxiety Scale. Journal of Anxiety Disorders, 26, 871–878. George, M. S., Ketter, T. A., & Post, R. M. (1994). Prefrontal cortex dysfunction in clinical depression. Depression, 2, 59–72. Graham, B. M., & Milad, M. R. (2011). The study of fear extinction: Implications for anxiety disorders. American Journal of Psychiatry, 168, 1255–1265.

Teens That Fear Screams

831

Grillon, C. (2002). Associative learning deficits increase symptoms of anxiety in humans. Biological Psychiatry, 51, 851–858. Haaker, J., Golkar, A., Hermans, D., & Lonsdorf, T. B. (2014). A review on human reinstatement studies: An overview and methodological challenges. Learning and Memory, 21, 424–420. Haddad, A. D. M., Lissek, S., Pine, D. S., & Lau, J. Y. F. (2011). How do social fears in adolescence develop? Fear conditioning shapes attention orienting to social threat cues. Cognition and Emotion, 25, 1139–1147. Henry, J. D., & Crawford, J. R. (2005). The short-form version of the Depression anxiety stress scales (DASS-21): Construct validity and normative data in a large nonclinical sample. British Journal of Clinical Psychology, 44, 227–239. Hermans, D., Dirikx, T., Vansteenwegenin, D., Baeyens, F., Van Den Bergh, O., & Eelen, P. (2005). Reinstatement of fear responses in human aversive conditioning. Behaviour Research and Therapy, 43, 533–551. Hofmann, S. G., Ellard, K. K., & Siegle, G. J. (2012). Neurobiological correlates of cognitions in fear and anxiety: A cognitive-neurobiological information-processing model. Cognition and Emotion, 26, 282–299. Jovanovic, T., Norrholm, S., Blanding, N. Q., Davis, M., Duncan, E., Bradley, B., & Ressler, K. J. (2010). Impaired fear inhibition is a biomarker of PTSD but not depression. Depression and Anxiety, 27, 244–251. Kessler, R. C., Avenevoli, S., McLaughlin, K. A., Green, J. G., Lakoma, M. D., Petukhova, M., & Merikangas, K. R. (2012). Lifetime co-morbidity of DSM-IV disorders in the US National Comorbidity Survey Replication Adolescent Supplement (NCS-A). Psychological Medicine, 42, 1997–2010. Kessler, R. C., & Wang, P. S. (2008). The descriptive epidemiology of commonly occurring mental disorders in the United States. Annual Review of Public Health, 29, 115–129. Kim-Cohen, J., Caspi, A., Moffitt, T. E., Harrington, H., Milne, B. J., & Poulton, R. (2003). Prior juvenile diagnoses in adults with mental disorder: Developmental follow-back of a prospective-longitudinal cohort. Archives of General Psychiatry, 60, 709–717. Kim, J. H., Li, S., & Richardson, R. (2011). Immunohistochemical analyses of long-term extinction of conditioned fear in adolescent rats. Cerebral Cortex, 21, 530–538. Lau, J. Y., Britton, J. C., Nelson, E. E., Angold, A., Ernst, M., Goldwin, M., . . . Pine, D. S. (2011). Distinct neural signatures of threat learning in adolescents and adults. Proceedings of the National Academy of Sciences of the United States of America, 108, 4500–4505. Lau, J. Y. F., Lissek, S., Nelson, E. E., Lee, Y., RobersonNay, R., Poeth, K., & Pine, D. S (2008). Fear conditioning in adolescents with anxiety disorders: Results from a novel experimental paradigm. Journal of the American Academy of Child and Adolescent Psychiatry, 47, 94–102. Lissek, S., Powers, A. S., McClure, E. B., Phelps, E. A., Woldehawariat, G., Grillon, C., & Pine, D. S. (2005).

832

Den et al.

Classical fear conditioning in the anxiety disorders: A meta-analysis. Behaviour Research and Therapy, 43, 1391–1424. Lovibond, P. F., & Lovibond, S. H. (1995). The structure of negative emotional states: Comparison of the depression anxiety stress scales (DASS) with the Beck Depression and Anxiety Inventories. Behaviour Research and Therapy, 33, 335–343. MacLeod, C., Mathews, A., & Tata, P. (1986). Attentional bias in emotional disorders. Journal of Abnormal Psychology, 95, 15–20. Mathews, R. R. S., Hall, W. D., Vos, T., Patton, G. C., & Degenhardt, L. (2011). What are the major drivers of prevalent disability burden in young Australians? Medical Journal of Australia, 194, 232–235. McCallum, J., Kim, J. H., & Richardson, R. (2010). Impaired extinction retention in adolescent rats: Effects of d-cycloserine. Neuropsychopharmacology, 35, 2134–2142. McNally, R. J. (2007). Mechanisms of exposure therapy: How neuroscience can improve psychological treatments for anxiety disorders. Clinical Psychology Review, 27, 750–759. Mogg, K., Millar, N., & Bradley, B. P. (2000). Biases in eye movements to threatening facial expressions in generalized anxiety disorder and depressive disorder. Journal of Abnormal Psychology, 109, 695–704. Muris, P., Schmidt, H., & Merckelbach, H. (2000). Correlations among two self-report questionnaires for measuring DSM-defined anxiety disorder symptoms in children: The screen for child anxiety related emotional disorders and the spence children’s anxiety scale. Personality and Individual Differences, 28, 333–346. Neumann, D. L., Waters, A. M., Westbury, H. R., & Henry, J. (2008). The use of an unpleasant sound unconditional stimulus in an aversive conditioning procedure with 8- to 11-year-old children. Biological Psychology, 79, 337–342. Onnis, R., Dadds, M. R., & Bryant, R. A. (2011). Is there a mutual relationship between opposite attentional biases underlying anxiety? Emotion, 11, 582–594. Orgil
es, M., Spence, S. H., Marzo, J. C., M
endez, X., & Espada, J. P. (2014). Psychometric properties and factorial structure of the Spence Children’s Anxiety Scale (SCAS) in Spanish adolescents. Journal of Personality Assessment, 96, 95–102. Pattwell, S. S., Duhoux, S., Hartley, C. A., Johnson, D. C., Jing, D., Elliott, M. D., & Lee, F. S (2012). Altered fear learning across development in both mouse and human. Proceedings of the National Academy of Sciences of the United States of America, 109, 16318–16323. Rescorla, R. A., & Heth, C. D. (1975). Reinstatement of fear to an extinguished conditioned stimulus. Journal of

Developmental Psychobiology Experimental Psychology: Animal Behavior Processes, 1, 88–96. Rogers, M. A., Kasai, K., Koji, M., Fukuda, R., Iwanami, A., Nakagome, K., & Kato, N (2004). Executive and prefrontal dysfunction in unipolar depression: A review of neuropsychological and imaging evidence. Neuroscience Research, 50, 1–11. Schmidt, N. B., Richey, J. A., Buckner, J. D., & Timpano, K. R. (2009). Attention training for generalized social anxiety disorder. Journal of Abnormal Psychology, 118, 5–14. Somerville, L. H., Jones, R. M., & Casey, B. J. (2010). A time of change: Behavioral and neural correlates of adolescent sensitivity to appetitive and aversive environmental cues. Brain and Cognition, 72, 124–133. Spence, S. H. (1998). A measure of anxiety symptoms among children. Behaviour Research and Therapy, 36, 545–566. Spielberger C. D., Gorsuch R. L., & Luschene R. (1970). Test manuel for the stait-trait anxiety inventory. Palo Alto, CA: Consulting Psychologists Press. Szab
o, M. (2010). The short version of the Depression Anxiety Stress Scales (DASS-21): Factor structure in a young adolescent sample. Journal of Adolescence, 33, 1–8. Taylor, R., Lovibond, P. F., Nicholas, M. K., Cayley, C., & Wilson, P. H. (2005). The utility of somatic items in the assessment of depression in patients with chronic pain: A comparison of the Zung Self-Rating Depression Scale and the Depression Anxiety Stress Scales in chronic pain and clinical and community samples. Clinical Journal of Pain, 21, 91–100. Whiteside, S. P., & Brown, A. M. (2008). Exploring the utility of the Spence Children’s Anxiety Scales parentand child-report forms in a North American sample. Journal of Anxiety Disorders, 22, 1440–1446. Zhao, J., Xing, X., & Wang, M. (2012). Psychometric properties of the Spence Children’s Anxiety Scale (SCAS) in Mainland Chinese children and adolescents. Journal of Anxiety Disorders, 26, 728–736. Zvielli, A., Bernstein, A., & Koster, E. H. W. (2014). Dynamics of attentional bias to threat in anxious adults: Bias towards and/or away? PLoS ONE, 9, 1–9.

Supporting Information Additional supporting information may be found in the online version of this article.