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Behaviorally inhibited temperament is associated with severity of post-traumatic stress disorder symptoms and faster eyeblink conditioning in veterans

Behaviorally inhibited temperament is associated with severity of post-traumatic stress disorder... Prior studies have sometimes demonstrated facilitated acquisition of classically conditioned responses and/or resistance to extinction in post-traumatic stress disorder (PTSD). However, it is unclear whether these behaviors are acquired as a result of PTSD or exposure to trauma, or reflect preexisting risk factors that confer vulnerability for PTSD. Here, we examined classical eyeblink conditioning and extinction in veterans self-assessed for current PTSD symptoms, exposure to combat, and the personality trait of behavioral inhibition (BI), a risk factor for PTSD. A total of 128 veterans were recruited (mean age 51.2 years; 13.3% female); 126 completed self-assessment, with 25.4% reporting a history of exposure to combat and 30.9% reporting current, severe PTSD symptoms (PTSS). The severity of PTSS was correlated with current BI (R ¼ 0.497) and PTSS status could be predicted based on current BI and combat history (80.2% correct classification). A subset of the veterans (n ¼ 87) also completed the eyeblink conditioning study. Among veterans without PTSS, childhood BI was associated with faster acquisition; veterans with PTSS showed delayed extinction, under some conditions. These data demonstrate a relationship between current BI and PTSS, and indicate that the facilitated conditioning sometimes observed in patients with PTSD may partially reflect personality traits such as childhood BI that pre-date and contribute to vulnerability for PTSD. Keywords: Behavioral inhibition, eyeblink, classical conditioning, learning, post-traumatic stress disorder (PTSD), veterans Introduction polymorphisms (Binder et al. 2008; Amstadter et al. 2009), female sex (Tolin and Foa 2006), prior In the wake of exposure to a traumatic event, some exposure to highly stressful situations such as combat, individuals develop post-traumatic stress disorder rape, or other trauma (e.g. North and Smith 1990; (PTSD), and others may experience varying degrees Davidson 2000; Seng et al. 2009), brain and of sub-clinical PTSD symptoms, including heightened physiological abnormalities (Pitman et al. 2006; emotional responses to and avoidance of reminders Liberzon and Sripada 2008), and various socio- of the trauma. The wide range of PTSD symptom behavioral variables including personality traits severity among individuals exposed to similarly (Engelhard et al. 2006; Gil and Caspi 2006; Qouta stressful traumatic events (Pitman et al. 1987; Orr et al. 2007). As one example, behavioral inhibition et al. 1993; Shalev et al. 1993) suggests that (BI) is a temperamental tendency for avoidance of or preexisting vulnerability factors modulate an individ- ual’s risk to develop PTSD. Several vulnerability withdrawal from unfamiliar social and nonsocial factors have been identified, including genetic situations (Fox et al. 2005). This tendency develops Correspondence: C. E. Myers, Stress & Motivated Behavior Institute, VA Medical Center, Mail Stop 129, 385 Tremont Avenue, East Orange, NJ 07108, USA. Tel: 973 676 1000 Ext. 1810. Fax: 973 395 7111. E-mail: [email protected] 32 C. E. Myers et al. early in life and is relatively stable over development study suggests that delayed extinction does not (Degnan and Fox 2007). Individuals with high BI pre-date PTSD. These studies did not take into are at increased risk for PTSD (Fincham et al. 2008; account preexisting vulnerabilities, such as tempera- Kashdan et al. 2009) as well as other anxiety disorders ment, which might help account for the discrepant (Hirshfeld et al. 1992). findings. Diathesis models of PTSD emphasize the Here, we consider a complementary approach to dynamic interaction of preexisting vulnerabilities and understanding the relationship between vulnerability environmental interactions. An influential theory factors and associative learning, by testing acquisition of PTSD (Pitman 1988; Pitman et al. 2000) suggests and extinction of classically CRs in veterans self- that many PTSD symptoms reflect learned associ- assessed for BI, history of exposure to combat, and ations in which cues (conditioned stimulus or CS) current PTSD symptom severity. Our hypothesis was present at the time of the trauma (unconditioned that if facilitated conditioning in PTSD partially stimulus or US) come to evoke emotional responses reflects preexisting vulnerabilities such as high BI, (conditioned responses or CRs) similar to those then it should be evident in veterans with high BI but provoked by the event itself. According to this model, without PTSD. Alternatively, if facilitated learning individual differences in the speed of acquisition of the emerges only as a symptom of PTSD and/or as a CR, and in extinction of the CR when the CS is consequence of exposure to trauma, then it should be no longer paired with the US, could promote evident only in veterans with severe PTSD symptoms individual differences in the development and main- tenance of PTSD symptoms. and/or history of exposure to combat. Consistent with this view, many studies have In this study, we considered classical eyeblink reported facilitated acquisition of CRs and delayed conditioning, in which the CS is a tone, the US is extinction of CRs in individuals with PTSD, an airpuff aimed at the eye that evokes a protective compared to non-PTSD controls (Grillon and eyeblink, and the CR is an anticipatory eyeblink that Morgan 1999; Orr et al. 2000; Peri et al. 2000; occurs after CS onset but before US arrival. Blechert et al. 2007; Burriss et al. 2007; Wessa and Participants were randomly assigned to receive Flor 2007; Jovanovic et al. 2010), although other training under delay contingencies, in which the CS studies have found no such effects (Ayers et al. 2003; and US overlap and co-terminate, or omission Orr et al. 2006; Vythilingam et al. 2006; Ginsberg et al. contingencies, in which a CR causes omission of the 2008a,b). The variability of results may partially US. Typically, imposition of an omission contingency reflect different experimental design and/or different into eyeblink conditioning results in lower perform- parameters such as stimulus duration and intensity. ance, in terms of number of CRs produced Such between-group studies do not address the (Logan 1951; Massaro and Moore 1967); accordingly, question of whether observed abnormalities in the inclusion of an omission group in this associative learning are acquired symptoms of PTSD, study allowed us to examine whether veterans with emerge as a consequence of exposure to stressful high BI, history of combat exposure, and/or severe events, or pre-date PTSD and exposure to trauma. In the latter case, strong learning of avoidant and PTSD symptoms could modulate their responding as emotional responses to trauma-related cues and a function of CS–US contingency. Following eyeblink resistance to extinction of these responses might bias acquisition, each participant also received a series of an individual to develop PTSD if exposed to traumatic CS-alone trials, during which the eyeblink CR was events. The few studies that have attempted to address expected to extinguish, allowing us to determine this question have yielded discrepant results. For whether delayed extinction occurred as a function of example, a prospective study of classical conditioning BI, history of combat exposure, and/or severe PTSD in firefighter recruits found that the degree of delayed symptoms. CR extinction, assessed during firefighter training, As our measure of BI, we used the Adult and was significantly correlated with PTSD symptom Retrospective Measures of Behavioural Inhibition severity following subsequent exposure to a traumatic (AMBI/RMBI), two recently developed self-report event (Guthrie and Bryant 2006), suggesting that measures that allow assessment of current and delayed extinction pre-dates trauma exposure in childhood inhibited temperament (Gladstone and vulnerable individuals. By contrast, a study of mono- Parker 2005); however, a relationship between zygotic twins discordant for combat exposure found these measures and current PTSD symptom status that combat-exposed participants with PTSD showed has not been established. Therefore, a secondary normal extinction of a conditioned fear response, purpose of this study was to determine whether compared with both their non-combat-exposed, non- AMBI/RMBI scores were significantly related to PTSD co-twins and with combat-exposed, non-PTSD participants, although extinction recall was deficient presence vs. absence of current, severe PTSD on the following day (Milad et al. 2008); thus, this symptoms in veterans. Behavioral inhibition in veterans 33 Methods “uninhibited”, whereas individuals scoring from 16 to 32 are classified as “inhibited” (Gladstone and Parker Participants 2005). In addition to a total AMBI score, items Veterans (n ¼ 128) were recruited from the New group into four subscales derived from factor analysis Jersey Health Care System (NJHCS), East Orange, (Gladstone and Parker 2005): “fearful inhibition” NJ. Participants included 111 males and 17 females (FI), “risk avoidance” (RA), “non-approach” (NA), (13.3%), with mean age 51.2 years (SD 8.0, range and “low sociability” (LS). Items in the FI subscale 23–65) and mean education 13.4 years (SD 1.7, range assess the general tendency to respond with wariness, 9–20). The group included 94 African–Americans show hypervigilance, and become physically anxious (73.4%), 26 Caucasians (20.3%), and 8 individuals of in response to novel social situations (e.g. “Do you Mixed/Other Race (6.3%). When asked to identify intend to withdraw and retreat from those around specific wars or conflicts in which they had served, 44 you?”). Items in the RA subscale assess the tendency veterans reported having served during the Vietnam to avoid physical risk, adventurous activities, and high conflict (approx. 1970–1975), 17 during Operation social stimulation (e.g. “If physically able, would you Desert Storm (1991), 7 during Operation Enduring enjoy adventure holidays with some element of risk?”). Freedom/Operation Iraqi Freedom (2001 þ), and 39 Items in the NA subscale assess willingness to engage during peacetime or no specific conflict; others others in novel social situations (e.g. “Do you tend to reported having served during various conflicts introduce yourself to new people?”). Items in the LS including operations in Granada, Panama, and the subscale assess preference for solo activities (e.g. “Do Middle East. Veterans were not included or excluded you prefer your own company to the company of based on any medical or psychiatric history, but others?”). were asked to self-report current medications; 41 The RMBI is a 18-item self-report inventory used to participants (32%) self-reported taking psychoactive assess childhood memories of exhibiting inhibition to medications. Although some participants were able to the unfamiliar; individuals scoring from 0 to 11 are clearly identify the name of their medications, others classified as “uninhibited”, whereas individuals scor- simply reported the use of medication (e.g. “anxiety ing from 12 to 25 are classified as “inhibited” meds” or “anti-depressant”). Thus, further analysis (Gladstone and Parker 2005). Like the AMBI, there regarding medication usage in this sample was not are four RMBI subscales derived from factor analysis possible. (Gladstone and Parker 2005): “fearful inhibition” Participants received payment at the rate of $30 (FI), “risk avoidance” (RA), “non-approach” (NA), per hour (maximum of $60) for their participation and “shyness and sensitivity” (SS). Items for the first in the study. Testing generally occurred between three subscales are similar to those on the AMBI, but 10:00–12:00 and 13:00–15:00 h; no obvious differen- target memories of childhood behaviors. The SS ces in subject demographics or experimental data were subscale assesses self-rated shyness, particularly at observed as a function of testing time. All participants school. The RMBI allows respondents to endorse a gave written informed consent before initiation of any “do not remember” item. For items in which experimental procedures; procedures were approved by participants endorsed “do not remember,” scores the NJHCS Institutional Review Board and were were prorated based on responses to the remaining conducted in accordance with the Declaration of questions on the same RMBI subscale, with reverse Helsinki and guidelines established by the Federal scoring taken into account. Any participant who Government for the protection of human subjects. endorsed “do not remember” on more than 50% of the total RMBI items was scored as incomplete. The CES is a 7-item self-report questionnaire that Self-report measures assesses exposure to stressful military events, with After informed consent, participants completed a items rated on frequency, duration, and degree of battery of paper-and-pencil questionnaires prior to exposure; for example, the question “Were you ever instrumentation for electromyography (EMG) surrounded by the enemy?” can be endorsed at a level recording. These questionnaires typically required of 1 ¼ “no” to 5 ¼ “more than 12 times.” Total CES 20–30 min to complete. The package included score is calculated from a sum of weighted scores; as in AMBI/RMBI (Gladstone and Parker 2005), the prior studies (Ginsberg et al. 2008a), veterans with a Combat Exposure Scale (CES; Keane et al. 1989), CES score of 0–7 were classified as non-combat and the PTSD Checklist-Military version (PCL-M; whereas those with a score of 8 þ were classified as Blanchard et al. 1996). having a history of exposure to combat. The AMBI is a 16-item self-report inventory that The PCL-M is a 17-item self-report questionnaire assesses current tendency to respond to new stimuli that asks about the presence and the frequency of with inhibition and/or avoidance, and it has also been PTSD symptoms in response to stressful military shown to be a measure of anxiety proneness; experiences; symptoms are rated according to how individuals scoring from 2 to 15 are classified as much they have bothered the participant in the past 34 C. E. Myers et al. month, on a scale from “Not at all” to “Extremely.” produce a unconditioned response (UR). Data from Specific questions correspond to DSM-IV symptom the participants who failed to produce URs, or failed clusters including cluster B (re-experiencing the to remain awake throughout the experiment, were traumatic event), cluster C (avoidance/numbing), discarded from analysis. and cluster D (increased arousal). PCL-M scores of Conditioning then commenced. For participants in the 50 þ have been shown to be a predictor of PTSD delay group, the CS was a 500-ms 83-dB, 800-Hz in military samples (Weathers et al. 1993; Blanchard pure tone (50 ms rise/fall) that co-terminated with the et al. 1996). Accordingly, we also categorized US, a 50-ms airpuff; the inter-trial interval varied participants according to the presence or the absence between 15 and 25 s. For participants in the omission of current, severe PTSD symptoms (PTSS) based on group, all parameters were identical to delay training, this cut-off. except that emitting a CR at least 40 ms prior to the airpuff prevented US delivery. Five blocks of 12 Eyeblink conditioning acquisition trials were presented (total 60 trials). In both delay and omission groups, acquisition trials Materials and apparatus. The eyeblink conditioning were followed by 20 extinction trials that were similar apparatus and procedures were as previously to the acquisition trials except that the US was not described (Beck et al. 2008). Auditory stimuli were presented. produced with Coulbourn Instruments (Allentown, PA, USA) signal generators and passed to a David Clark aviation headset (Model H10–50, Worchester, Data processing. Processing of eyeblink responses MA, USA). Sound levels were verified with a Realistic followed methods previously reported (Servatius sound meter (RadioShack, Fort Worth, TX, USA). et al. 1998; Beck et al. 2008). To determine the Airpuffs were produced by pressurizing ambient air to occurrence of an eyeblink, EMG activity was first low- 3.5 psi (Fu¨rgut Industries, Aitrach, Germany), and pass filtered using a Lowess filter (Stat-Sci, Tacoma, released through Silastic tubing attached to the boom WA, USA) using a time constant of 0.025 and a of the headphones by a computer-controlled solenoid smoothing interval of 5. Using the filter values, activity valve (Clipper Instruments, Cincinnati, OH, USA). greater than 0.2 (unitless) corresponds to an eyeblink. The boom was placed 1 cm from the eye and aimed at An a-response (orienting response) was scored when it. To transduce the eyelid EMG signal, pediatric an eyeblink occurred within 80 ms of CS onset; these silver/silver chloride EMG electrodes with solid gel responses rarely occur with the present equipment were placed above and below the left eye, with the configuration. A CR was scored when an eyeblink was ground electrode placed on the neck. The EMG signal elicited 80 ms after CS onset but before US onset. was passed to a medically isolated physiological An UR was scored when an eyeblink was produced amplifier (UFI, Morro Bay, CA, USA), low-pass 0–100 ms after US onset during the three US-alone filtered and amplified 10 K. The signal for EMG was presentations preceding training. sampled at 200 Hz by an A/D board (PCI 6025E, National Instruments, Austin, TX, USA) connected to an IBM-compatible computer. Software control Data analysis of stimulus generation was accomplished with LabView (National Instruments). For the omission Questionnaire scores were analyzed using t-test or contingency, a time-varying Gabor filter processed the univariate analysis of variance (ANOVA) for continu- data up to 10 ms prior to US trigger. If a CR was ous values and chi-square tests for categorical values. detected during this period, the US trigger was not Inter-item relationships and correlations across scores initiated. were analyzed using the Pearson correlation coeffi- cient (using Yates continuity correction for 2 £ 2 tables) or Cronbach’s a. Stepwise linear regression Procedures. Participants were pseudorandomly was used to investigate the ability of questionnaire assigned to the delay and omission groups: for each scores to predict PCL-M scores and stepwise pair of participants, the first was randomly assigned discriminant analysis was used to investigate the to one group and the second was assigned to the ability of categorical values based on questionnaire other group. Participants were seated in a comfortable scores to predict PTSS status. chair and fitted with EMG electrodes; they were For eyeblink data, the dependent measure was instructed that the study evaluated responses to tones percent CRs scored within each block of trials and and airpuffs to the eye, that they were to watch a silent total percent CRs over the entire acquisition or video of their choice (e.g. Free Willy with sound extinction phase. Total scores were analyzed by muted), and to stay awake. Each participant was Pearson’s correlation to assess relationships with then exposed to three airpuff stimuli; these trials continuously valued questionnaire scores, and uni- served to verify the ability of the participant to variate ANOVA to assess relationships with categorical Behavioral inhibition in veterans 35 values; scores across the five blocks of acquisition endorsing “Moderate” or higher for an average of and extinction were analyzed by repeated measures 1.5 cluster B symptoms (SD 2.0), 2.4 cluster C ANOVA, with post hoc ANOVA and t-tests as symptoms (SD 2.6), and 2.1 cluster D symptoms appropriate. As explained below, UR magnitude (SD 1.9). Scores on all PTSD symptom clusters were was included as a covariate in all assessments of significantly correlated with each other (Pearson’s r, acquisition data, and total percent CRs during all r . 0.650, all p , 0.001) and with CES score acquisition was included as a covariate in all (Pearson’s r, all r . 0.350, all p , 0.001). Total PCL- assessments of extinction data. M scores, as well as cluster B, C, and D scores, were all All ANOVAs used type III sum-of-squares, as significantly higher in combat than non-combat appropriate for designs in which cell sizes are unequal veterans (Table I; independent-samples t-tests, all (and some cells may be empty). All tests were two- p , 0.004). tailed, with threshold for significance set at 0.050. Following Weathers et al.’s (1993) cutoff of 50þ as Where multiple pairwise comparisons were made, the indicating current, severe (PTSS), 39 of our 126 Bonferroni correction was used to reduce alpha to veterans were classed with PTSS (30.9%); this protect against risk of increased family-wise error; the included 13 of the 32 combat veterans (40.6%) but corrected alpha is reported in the text only when only 20 of the 94 non-combat veterans (21.3%), a p-values approach 0.050 but fall short of the corrected statistically significant difference (Yates-corrected alpha. chi-square x ¼ 14.48, df ¼ 1, p , 0.001). Among Because of the low number of females in this study, the 17 females in this study, 10 had PTSS (58.8%) and the fact that random assignment led to only three compared with only 29 of 109 males (26.6%), females being assigned to the omission group, we did a statistically significant difference (Yates-corrected not consider gender as a factor in the analysis of chi-square x ¼ 5.72, df ¼ 1, p ¼ 0.017). eyeblink data. When the eyeblink analyses described above were rerun on the subset of data from males only, the general pattern of results was qualitatively Adult and retrospective measures of behavioural inhibition. similar to that obtained for the complete dataset, All 126 participants responded to all AMBI questions, although the reduced sample size meant lower power except for one participant who failed to enter a to detect significant differences. response to question 3 (“Do you tend to become quiet?”). Three participants endorsed “do not remember” responses on all RMBI questions, and so Results their total RMBI and RMBI subscales could not be calculated. These three participants were accordingly Questionnaire data included in the analysis of AMBI but not RMBI data. CES and PCL-M. Of the total sample (n ¼ 128), two Among the remaining 123 participants, only four participants did not complete any questionnaires, and endorsed more than one “do not remember” their data were dropped from all further analysis. responses on RMBI. RMBI item response rates Among the remaining 126 participants, 94 (74.6%) ranged from 92.7% (question 3: “Were you reluctant were classed as non-combat based on CES scores; the to go to school on your first day or the first day after remaining 32 were classed as combat (25.4%). Mean holidays?”) and 93.5% (question 4: “Did you prefer CES score for the non-combat veterans was 1.5 (SD parties with crowds of children rather than small 2.5); for the combat veterans, it was 19.6 (SD 8.8). gatherings?”) to 100% (8 questions total). Mean PCL-M score for the 126 participants was Mean AMBI/RMBI total scores and subscale scores 38.2 (SD 18.7, range 17–85), with participants for the veteran sample are given in Table II. Both Table I. Mean (SD) PCL-M total scores and scores for PTSD cluster B, C, and D symptoms in individuals with inhibited vs. uninhibited temperament based on AMBI and RMBI, and with vs. without combat history. Combat history AMBI RMBI (n ¼ 126) (n ¼ 126) (n ¼ 123) Combat Non-combat Inhibited Uninhibited Inhibited Uninhibited (n ¼ 32) (n ¼ 94) (n ¼ 69) (n ¼ 57) (n ¼ 62) (n ¼ 61) PCL-M (total) 53.50 (17.91) 32.97 (16.00) 43.30 (19.56) 31.98 (15.70) 42.13 (18.99) 33.97 (17.18) * * Cluster B symptoms 3.09 (2.02) 0.97 (1.68) 1.97 (2.13) 0.95 (1.67) 1.87 (2.17) 1.13 (1.72) * * Cluster C symptoms 4.41 (2.24) 1.74 (2.32) 3.01 (2.65) 1.70 (2.30) 2.98 (2.71) 1.80 (2.26) * * Cluster D symptoms 3.19 (1.93) 1.76 (1.77) 2.75 (1.81) 1.35 (1.75) 2.63 (1.90) 1.62 (1.76) * * Note: Asterisks indicate significant differences (ANOVA with factors of combat history and AMBI/RMBI, with alpha corrected to 0.004 to protect against increased family-wise error) between inhibited/uninhibited and combat/non-combat veterans (F . 4.00, p , 0.004). PCL-M, PTSD Checklist-Military version; AMBI/RMBI, Adult/Retrospective Measure of Behavioural Inhibition. 36 C. E. Myers et al. veterans in this sample were “inhibited” based on Table II. Mean (SD) AMBI and RMBI total scores and subscale scores for the complete set of 126 veterans and for the subset of AMBI scores. There were no significant differences in 87 veterans who produced useable eyeblink conditioning data. gender distribution or history of combat exposure among individuals classed as inhibited vs. uninhibited Total sample Eyeblink sample (n ¼ 126) (n ¼ 87) on AMBI or RMBI (all x , 1.00, all p . 0.500). Among veterans classed as “inhibited” based on RMBI total score 12.7 (6.6) 12.6 (6.7) RMBI, 26 had PTSS (41.9%) compared with only Non-approach (NA) 4.5 (2.9) 4.5 (2.9) 12 of those classed as “uninhibited” (19.7%), a Fearful inhibition (FI) 2.5 (2.3) 2.5 (2.3) significant difference (Yates-corrected chi-square, Risk avoidance (RA) 2.9 (1.4) 2.7 (1.4) Shyness & sensitivity (SS) 2.8 (2.0) 2.9 (2.2) x ¼ 7.14, df ¼ 1, p ¼ 0.008). Similarly, among AMBI total score 17.0 (6.1) 17.2 (6.4) those classed as “inhibited” based on AMBI, 29 had Non-approach (NA) 3.2 (1.5) 3.2 (1.6) PTSS (42.0%) compared with only 10 of those classed Fearful inhibition (FI) 7.2 (3.4) 7.3 (3.5) as “uninhibited” (17.5%; Yates-corrected chi-square, Risk avoidance (RA) 3.5 (1.4) 3.5 (1.4) x ¼ 8.76, df ¼ 1, p ¼ 0.003). Low sociability (LS) 3.2 (1.6) 3.3 (1.6) Note: Note that RMBI scores were not available for three veterans in the larger sample, due to endorsement of “do not remember” Predicting PTSD symptoms based on combat history and responses for more than 50% of RMBI items; RMBI scores were BI. Stepwise linear regression on PCL-M scores, with available for all veterans in the eyeblink sample. AMBI/RMBI, Adult/Retrospective Measure of Behavioural Inhibition. factors of total AMBI, total RMBI, and CES score revealed that PCL-M scores could be significantly predicted by a two-variable model including AMBI AMBI and RMBI were significantly higher in (b ¼ 0.501) and CES (b ¼ 0.443). This model could individuals with PTSS (Table I; independent-samples account for significant variance in PCL-M scores t-tests, all t . 2.75, all p , 0.010). Although Glad- (R ¼ 0.497; F(2,120) ¼ 59.27, p , 0.001); the stone and Parker (2005) reported higher RA in addition of RMBI into the model did not account females, the gender difference was not significant in for significant additional variance ( p . 0.050). When this sample (males RMBI: M ¼ 2.8, SD 1.4; AMBI: the regression was repeated replacing AMBI/RMBI M ¼ 3.4, SD 1.4; females RMBI: M ¼ 3.4, SD 1.5; total scores with the eight subscale scores, the best AMBI: M ¼ 4.1, SD 1.3; independent-samples prediction was produced by a three-factor model t-tests, all t , 1.8, 0.050 , p , 0.010), nor were including CES (b ¼ 0.415) and two AMBI subscales: there significant gender differences on any other FI (b ¼ 0.306) and LS (b ¼ 0.221). This model could AMBI/RMBI scores or subscales (all t , 1.0, all also account for significant variance in PCL-M scores p . 0.300). (R ¼ 0.473; F(3,119) ¼ 35.31, p , 0.001); the Internal consistency of AMBI and RMBI total and addition of the remaining AMBI and RMBI subscale scores was estimated using Cronbach’s a, subscales into the model did not account for with reverse scoring for individual questions taken into significant additional variance (all p . 0.050). account. For the 16 questions comprising AMBI total Univariate ANOVA on PCL-M total score, with score, Cronbach’s a ¼ 0.841; for individual AMBI the factors of AMBI and RMBI (“inhibited” vs. subscales, inter-item reliability was high for NA, FI, “uninhibited”) and combat history (exposed vs. and LS subscales (with a ranging from 0.588 to 0.793) non-exposed) revealed significant main effects but lower for RA (a ¼ 0.249). Similarly, inter-item of combat (F(1,115) ¼ 31.98, p , 0.001) and AMBI reliability was high for the 18 questions comprising (F(2,115) ¼ 8.72, p ¼ 0.004) with no main effect of RMBI total score (a ¼ 0.816) as well as for the NA, RMBI and no interactions (all F , 1.00, all FI, and SS subscales (a ranging from 0.600 to 0.722) p . 0.400). Specifically, veterans with a history of but lower for RA (a ¼ 0.233). exposure to combat had higher PCL-M scores than In this sample, AMBI and RMBI scores were non-combat veterans (Figure 1A) and veterans classed highly correlated (Pearson’s r ¼ 0.559, p , 0.001). as inhibited (on AMBI or RMBI) had higher PCL-M Within AMBI, all four subscale scores were signi- scores than uninhibited veterans (Figure 1B). ficantly correlated (all p , 0.008); correlations Considering scores on PCL-M cluster B, C, and D ranged from r ¼ 0.242 (NA vs. RA) to r ¼ 0.644 (FI symptoms, the results were similar (Table I): signifi- vs. LS). Within RMBI, the NA, FI, and SS subscales cant main effects of combat history and AMBI (all were all correlated with each other (all r . 0.600, F . 4.00, all p , 0.050) with no effect of RMBI and all p , 0.001) but RA was not correlated with any of no interactions (all F , 3.0, all p . 0.050). the other subscales (all r , 0.150, all p . 0.300). As noted above, 30.9% of the veterans in our sample According to the cutoffs in the original validation were classed with PTSS, meaning that they scored 50 article of Gladstone and Parker (2005), 62 of 123 or higher on PCL-M. Stepwise discriminant analysis, (50.4%) veterans in this sample were “inhibited” using a priori probability of 30.9%, with independent based on RMBI scores and 69 of 126 (54.8%) variables of AMBI, RMBI, and CES scores, found Behavioral inhibition in veterans 37 AB 80 60 ** Combat (n = 32) Non-Combat (n = 94) AMBI AMBI RMBI RMBI Inhibited Uninhibited Inhibited Uninhibited (n = 69) (n = 57) (n = 62) (n = 61) Figure 1. (A) PCL-M scores are significantly higher in veterans with a history of exposure to combat (F(1,117) ¼ 36.41, p , 0.001. (B) Veterans classed as inhibited (based on either AMBI or RMBI scores) score higher on PCL-M than veterans classed as uninhibited (Univariate ANOVAs, all F . 8.00, all p , 0.010). Asterisks indicate significant differences ( p , 0.050). PCL-M, PTSD Checklist-Military version; AMBI/RMBI, Adult/Retrospective Measure of Behavioural Inhibition. that a model including AMBI (standardized coeffi- The remaining n ¼ 87 participants had been cient 0.762) and CES (standardized coefficient 0.710) randomly assigned to the delay (n ¼ 43) and omission correctly classified 21 of 39 PTSS cases (53.8% (n ¼ 44) groups. There were no significant differences sensitivity) and 80 of 87 non-PTSS cases (92.0% between participants in the delay vs. omission groups selectivity) for an overall 80.2% correct classification. on age, education, PCL-M scores, CES scores, or The addition of RMBI to the model did not AMBI/RMBI scores (independent-samples t-tests, significantly increase predictive power (at tolerance- all p . 0.050). The groups did however differ in to-enter/remove 0.050). gender distribution (Yates-corrected chi-square test, x ¼ 4.62, df ¼ 1, p ¼ 0.032), with 10 females assigned to the delay group but only 3 assigned to Eyeblink conditioning theomission group. Therewerenodifferences Study completion rates and group assignment. Of the 126 between delay and omission groups in the distribution veterans who completed the AMBI, CES, and PCL-M of individuals with a history of exposure to combat, questionnaires, a complete eyeblink conditioning BI, or PTSS (Yates-corrected chi-square tests, all dataset was obtained from 87. For one of these p . 0.200). participants, RMBI could not be calculated, due to endorsement of “do not remember” responses on over 50% of items; this participant’s remaining Unconditioned eyeblink responding. An ANOVA on UR questionnaire scores and eyeblink data were included magnitude, with factors of training group, history of in the analysis. combat exposure, AMBI, RMBI, and PTSS, revealed Conditioning data from the remaining participants no significant main effects or interactions (all (n ¼ 36) were unusable. Specifically, 15 participants F , 2.60, all p . 0.050). There were no significant fell asleep one or more times during the 1-h eyeblink correlations between UR magnitude and any testing session; another 19 participants failed to AMBI/RMBI subscale or PTSD symptom cluster exhibit any eyeblink URs, even after the experimenter (Pearson’s r, all r , 0.20, all p . 0.050). However, made several attempts to reposition the headset. Data there were significant correlations between UR from the remaining participants were lost due to poor magnitude and total eyeblink CRs during the signal quality (noise from ambient electrical fields acquisition phase of eyeblink conditioning (Pearson’s interfering with an EMG signal). r ¼ 0.301, n ¼ 87, p ¼ 0.005). The relationships Those participants who completed the eyeblink between UR magnitude and age, and between conditioning study did not differ from those who did age and total CRs, both fell short of significance not on any measures including gender distribution (all r , 0.200, all p . 0.050). Accordingly, UR (Yates-corrected chi-square test, x ¼ 0.410, df ¼ 1, magnitude but not age was included as a covariate in subsequent analyses of eyeblink acquisition data. p ¼ 0.522), age, education (years), or questionnaire scores (independent-samples t-tests, all p . 0.100). Total percent CRs during extinction were correlated Data from the participants who failed to complete the with total CRs during acquisition (r ¼ 0.543, n ¼ 87, eyeblink study were discarded from further analysis. p , 0.001) but not with age or UR magnitude (all Mean PCL-M Score Mean PCL-M Score 38 C. E. Myers et al. Acquisition Acquisition AB 100 100 Delay (n = 43) noPTSS, Uninhib (n = 36) noPTSS, Inhib (n = 22) Omission (n = 44) 80 80 PTSS, Uninhib (n = 10) PTSS, Inhib (n = 19) 60 60 40 40 20 20 0 0 123 45 123 45 Blocks (of 12 trials) Blocks (of 12 trials) Figure 2. Eyeblink acquisition data. (A) Veterans in the delay group (CS and US overlap and co-terminate) showed more eyeblink-CRs than in the omission group (CR causes omission of US) (repeated-measures ANOVA, F(1,74) ¼ 7.74, p ¼ 0.007). (B) There was also a block £ RMBI £ PTSS interaction, such that, among individuals without current, severe PTSD symptoms (noPTSS), those with childhood BI (Inhib) made more CRs than those with an uninhibited temperament (Uninhib, F(1,56) ¼ 4.55, p ¼ 0.037). RMBI, Retrospective Measure of Behavioural Inhibition. r , 0.200, all p . 0.050). Accordingly, percent CRs shows the interaction between block, RMBI and during acquisition was included as a covariate in PTSS: specifically, there was no difference in subsequent analysis of eyeblink extinction data. responding across blocks between inhibited vs. uninhibited veterans with PTSS (repeated measures ANOVA, F , 1.00, p . 0.500); but among non- PTSS veterans, those with inhibited temperament Acquisition and extinction. Total percent eyeblink gave more CRs than those with uninhibited tempera- CRs during acquisition was significantly correlated ment (F(1,56) ¼ 4.55, p ¼ 0.037). with RMBI scores (Pearson’s r ¼ 0.216, n ¼ 87, Figure 3A shows eyeblink responding across the five p ¼ 0.045) but not AMBI scores (r ¼ 0.185, extinction blocks in the delay and omission groups; p ¼ 0.086); neither AMBI nor RMBI scores were given that the delay group had reached higher levels of correlated with extinction CRs (all r , 0.100, all responding during acquisition (compare Figure 2A), p . 0.500). Of the eight AMBI and RMBI subscales, they extinguished at a steeper rate than the omission none correlated significantly with acquisition or group. A repeated measures ANOVA on these data, extinction CRs (all r , 0.200, all p . 0.050). There with factors of group, AMBI, RMBI, PTSS, and was no significant difference in total percent combat history, and covariate of total percent CRs acquisition or extinction CRs in veterans with vs. during acquisition, confirmed this main effect of without a history of combat exposure (independent- group (F(1,62) ¼ 6.29, p ¼ 0.004), as well as signifi- samples t-tests, all t , 1.50, all p . 0.100). Total cant interactions between AMBI and RMBI percent CRs during acquisition and extinction were (F(1,62) ¼ 6.29, p ¼ 0.015), between RMBI and not significantly correlated with PCL-M total scores group (F(1,62) ¼ 4.48, p ¼ 0.038), between block, or scores on any of the three PTSD symptom clusters AMBI, and combat history (F(4,248) ¼ 4.62, (all r , 0.250, all p . 0.050). p ¼ 0.001) and between block, combat history, Figure 2A shows eyeblink responding across the PTSS, and group (F(4,248) ¼ 3.44, p ¼ 0.009); no five blocks of acquisition conditioning in the delay other effects or interactions approached significance and omission groups. A repeated measures ANOVA (all p . 0.100). The AMBI £ RMBI interaction was on mean percent CRs over the five acquisition due to much higher responding during extinction in blocks, with factors of group (delay vs. omission), the small number (n ¼ 6) of AMBI-uninhibited and RMBI (inhibited vs. uninhibited), AMBI (inhibited RMBI-inhibited veterans (M ¼ 45.8% CRs, SD 44.3%) vs. uninhibited), PTSS (with vs. without), and compared to the other cells (M range 29.4–30.9% history of exposure to combat (combat vs. non- CRs, SD 25.4–27.5%); this difference did not survive combat), and covariate of UR magnitude, revealed post hoc testing (univariate ANOVA, F(3,83) ¼ 0.62, a significant within-subjects effect of block p ¼ 0.605), probably due to the low sample size in that (F(4,248) ¼ 4.03 p ¼ 0.003), a block £ group inter- action (F(4,248) ¼ 2.84, F ¼ 0.025) and a three-way cell. The group £ RMBI interaction was due to interaction between block, RMBI and PTSS significantly higher responding during extinction (F(4,248) ¼ 3.33, p ¼ 0.011); no other effects or among RMBI-inhibited individuals in the omission interactions were significant (all p . 0.050). Figure 2B group (Figure 3B; independent-samples t-test, % CRs % CRs Behavioral inhibition in veterans 39 Extinction Extinction B 100 A 100 Inhibited Delay (n = 43) Uninhibited Omission (n = 44) * * 38 28 24 33 0 0 123 45 Delay Omission Blocks (of 4 trials) Extinction, block 1 C 100 Inhibited Uninhibited 15 17 52 42 Combat Non-Combat Figure 3. Eyeblink extinction data. (A) Given their higher level of responding during acquisition, the delay group (CS and US overlap and co-terminate) showed significantly faster extinction than the omission group (CR causes omission of US) (repeated-measures ANOVA, F(1,62) ¼ 6.29, p ¼ 0.004). (B) Within the omission group, veterans with uninhibited childhood temperament showed fewer CRs than those with inhibited childhood temperament (independent-samples t-test, t(42) ¼ 2.14, p ¼ 0.039). (C) Among non-combat veterans, those with inhibited current temperament showed more CRs during the first extinction block than those with uninhibited current temperament (independent-samples t-test, t(22) ¼ 2.11, p ¼ 0.047). N is shown at the base of each bar in (B) and (C). Asterisks indicate significant difference ( p , 0.050). t(42) ¼ 2.14, p ¼ 0.039) but not in the delay Discussion group (t(41) ¼ 1.36, p ¼ 0.183). The block £ Given that avoidance reflects a learned association AMBI £ combat history was due to higher respon- between implicit or explicit cues, individual differ- ding during block 1 of extinction AMBI-inhibited ences in vulnerability to anxiety disorders such as non-combat veterans than in AMBI-uninhibited non- PTSD may at least in part reflect differences in combat veterans (Figure 3C; independent-samples t- associative learning. This study was designed to test, t(57.7) ¼ 2.11, p ¼ 0.047); there was no such investigate whether differences in associative learning effect of AMBI in combat veterans (t(22) ¼ 0.024, and extinction might be related to PTSD symptom p . 0.500). To investigate the block £ combat severity, history of combat exposure, or BI. Indeed, history £ PTSS £ group interaction, separate post hoc total conditioned responding during acquisition was tests were conducted on extinction data from the delay correlated with childhood, but not current, BI; and omission groups. In the omission group, veterans extinction was delayed in veterans with PTSS with PTSS gave significantly more CRs during regardless of current or childhood BI, although BI extinction blocks 1 and 2 (Figure 4A; independent- did interact with both combat history and training samples t-tests, all t . 2.00, all p , 0.050) but not group to affect extinction. A secondary objective of the during blocks 3–5 (all t , 1.5, all p . 0.100); the study was to determine whether the AMBI/RMBI interaction with combat did not survive post hoc scale, a self-report measure used to assess current and analysis (all p . 0.050). There was no significant childhood BI, was associated with PTSD symptoms in effect of PTSS, nor any interaction with combat veterans; the results demonstrated that current BI and history, in the delay group (Figure 4A). PTSS were correlated, although PTSS status was best % CRs % CRs % CRs 40 C. E. Myers et al. Delay group Omission group A B 100 100 PTSS (n = 12) PTSS (n = 17) * non-PTSS (n = 32) 80 80 non-PTSS (n = 26) 60 60 40 40 20 20 0 0 A1 A2 A3 A4 A5 E1 E2 E3 E4 E5 A1 A2 A3 A4 A5 E1 E2 E3 E4 E5 Blocks Blocks Figure 4. Eyeblink extinction data. (A) There was no difference in acquisition or extinction as a function of PTSS in the delay group (CS and US overlap and co-terminate) (all p . 0.050). (B) In the omission group (CR causes omission of US), veterans with PTSS showed more eyeblink-CRs than those without PTSS during extinction blocks 1 and 2 (independent-samples t-tests, all t . 2.00, all p , 0.050) but not during blocks 3–5 (all t , 1.5, all p . 0.100). PTSS, severe, current PTSD symptoms. Asterisks indicate significant differences ( p , 0.050). predicted by a combination of current BI and validation paper, nevertheless resulted in only slightly combat exposure measures. We discuss these findings more than half of all veterans in this sample being further below. classed as “inhibited” based on each scale. This indicates that, even though the veteran means are higher than those in the validation sample, the AMBI/RMBI and PTSD symptoms incidence of “uninhibited” vs. “inhibited” tempera- ment (based on either current or childhood behavior) Consistent with other studies that have demonstrated is comparable. increased vulnerability to PTSD in veterans exposed Internal consistency of AMBI/RMBI question- to combat, and in females, we found a higher naires, and correlations between AMBI/RMBI incidence of PTSS in combat veterans, and in females, subscale scores, were similar to those reported by in the current sample. PTSS was also more prevalent Gladstone and Parker (2005); however, that paper in participants who self-reported current BI based on also reported gender differences, with females show- AMBI. Furthermore, within this veteran sample, a ing higher RA than males on both AMBI (4.0 vs. 3.3) model including the individual’s history of exposure to and RMBI (3.1 vs. 2.5). There was no significant combat and the presence/absence of current BI could gender difference in this sample, although the means predict PTSS status with slightly over 80% accuracy. were similar to those observed in the validation To our knowledge, this study is the first documenting study, indicating that the lack of a significant a relationship between self-reported current BI and difference in this sample may have been due to the current PTSD symptom severity. low inclusion of females, although there may also be Although current and retrospective BI were highly unique characteristics of the female veteran popu- correlated in this sample, retrospective BI (based on lation. It is also worth noting that the internal RMBI scores) did not account for additional variance consistency of the RA subscales was relatively low in in PCL-M scores beyond what was already accounted both this sample and in the Gladstone and Parker for by current BI (based on AMBI scores). This is (2005) report, which could contribute to inconsistent broadly consistent with the conclusion of Gladstone findings. and Parker (2005), in their original validation article, A final note on the questionnaire data is that, that AMBI is more useful as a predictor of con- although the majority (94 of 126) veterans were temporaneous clinical outcomes. classed as non-combat based on CES scoring criteria, This study also provides some initial normative data the mean PCL-M score for non-combat veterans was for AMBI/RMBI scores on a veteran sample. Mean still over 30, as given in Table I, and 20 non-combat AMBI (17.0) and RMBI (12.7) in this sample were veterans met the criteria for current, severe PTSD higher than those reported in the original validation symptoms (PCL-M score 50 þ). Clearly, non-combat paper (Gladstone and Parker 2005) for healthy adult veterans can and do report experiencing PTSD controls (AMBI 12.0, SD 4.7; RMBI 8.7, SD 6.1) but lower than those reported for patients with clinical symptoms related to their military service. Given anxiety (AMBI 19.4, SD 6.3; RMBI 15.0, SD 8.7). that even individuals with subthreshold PTSD The cutoff for high inhibition (AMBI 16 þ ,RMBI symptoms are at risk for other medical and psychiatric 12 þ), based on median split of the data in the disorders, including but not limited to subsequent % CRs % CRs Behavioral inhibition in veterans 41 development of full-blown PTSD (Yarvis and Schiess Eyeblink extinction 2008; O’Donnell et al. 2009), this is an important During extinction, participants in the delay population for continued study. group showed fewer CRs (extinguished faster) than the omission group. This is consistent with the partial reinforcement extinction effect (PREE), an increased Eyeblink acquisition resistance to extinction that is observed after training with partial reinforcement, as compared to paradigms Although current BI was most strongly correlated with in which reinforcement is present on every trial during the degree of current PTSD symptoms, childhood BI training (Nation and Woods 1980; Flaherty 1985). was significantly correlated with the acquisition of Among several theories that have been put forward to eyeblink CRs. This was particularly true in veterans explain the PREE is the sequential theory of Capaldi without PTSS; as Figure 2B shows, veterans with (1966); at its simplest, this theory acknowledges that, PTSS tended to learn quickly regardless of BI. The during acquisition under conditions of partial finding that there was no main effect of PTSS in this reinforcement, subjects learn that trials on which the sample may just reflect the relatively small number of CS is not paired with the US are often followed by PTSS veterans. Still, the absence of a main effect of trials in which the CS and US are paired; thus, on any PTSS on learning in this study is broadly consistent given trial, the current CS may be paired with the US, with several prior studies documenting no effects of even if it was not so paired on the previous trial. PTSD on the acquisition of classically conditioned Hence, during the early extinction trials, when the CS CRs (Ayers et al. 2003; Orr et al. 2006; Vythilingam is no longer followed by the US, the subject is already et al. 2006), although these prior studies considered “trained” to continue responding to the CS despite a patients with a clinical diagnosis of PTSD, whereas train of CS-noUS trials. By contrast, for subjects given our study included both combat and non-combat acquisition training under delay contingencies, the veterans with PTSS assessed by self-report. first CS-noUS extinction trial is a novel event, which is The finding that childhood (RMBI), not adult more likely to cause a disruption in responding. (AMBI), temperament was associated with learning Given this interpretation of the PREE, it is speed suggests that faster learning is associated with a interesting that, in this study, although there was no preexisting character trait, rather than having been effect of PTSS on extinction following delay con- acquired later in life through normal aging or via ditioning, veterans with PTSS did show delayed exposure to combat or other stressors, although as extinction in the omission group. Specifically, during mentioned above, we cannot rule out the possibility the early extinction blocks, veterans with PTSS in the that life experiences modify an individual’s self-report omission group showed strong responding to the CS of retrospective measures. There was no increase in (Figure 4B). Similarly, there was extinction resistance UR magnitude as a function of RMBI, indicating that in the omission group among veterans with high increased sensitivity to the US is not a sufficient RMBI (Figure 3B). This suggests that there may be explanation for the relationship between childhood BI individual differences in PREE, such that certain and learning. The relationship between high child- groups, such as those with childhood BI and/or PTSS hood BI and learning is also broadly consistent with may be more resistant to extinction following partial animal models of anxiety vulnerability: specifically, reinforcement. Interestingly, persistent responding to rats bred to show high BI, assessed through open field stimuli that no longer signal important outcomes has behavior and other behavioral and physiological also been proposed as a mechanism contributing characteristics, also show facilitated acquisition of to learned helplessness and depression (Nation and conditioned eyeblink responses (Ricart et al. 2011). Woods 1980), a condition which is highly comorbid There was also faster acquisition of eyeblink CRs with PTSD (Foa et al. 2006) as well as with subclinical in the delay group than in the omission group; this PTSD (Yarvis and Schiess 2008). This raises the is consistent with findings from prior eyeblink con- question of whether some features of PTSD and ditioning studies (Logan 1951; Massaro and Moore depression might reflect the same underlying associ- 1967). In general, training curves obtained under ative learning mechanisms. To examine this issue omission contingencies often replicate those observed further, it would be interesting to assess acquisition under partial reinforcement schedules (Church 1964), and extinction with omission contingencies in patients which is often taken to support the position that with depression as well as with both depression eyeblink conditioning is truly classical rather than and PTSS. operant in nature (Coleman 1975). The presence of Extinction was also reduced for non-combat the main effect of group indicates that high-RMBI individuals do not simply produce more CRs under all veterans with inhibited temperament based on conditions, but that they and low-RMBI individuals AMBI, although this difference was significant only can both modulate their responding as a function of during block 1 of extinction (Figure 3C). It is not clear stimulus contingencies. why this effect should appear in non-combat but not 42 C. E. Myers et al. combat veterans, nor why this interaction involves increasing risk for the development of clinical PTSD, AMBI rather than RMBI. One difficulty with using subclinical PTSD poses its own associated health the AMBI/RMBI scales is that two measurements are costs; veterans with subclinical PTSD but without a provided, representing current and retrospective diagnosis of full-blown PTSD are at increased risk for inhibition, and although these two measures are comorbid diseases such as depression, alcohol abuse, generally correlated (as they were in this study), this poor health, and disability following physical injury correlation is not perfect; in addition, the use of two (Yarvis and Schiess 2008; O’Donnell et al. 2009). related scales may reduce the power of either to For this reason, although many studies of PTSD in demonstrate a significant effect. veterans have considered only combat veterans dichotomized as PTSD or non-PTSD based on clinical diagnosis, it is also important to study both Limitations and future directions combat and non-combat veterans and to consider a There are several limitations to this study, most continuum of PTSD symptom severity, including notably the reliance on participants’ memory for subclinical as well as clinical PTSD cases. retrospective measures (such as RMBI and even Despite these limitations, this study demonstrates CES). There are also limitations related to this that current BI, assessed by self-report using the sample, including the inclusion of only a small number AMBI, correlates with current, severe PTSD symp- of females, which hindered the investigation of gender toms in veterans; however, AMBI scores alone did not differences, and a range of ages and time since combat predict PTSS as well as a model that included both exposure. Since we were relying on self-report, we were AMBI and combat history as predictive variables, unable to fully investigate the effects of medication, as reflecting the fact that the development of PTSD some individuals were unable to specify their precisely symptoms depends on exposure to stressors as well as medication name or dosage. In addition, although we preexisting vulnerability. However, retrospective used CES to assess the history of exposure to combat, (RMBI) rather than current (AMBI) BI was associ- participants may have been exposed to traumatic ated with faster eyeblink conditioning. To the extent events unrelated to military service. An important that RMBI indexes childhood BI that pre-dates issue in understanding PTSD in veterans is not only combat exposure in veterans, this finding is consistent psychopathology which develops directly in response with the idea that a bias for faster associative learning to traumatic events experienced during military may play a role in establishing risk for PTSD, and service (e.g. combat exposure), but also the degree suggests that the facilitated conditioning sometimes to which prior exposure to combat and other service- observed in patients with clinically diagnosed PTSD may be related to preexisting vulnerability for PTSD, related stressors affects veterans’ risk for PTSD if exposed to further traumatic events during sub- rather than emerging selectively as a consequence sequent civilian life. Although we did not find of exposure to trauma or development of PTSD significant effects of combat history on acquisition or symptoms per se. extinction in this study, with the exception of a However, although inhibited temperament is a risk combat-AMBI interaction that was significant for only factor for PTSD, it is neither necessary nor sufficient a single block during extinction, this is likely to be due for PTSD. In this sample, there were individuals to the inclusion of rather few combat veterans in this classified as uninhibited on both AMBI and RMBI sample; studies focusing on combat veterans might who nevertheless score above the cutoff for PTSS, as more clearly address this issue. well as individuals with high AMBI/RMBI scores but Given the low number of combat veterans in this without PTSS. The finding that PTSS alone did not sample, there was a high rate of PTSS, including over significantly affect acquisition in this sample suggests one-fifth of the 94 non-combat veterans. Indeed, non- that BI is strongly linked to associative learning, combat veterans in this sample reported an average of whether or not an individual is subsequently exposed almost one cluster B symptom and more than one to trauma (e.g. combat) and/or develops PTSS. Thus, symptom each from clusters C and D (see Table I). inhibited temperament and faster conditioning may be This indicates that non-combat veterans may experi- preexisting factors that provide one (but certainly not ence severe stressors unrelated to combat at a higher the only) pathway to risk for PTSD. However, this rate than would normally be expected from the general finding of delayed extinction in PTSS veterans population. Indeed, there is some evidence that following acquisition under omission contingencies individuals who exhibit subclinical PTSD symptoms, is consistent with the idea that extinction resistance but fall short of diagnostic criteria, are at heightened may emerge as an acquired sign following exposure risk of future exposure to trauma, possibly because of to trauma and/or development of PTSD symptoms; an increase in behaviors (e.g. substance abuse) that nonetheless, milder but significant extinction resis- magnify risk for trauma and/or a decrease in normal tance also appeared in behaviorally inhibited, psychological processes for recognizing and respond- non-combat veterans in this study, suggesting that, ing to threat (Orcutt et al. 2002). In addition to at least under some conditions, extinction resistance Behavioral inhibition in veterans 43 Fincham D, Smit J, Carey P, Stein DJ, Seedat S. 2008. 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Behaviorally inhibited temperament is associated with severity of post-traumatic stress disorder symptoms and faster eyeblink conditioning in veterans

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Taylor & Francis
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© Informa Healthcare USA, Inc.
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1607-8888
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1025-3890
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10.3109/10253890.2011.578184
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Abstract

Prior studies have sometimes demonstrated facilitated acquisition of classically conditioned responses and/or resistance to extinction in post-traumatic stress disorder (PTSD). However, it is unclear whether these behaviors are acquired as a result of PTSD or exposure to trauma, or reflect preexisting risk factors that confer vulnerability for PTSD. Here, we examined classical eyeblink conditioning and extinction in veterans self-assessed for current PTSD symptoms, exposure to combat, and the personality trait of behavioral inhibition (BI), a risk factor for PTSD. A total of 128 veterans were recruited (mean age 51.2 years; 13.3% female); 126 completed self-assessment, with 25.4% reporting a history of exposure to combat and 30.9% reporting current, severe PTSD symptoms (PTSS). The severity of PTSS was correlated with current BI (R ¼ 0.497) and PTSS status could be predicted based on current BI and combat history (80.2% correct classification). A subset of the veterans (n ¼ 87) also completed the eyeblink conditioning study. Among veterans without PTSS, childhood BI was associated with faster acquisition; veterans with PTSS showed delayed extinction, under some conditions. These data demonstrate a relationship between current BI and PTSS, and indicate that the facilitated conditioning sometimes observed in patients with PTSD may partially reflect personality traits such as childhood BI that pre-date and contribute to vulnerability for PTSD. Keywords: Behavioral inhibition, eyeblink, classical conditioning, learning, post-traumatic stress disorder (PTSD), veterans Introduction polymorphisms (Binder et al. 2008; Amstadter et al. 2009), female sex (Tolin and Foa 2006), prior In the wake of exposure to a traumatic event, some exposure to highly stressful situations such as combat, individuals develop post-traumatic stress disorder rape, or other trauma (e.g. North and Smith 1990; (PTSD), and others may experience varying degrees Davidson 2000; Seng et al. 2009), brain and of sub-clinical PTSD symptoms, including heightened physiological abnormalities (Pitman et al. 2006; emotional responses to and avoidance of reminders Liberzon and Sripada 2008), and various socio- of the trauma. The wide range of PTSD symptom behavioral variables including personality traits severity among individuals exposed to similarly (Engelhard et al. 2006; Gil and Caspi 2006; Qouta stressful traumatic events (Pitman et al. 1987; Orr et al. 2007). As one example, behavioral inhibition et al. 1993; Shalev et al. 1993) suggests that (BI) is a temperamental tendency for avoidance of or preexisting vulnerability factors modulate an individ- ual’s risk to develop PTSD. Several vulnerability withdrawal from unfamiliar social and nonsocial factors have been identified, including genetic situations (Fox et al. 2005). This tendency develops Correspondence: C. E. Myers, Stress & Motivated Behavior Institute, VA Medical Center, Mail Stop 129, 385 Tremont Avenue, East Orange, NJ 07108, USA. Tel: 973 676 1000 Ext. 1810. Fax: 973 395 7111. E-mail: [email protected] 32 C. E. Myers et al. early in life and is relatively stable over development study suggests that delayed extinction does not (Degnan and Fox 2007). Individuals with high BI pre-date PTSD. These studies did not take into are at increased risk for PTSD (Fincham et al. 2008; account preexisting vulnerabilities, such as tempera- Kashdan et al. 2009) as well as other anxiety disorders ment, which might help account for the discrepant (Hirshfeld et al. 1992). findings. Diathesis models of PTSD emphasize the Here, we consider a complementary approach to dynamic interaction of preexisting vulnerabilities and understanding the relationship between vulnerability environmental interactions. An influential theory factors and associative learning, by testing acquisition of PTSD (Pitman 1988; Pitman et al. 2000) suggests and extinction of classically CRs in veterans self- that many PTSD symptoms reflect learned associ- assessed for BI, history of exposure to combat, and ations in which cues (conditioned stimulus or CS) current PTSD symptom severity. Our hypothesis was present at the time of the trauma (unconditioned that if facilitated conditioning in PTSD partially stimulus or US) come to evoke emotional responses reflects preexisting vulnerabilities such as high BI, (conditioned responses or CRs) similar to those then it should be evident in veterans with high BI but provoked by the event itself. According to this model, without PTSD. Alternatively, if facilitated learning individual differences in the speed of acquisition of the emerges only as a symptom of PTSD and/or as a CR, and in extinction of the CR when the CS is consequence of exposure to trauma, then it should be no longer paired with the US, could promote evident only in veterans with severe PTSD symptoms individual differences in the development and main- tenance of PTSD symptoms. and/or history of exposure to combat. Consistent with this view, many studies have In this study, we considered classical eyeblink reported facilitated acquisition of CRs and delayed conditioning, in which the CS is a tone, the US is extinction of CRs in individuals with PTSD, an airpuff aimed at the eye that evokes a protective compared to non-PTSD controls (Grillon and eyeblink, and the CR is an anticipatory eyeblink that Morgan 1999; Orr et al. 2000; Peri et al. 2000; occurs after CS onset but before US arrival. Blechert et al. 2007; Burriss et al. 2007; Wessa and Participants were randomly assigned to receive Flor 2007; Jovanovic et al. 2010), although other training under delay contingencies, in which the CS studies have found no such effects (Ayers et al. 2003; and US overlap and co-terminate, or omission Orr et al. 2006; Vythilingam et al. 2006; Ginsberg et al. contingencies, in which a CR causes omission of the 2008a,b). The variability of results may partially US. Typically, imposition of an omission contingency reflect different experimental design and/or different into eyeblink conditioning results in lower perform- parameters such as stimulus duration and intensity. ance, in terms of number of CRs produced Such between-group studies do not address the (Logan 1951; Massaro and Moore 1967); accordingly, question of whether observed abnormalities in the inclusion of an omission group in this associative learning are acquired symptoms of PTSD, study allowed us to examine whether veterans with emerge as a consequence of exposure to stressful high BI, history of combat exposure, and/or severe events, or pre-date PTSD and exposure to trauma. In the latter case, strong learning of avoidant and PTSD symptoms could modulate their responding as emotional responses to trauma-related cues and a function of CS–US contingency. Following eyeblink resistance to extinction of these responses might bias acquisition, each participant also received a series of an individual to develop PTSD if exposed to traumatic CS-alone trials, during which the eyeblink CR was events. The few studies that have attempted to address expected to extinguish, allowing us to determine this question have yielded discrepant results. For whether delayed extinction occurred as a function of example, a prospective study of classical conditioning BI, history of combat exposure, and/or severe PTSD in firefighter recruits found that the degree of delayed symptoms. CR extinction, assessed during firefighter training, As our measure of BI, we used the Adult and was significantly correlated with PTSD symptom Retrospective Measures of Behavioural Inhibition severity following subsequent exposure to a traumatic (AMBI/RMBI), two recently developed self-report event (Guthrie and Bryant 2006), suggesting that measures that allow assessment of current and delayed extinction pre-dates trauma exposure in childhood inhibited temperament (Gladstone and vulnerable individuals. By contrast, a study of mono- Parker 2005); however, a relationship between zygotic twins discordant for combat exposure found these measures and current PTSD symptom status that combat-exposed participants with PTSD showed has not been established. Therefore, a secondary normal extinction of a conditioned fear response, purpose of this study was to determine whether compared with both their non-combat-exposed, non- AMBI/RMBI scores were significantly related to PTSD co-twins and with combat-exposed, non-PTSD participants, although extinction recall was deficient presence vs. absence of current, severe PTSD on the following day (Milad et al. 2008); thus, this symptoms in veterans. Behavioral inhibition in veterans 33 Methods “uninhibited”, whereas individuals scoring from 16 to 32 are classified as “inhibited” (Gladstone and Parker Participants 2005). In addition to a total AMBI score, items Veterans (n ¼ 128) were recruited from the New group into four subscales derived from factor analysis Jersey Health Care System (NJHCS), East Orange, (Gladstone and Parker 2005): “fearful inhibition” NJ. Participants included 111 males and 17 females (FI), “risk avoidance” (RA), “non-approach” (NA), (13.3%), with mean age 51.2 years (SD 8.0, range and “low sociability” (LS). Items in the FI subscale 23–65) and mean education 13.4 years (SD 1.7, range assess the general tendency to respond with wariness, 9–20). The group included 94 African–Americans show hypervigilance, and become physically anxious (73.4%), 26 Caucasians (20.3%), and 8 individuals of in response to novel social situations (e.g. “Do you Mixed/Other Race (6.3%). When asked to identify intend to withdraw and retreat from those around specific wars or conflicts in which they had served, 44 you?”). Items in the RA subscale assess the tendency veterans reported having served during the Vietnam to avoid physical risk, adventurous activities, and high conflict (approx. 1970–1975), 17 during Operation social stimulation (e.g. “If physically able, would you Desert Storm (1991), 7 during Operation Enduring enjoy adventure holidays with some element of risk?”). Freedom/Operation Iraqi Freedom (2001 þ), and 39 Items in the NA subscale assess willingness to engage during peacetime or no specific conflict; others others in novel social situations (e.g. “Do you tend to reported having served during various conflicts introduce yourself to new people?”). Items in the LS including operations in Granada, Panama, and the subscale assess preference for solo activities (e.g. “Do Middle East. Veterans were not included or excluded you prefer your own company to the company of based on any medical or psychiatric history, but others?”). were asked to self-report current medications; 41 The RMBI is a 18-item self-report inventory used to participants (32%) self-reported taking psychoactive assess childhood memories of exhibiting inhibition to medications. Although some participants were able to the unfamiliar; individuals scoring from 0 to 11 are clearly identify the name of their medications, others classified as “uninhibited”, whereas individuals scor- simply reported the use of medication (e.g. “anxiety ing from 12 to 25 are classified as “inhibited” meds” or “anti-depressant”). Thus, further analysis (Gladstone and Parker 2005). Like the AMBI, there regarding medication usage in this sample was not are four RMBI subscales derived from factor analysis possible. (Gladstone and Parker 2005): “fearful inhibition” Participants received payment at the rate of $30 (FI), “risk avoidance” (RA), “non-approach” (NA), per hour (maximum of $60) for their participation and “shyness and sensitivity” (SS). Items for the first in the study. Testing generally occurred between three subscales are similar to those on the AMBI, but 10:00–12:00 and 13:00–15:00 h; no obvious differen- target memories of childhood behaviors. The SS ces in subject demographics or experimental data were subscale assesses self-rated shyness, particularly at observed as a function of testing time. All participants school. The RMBI allows respondents to endorse a gave written informed consent before initiation of any “do not remember” item. For items in which experimental procedures; procedures were approved by participants endorsed “do not remember,” scores the NJHCS Institutional Review Board and were were prorated based on responses to the remaining conducted in accordance with the Declaration of questions on the same RMBI subscale, with reverse Helsinki and guidelines established by the Federal scoring taken into account. Any participant who Government for the protection of human subjects. endorsed “do not remember” on more than 50% of the total RMBI items was scored as incomplete. The CES is a 7-item self-report questionnaire that Self-report measures assesses exposure to stressful military events, with After informed consent, participants completed a items rated on frequency, duration, and degree of battery of paper-and-pencil questionnaires prior to exposure; for example, the question “Were you ever instrumentation for electromyography (EMG) surrounded by the enemy?” can be endorsed at a level recording. These questionnaires typically required of 1 ¼ “no” to 5 ¼ “more than 12 times.” Total CES 20–30 min to complete. The package included score is calculated from a sum of weighted scores; as in AMBI/RMBI (Gladstone and Parker 2005), the prior studies (Ginsberg et al. 2008a), veterans with a Combat Exposure Scale (CES; Keane et al. 1989), CES score of 0–7 were classified as non-combat and the PTSD Checklist-Military version (PCL-M; whereas those with a score of 8 þ were classified as Blanchard et al. 1996). having a history of exposure to combat. The AMBI is a 16-item self-report inventory that The PCL-M is a 17-item self-report questionnaire assesses current tendency to respond to new stimuli that asks about the presence and the frequency of with inhibition and/or avoidance, and it has also been PTSD symptoms in response to stressful military shown to be a measure of anxiety proneness; experiences; symptoms are rated according to how individuals scoring from 2 to 15 are classified as much they have bothered the participant in the past 34 C. E. Myers et al. month, on a scale from “Not at all” to “Extremely.” produce a unconditioned response (UR). Data from Specific questions correspond to DSM-IV symptom the participants who failed to produce URs, or failed clusters including cluster B (re-experiencing the to remain awake throughout the experiment, were traumatic event), cluster C (avoidance/numbing), discarded from analysis. and cluster D (increased arousal). PCL-M scores of Conditioning then commenced. For participants in the 50 þ have been shown to be a predictor of PTSD delay group, the CS was a 500-ms 83-dB, 800-Hz in military samples (Weathers et al. 1993; Blanchard pure tone (50 ms rise/fall) that co-terminated with the et al. 1996). Accordingly, we also categorized US, a 50-ms airpuff; the inter-trial interval varied participants according to the presence or the absence between 15 and 25 s. For participants in the omission of current, severe PTSD symptoms (PTSS) based on group, all parameters were identical to delay training, this cut-off. except that emitting a CR at least 40 ms prior to the airpuff prevented US delivery. Five blocks of 12 Eyeblink conditioning acquisition trials were presented (total 60 trials). In both delay and omission groups, acquisition trials Materials and apparatus. The eyeblink conditioning were followed by 20 extinction trials that were similar apparatus and procedures were as previously to the acquisition trials except that the US was not described (Beck et al. 2008). Auditory stimuli were presented. produced with Coulbourn Instruments (Allentown, PA, USA) signal generators and passed to a David Clark aviation headset (Model H10–50, Worchester, Data processing. Processing of eyeblink responses MA, USA). Sound levels were verified with a Realistic followed methods previously reported (Servatius sound meter (RadioShack, Fort Worth, TX, USA). et al. 1998; Beck et al. 2008). To determine the Airpuffs were produced by pressurizing ambient air to occurrence of an eyeblink, EMG activity was first low- 3.5 psi (Fu¨rgut Industries, Aitrach, Germany), and pass filtered using a Lowess filter (Stat-Sci, Tacoma, released through Silastic tubing attached to the boom WA, USA) using a time constant of 0.025 and a of the headphones by a computer-controlled solenoid smoothing interval of 5. Using the filter values, activity valve (Clipper Instruments, Cincinnati, OH, USA). greater than 0.2 (unitless) corresponds to an eyeblink. The boom was placed 1 cm from the eye and aimed at An a-response (orienting response) was scored when it. To transduce the eyelid EMG signal, pediatric an eyeblink occurred within 80 ms of CS onset; these silver/silver chloride EMG electrodes with solid gel responses rarely occur with the present equipment were placed above and below the left eye, with the configuration. A CR was scored when an eyeblink was ground electrode placed on the neck. The EMG signal elicited 80 ms after CS onset but before US onset. was passed to a medically isolated physiological An UR was scored when an eyeblink was produced amplifier (UFI, Morro Bay, CA, USA), low-pass 0–100 ms after US onset during the three US-alone filtered and amplified 10 K. The signal for EMG was presentations preceding training. sampled at 200 Hz by an A/D board (PCI 6025E, National Instruments, Austin, TX, USA) connected to an IBM-compatible computer. Software control Data analysis of stimulus generation was accomplished with LabView (National Instruments). For the omission Questionnaire scores were analyzed using t-test or contingency, a time-varying Gabor filter processed the univariate analysis of variance (ANOVA) for continu- data up to 10 ms prior to US trigger. If a CR was ous values and chi-square tests for categorical values. detected during this period, the US trigger was not Inter-item relationships and correlations across scores initiated. were analyzed using the Pearson correlation coeffi- cient (using Yates continuity correction for 2 £ 2 tables) or Cronbach’s a. Stepwise linear regression Procedures. Participants were pseudorandomly was used to investigate the ability of questionnaire assigned to the delay and omission groups: for each scores to predict PCL-M scores and stepwise pair of participants, the first was randomly assigned discriminant analysis was used to investigate the to one group and the second was assigned to the ability of categorical values based on questionnaire other group. Participants were seated in a comfortable scores to predict PTSS status. chair and fitted with EMG electrodes; they were For eyeblink data, the dependent measure was instructed that the study evaluated responses to tones percent CRs scored within each block of trials and and airpuffs to the eye, that they were to watch a silent total percent CRs over the entire acquisition or video of their choice (e.g. Free Willy with sound extinction phase. Total scores were analyzed by muted), and to stay awake. Each participant was Pearson’s correlation to assess relationships with then exposed to three airpuff stimuli; these trials continuously valued questionnaire scores, and uni- served to verify the ability of the participant to variate ANOVA to assess relationships with categorical Behavioral inhibition in veterans 35 values; scores across the five blocks of acquisition endorsing “Moderate” or higher for an average of and extinction were analyzed by repeated measures 1.5 cluster B symptoms (SD 2.0), 2.4 cluster C ANOVA, with post hoc ANOVA and t-tests as symptoms (SD 2.6), and 2.1 cluster D symptoms appropriate. As explained below, UR magnitude (SD 1.9). Scores on all PTSD symptom clusters were was included as a covariate in all assessments of significantly correlated with each other (Pearson’s r, acquisition data, and total percent CRs during all r . 0.650, all p , 0.001) and with CES score acquisition was included as a covariate in all (Pearson’s r, all r . 0.350, all p , 0.001). Total PCL- assessments of extinction data. M scores, as well as cluster B, C, and D scores, were all All ANOVAs used type III sum-of-squares, as significantly higher in combat than non-combat appropriate for designs in which cell sizes are unequal veterans (Table I; independent-samples t-tests, all (and some cells may be empty). All tests were two- p , 0.004). tailed, with threshold for significance set at 0.050. Following Weathers et al.’s (1993) cutoff of 50þ as Where multiple pairwise comparisons were made, the indicating current, severe (PTSS), 39 of our 126 Bonferroni correction was used to reduce alpha to veterans were classed with PTSS (30.9%); this protect against risk of increased family-wise error; the included 13 of the 32 combat veterans (40.6%) but corrected alpha is reported in the text only when only 20 of the 94 non-combat veterans (21.3%), a p-values approach 0.050 but fall short of the corrected statistically significant difference (Yates-corrected alpha. chi-square x ¼ 14.48, df ¼ 1, p , 0.001). Among Because of the low number of females in this study, the 17 females in this study, 10 had PTSS (58.8%) and the fact that random assignment led to only three compared with only 29 of 109 males (26.6%), females being assigned to the omission group, we did a statistically significant difference (Yates-corrected not consider gender as a factor in the analysis of chi-square x ¼ 5.72, df ¼ 1, p ¼ 0.017). eyeblink data. When the eyeblink analyses described above were rerun on the subset of data from males only, the general pattern of results was qualitatively Adult and retrospective measures of behavioural inhibition. similar to that obtained for the complete dataset, All 126 participants responded to all AMBI questions, although the reduced sample size meant lower power except for one participant who failed to enter a to detect significant differences. response to question 3 (“Do you tend to become quiet?”). Three participants endorsed “do not remember” responses on all RMBI questions, and so Results their total RMBI and RMBI subscales could not be calculated. These three participants were accordingly Questionnaire data included in the analysis of AMBI but not RMBI data. CES and PCL-M. Of the total sample (n ¼ 128), two Among the remaining 123 participants, only four participants did not complete any questionnaires, and endorsed more than one “do not remember” their data were dropped from all further analysis. responses on RMBI. RMBI item response rates Among the remaining 126 participants, 94 (74.6%) ranged from 92.7% (question 3: “Were you reluctant were classed as non-combat based on CES scores; the to go to school on your first day or the first day after remaining 32 were classed as combat (25.4%). Mean holidays?”) and 93.5% (question 4: “Did you prefer CES score for the non-combat veterans was 1.5 (SD parties with crowds of children rather than small 2.5); for the combat veterans, it was 19.6 (SD 8.8). gatherings?”) to 100% (8 questions total). Mean PCL-M score for the 126 participants was Mean AMBI/RMBI total scores and subscale scores 38.2 (SD 18.7, range 17–85), with participants for the veteran sample are given in Table II. Both Table I. Mean (SD) PCL-M total scores and scores for PTSD cluster B, C, and D symptoms in individuals with inhibited vs. uninhibited temperament based on AMBI and RMBI, and with vs. without combat history. Combat history AMBI RMBI (n ¼ 126) (n ¼ 126) (n ¼ 123) Combat Non-combat Inhibited Uninhibited Inhibited Uninhibited (n ¼ 32) (n ¼ 94) (n ¼ 69) (n ¼ 57) (n ¼ 62) (n ¼ 61) PCL-M (total) 53.50 (17.91) 32.97 (16.00) 43.30 (19.56) 31.98 (15.70) 42.13 (18.99) 33.97 (17.18) * * Cluster B symptoms 3.09 (2.02) 0.97 (1.68) 1.97 (2.13) 0.95 (1.67) 1.87 (2.17) 1.13 (1.72) * * Cluster C symptoms 4.41 (2.24) 1.74 (2.32) 3.01 (2.65) 1.70 (2.30) 2.98 (2.71) 1.80 (2.26) * * Cluster D symptoms 3.19 (1.93) 1.76 (1.77) 2.75 (1.81) 1.35 (1.75) 2.63 (1.90) 1.62 (1.76) * * Note: Asterisks indicate significant differences (ANOVA with factors of combat history and AMBI/RMBI, with alpha corrected to 0.004 to protect against increased family-wise error) between inhibited/uninhibited and combat/non-combat veterans (F . 4.00, p , 0.004). PCL-M, PTSD Checklist-Military version; AMBI/RMBI, Adult/Retrospective Measure of Behavioural Inhibition. 36 C. E. Myers et al. veterans in this sample were “inhibited” based on Table II. Mean (SD) AMBI and RMBI total scores and subscale scores for the complete set of 126 veterans and for the subset of AMBI scores. There were no significant differences in 87 veterans who produced useable eyeblink conditioning data. gender distribution or history of combat exposure among individuals classed as inhibited vs. uninhibited Total sample Eyeblink sample (n ¼ 126) (n ¼ 87) on AMBI or RMBI (all x , 1.00, all p . 0.500). Among veterans classed as “inhibited” based on RMBI total score 12.7 (6.6) 12.6 (6.7) RMBI, 26 had PTSS (41.9%) compared with only Non-approach (NA) 4.5 (2.9) 4.5 (2.9) 12 of those classed as “uninhibited” (19.7%), a Fearful inhibition (FI) 2.5 (2.3) 2.5 (2.3) significant difference (Yates-corrected chi-square, Risk avoidance (RA) 2.9 (1.4) 2.7 (1.4) Shyness & sensitivity (SS) 2.8 (2.0) 2.9 (2.2) x ¼ 7.14, df ¼ 1, p ¼ 0.008). Similarly, among AMBI total score 17.0 (6.1) 17.2 (6.4) those classed as “inhibited” based on AMBI, 29 had Non-approach (NA) 3.2 (1.5) 3.2 (1.6) PTSS (42.0%) compared with only 10 of those classed Fearful inhibition (FI) 7.2 (3.4) 7.3 (3.5) as “uninhibited” (17.5%; Yates-corrected chi-square, Risk avoidance (RA) 3.5 (1.4) 3.5 (1.4) x ¼ 8.76, df ¼ 1, p ¼ 0.003). Low sociability (LS) 3.2 (1.6) 3.3 (1.6) Note: Note that RMBI scores were not available for three veterans in the larger sample, due to endorsement of “do not remember” Predicting PTSD symptoms based on combat history and responses for more than 50% of RMBI items; RMBI scores were BI. Stepwise linear regression on PCL-M scores, with available for all veterans in the eyeblink sample. AMBI/RMBI, Adult/Retrospective Measure of Behavioural Inhibition. factors of total AMBI, total RMBI, and CES score revealed that PCL-M scores could be significantly predicted by a two-variable model including AMBI AMBI and RMBI were significantly higher in (b ¼ 0.501) and CES (b ¼ 0.443). This model could individuals with PTSS (Table I; independent-samples account for significant variance in PCL-M scores t-tests, all t . 2.75, all p , 0.010). Although Glad- (R ¼ 0.497; F(2,120) ¼ 59.27, p , 0.001); the stone and Parker (2005) reported higher RA in addition of RMBI into the model did not account females, the gender difference was not significant in for significant additional variance ( p . 0.050). When this sample (males RMBI: M ¼ 2.8, SD 1.4; AMBI: the regression was repeated replacing AMBI/RMBI M ¼ 3.4, SD 1.4; females RMBI: M ¼ 3.4, SD 1.5; total scores with the eight subscale scores, the best AMBI: M ¼ 4.1, SD 1.3; independent-samples prediction was produced by a three-factor model t-tests, all t , 1.8, 0.050 , p , 0.010), nor were including CES (b ¼ 0.415) and two AMBI subscales: there significant gender differences on any other FI (b ¼ 0.306) and LS (b ¼ 0.221). This model could AMBI/RMBI scores or subscales (all t , 1.0, all also account for significant variance in PCL-M scores p . 0.300). (R ¼ 0.473; F(3,119) ¼ 35.31, p , 0.001); the Internal consistency of AMBI and RMBI total and addition of the remaining AMBI and RMBI subscale scores was estimated using Cronbach’s a, subscales into the model did not account for with reverse scoring for individual questions taken into significant additional variance (all p . 0.050). account. For the 16 questions comprising AMBI total Univariate ANOVA on PCL-M total score, with score, Cronbach’s a ¼ 0.841; for individual AMBI the factors of AMBI and RMBI (“inhibited” vs. subscales, inter-item reliability was high for NA, FI, “uninhibited”) and combat history (exposed vs. and LS subscales (with a ranging from 0.588 to 0.793) non-exposed) revealed significant main effects but lower for RA (a ¼ 0.249). Similarly, inter-item of combat (F(1,115) ¼ 31.98, p , 0.001) and AMBI reliability was high for the 18 questions comprising (F(2,115) ¼ 8.72, p ¼ 0.004) with no main effect of RMBI total score (a ¼ 0.816) as well as for the NA, RMBI and no interactions (all F , 1.00, all FI, and SS subscales (a ranging from 0.600 to 0.722) p . 0.400). Specifically, veterans with a history of but lower for RA (a ¼ 0.233). exposure to combat had higher PCL-M scores than In this sample, AMBI and RMBI scores were non-combat veterans (Figure 1A) and veterans classed highly correlated (Pearson’s r ¼ 0.559, p , 0.001). as inhibited (on AMBI or RMBI) had higher PCL-M Within AMBI, all four subscale scores were signi- scores than uninhibited veterans (Figure 1B). ficantly correlated (all p , 0.008); correlations Considering scores on PCL-M cluster B, C, and D ranged from r ¼ 0.242 (NA vs. RA) to r ¼ 0.644 (FI symptoms, the results were similar (Table I): signifi- vs. LS). Within RMBI, the NA, FI, and SS subscales cant main effects of combat history and AMBI (all were all correlated with each other (all r . 0.600, F . 4.00, all p , 0.050) with no effect of RMBI and all p , 0.001) but RA was not correlated with any of no interactions (all F , 3.0, all p . 0.050). the other subscales (all r , 0.150, all p . 0.300). As noted above, 30.9% of the veterans in our sample According to the cutoffs in the original validation were classed with PTSS, meaning that they scored 50 article of Gladstone and Parker (2005), 62 of 123 or higher on PCL-M. Stepwise discriminant analysis, (50.4%) veterans in this sample were “inhibited” using a priori probability of 30.9%, with independent based on RMBI scores and 69 of 126 (54.8%) variables of AMBI, RMBI, and CES scores, found Behavioral inhibition in veterans 37 AB 80 60 ** Combat (n = 32) Non-Combat (n = 94) AMBI AMBI RMBI RMBI Inhibited Uninhibited Inhibited Uninhibited (n = 69) (n = 57) (n = 62) (n = 61) Figure 1. (A) PCL-M scores are significantly higher in veterans with a history of exposure to combat (F(1,117) ¼ 36.41, p , 0.001. (B) Veterans classed as inhibited (based on either AMBI or RMBI scores) score higher on PCL-M than veterans classed as uninhibited (Univariate ANOVAs, all F . 8.00, all p , 0.010). Asterisks indicate significant differences ( p , 0.050). PCL-M, PTSD Checklist-Military version; AMBI/RMBI, Adult/Retrospective Measure of Behavioural Inhibition. that a model including AMBI (standardized coeffi- The remaining n ¼ 87 participants had been cient 0.762) and CES (standardized coefficient 0.710) randomly assigned to the delay (n ¼ 43) and omission correctly classified 21 of 39 PTSS cases (53.8% (n ¼ 44) groups. There were no significant differences sensitivity) and 80 of 87 non-PTSS cases (92.0% between participants in the delay vs. omission groups selectivity) for an overall 80.2% correct classification. on age, education, PCL-M scores, CES scores, or The addition of RMBI to the model did not AMBI/RMBI scores (independent-samples t-tests, significantly increase predictive power (at tolerance- all p . 0.050). The groups did however differ in to-enter/remove 0.050). gender distribution (Yates-corrected chi-square test, x ¼ 4.62, df ¼ 1, p ¼ 0.032), with 10 females assigned to the delay group but only 3 assigned to Eyeblink conditioning theomission group. Therewerenodifferences Study completion rates and group assignment. Of the 126 between delay and omission groups in the distribution veterans who completed the AMBI, CES, and PCL-M of individuals with a history of exposure to combat, questionnaires, a complete eyeblink conditioning BI, or PTSS (Yates-corrected chi-square tests, all dataset was obtained from 87. For one of these p . 0.200). participants, RMBI could not be calculated, due to endorsement of “do not remember” responses on over 50% of items; this participant’s remaining Unconditioned eyeblink responding. An ANOVA on UR questionnaire scores and eyeblink data were included magnitude, with factors of training group, history of in the analysis. combat exposure, AMBI, RMBI, and PTSS, revealed Conditioning data from the remaining participants no significant main effects or interactions (all (n ¼ 36) were unusable. Specifically, 15 participants F , 2.60, all p . 0.050). There were no significant fell asleep one or more times during the 1-h eyeblink correlations between UR magnitude and any testing session; another 19 participants failed to AMBI/RMBI subscale or PTSD symptom cluster exhibit any eyeblink URs, even after the experimenter (Pearson’s r, all r , 0.20, all p . 0.050). However, made several attempts to reposition the headset. Data there were significant correlations between UR from the remaining participants were lost due to poor magnitude and total eyeblink CRs during the signal quality (noise from ambient electrical fields acquisition phase of eyeblink conditioning (Pearson’s interfering with an EMG signal). r ¼ 0.301, n ¼ 87, p ¼ 0.005). The relationships Those participants who completed the eyeblink between UR magnitude and age, and between conditioning study did not differ from those who did age and total CRs, both fell short of significance not on any measures including gender distribution (all r , 0.200, all p . 0.050). Accordingly, UR (Yates-corrected chi-square test, x ¼ 0.410, df ¼ 1, magnitude but not age was included as a covariate in subsequent analyses of eyeblink acquisition data. p ¼ 0.522), age, education (years), or questionnaire scores (independent-samples t-tests, all p . 0.100). Total percent CRs during extinction were correlated Data from the participants who failed to complete the with total CRs during acquisition (r ¼ 0.543, n ¼ 87, eyeblink study were discarded from further analysis. p , 0.001) but not with age or UR magnitude (all Mean PCL-M Score Mean PCL-M Score 38 C. E. Myers et al. Acquisition Acquisition AB 100 100 Delay (n = 43) noPTSS, Uninhib (n = 36) noPTSS, Inhib (n = 22) Omission (n = 44) 80 80 PTSS, Uninhib (n = 10) PTSS, Inhib (n = 19) 60 60 40 40 20 20 0 0 123 45 123 45 Blocks (of 12 trials) Blocks (of 12 trials) Figure 2. Eyeblink acquisition data. (A) Veterans in the delay group (CS and US overlap and co-terminate) showed more eyeblink-CRs than in the omission group (CR causes omission of US) (repeated-measures ANOVA, F(1,74) ¼ 7.74, p ¼ 0.007). (B) There was also a block £ RMBI £ PTSS interaction, such that, among individuals without current, severe PTSD symptoms (noPTSS), those with childhood BI (Inhib) made more CRs than those with an uninhibited temperament (Uninhib, F(1,56) ¼ 4.55, p ¼ 0.037). RMBI, Retrospective Measure of Behavioural Inhibition. r , 0.200, all p . 0.050). Accordingly, percent CRs shows the interaction between block, RMBI and during acquisition was included as a covariate in PTSS: specifically, there was no difference in subsequent analysis of eyeblink extinction data. responding across blocks between inhibited vs. uninhibited veterans with PTSS (repeated measures ANOVA, F , 1.00, p . 0.500); but among non- PTSS veterans, those with inhibited temperament Acquisition and extinction. Total percent eyeblink gave more CRs than those with uninhibited tempera- CRs during acquisition was significantly correlated ment (F(1,56) ¼ 4.55, p ¼ 0.037). with RMBI scores (Pearson’s r ¼ 0.216, n ¼ 87, Figure 3A shows eyeblink responding across the five p ¼ 0.045) but not AMBI scores (r ¼ 0.185, extinction blocks in the delay and omission groups; p ¼ 0.086); neither AMBI nor RMBI scores were given that the delay group had reached higher levels of correlated with extinction CRs (all r , 0.100, all responding during acquisition (compare Figure 2A), p . 0.500). Of the eight AMBI and RMBI subscales, they extinguished at a steeper rate than the omission none correlated significantly with acquisition or group. A repeated measures ANOVA on these data, extinction CRs (all r , 0.200, all p . 0.050). There with factors of group, AMBI, RMBI, PTSS, and was no significant difference in total percent combat history, and covariate of total percent CRs acquisition or extinction CRs in veterans with vs. during acquisition, confirmed this main effect of without a history of combat exposure (independent- group (F(1,62) ¼ 6.29, p ¼ 0.004), as well as signifi- samples t-tests, all t , 1.50, all p . 0.100). Total cant interactions between AMBI and RMBI percent CRs during acquisition and extinction were (F(1,62) ¼ 6.29, p ¼ 0.015), between RMBI and not significantly correlated with PCL-M total scores group (F(1,62) ¼ 4.48, p ¼ 0.038), between block, or scores on any of the three PTSD symptom clusters AMBI, and combat history (F(4,248) ¼ 4.62, (all r , 0.250, all p . 0.050). p ¼ 0.001) and between block, combat history, Figure 2A shows eyeblink responding across the PTSS, and group (F(4,248) ¼ 3.44, p ¼ 0.009); no five blocks of acquisition conditioning in the delay other effects or interactions approached significance and omission groups. A repeated measures ANOVA (all p . 0.100). The AMBI £ RMBI interaction was on mean percent CRs over the five acquisition due to much higher responding during extinction in blocks, with factors of group (delay vs. omission), the small number (n ¼ 6) of AMBI-uninhibited and RMBI (inhibited vs. uninhibited), AMBI (inhibited RMBI-inhibited veterans (M ¼ 45.8% CRs, SD 44.3%) vs. uninhibited), PTSS (with vs. without), and compared to the other cells (M range 29.4–30.9% history of exposure to combat (combat vs. non- CRs, SD 25.4–27.5%); this difference did not survive combat), and covariate of UR magnitude, revealed post hoc testing (univariate ANOVA, F(3,83) ¼ 0.62, a significant within-subjects effect of block p ¼ 0.605), probably due to the low sample size in that (F(4,248) ¼ 4.03 p ¼ 0.003), a block £ group inter- action (F(4,248) ¼ 2.84, F ¼ 0.025) and a three-way cell. The group £ RMBI interaction was due to interaction between block, RMBI and PTSS significantly higher responding during extinction (F(4,248) ¼ 3.33, p ¼ 0.011); no other effects or among RMBI-inhibited individuals in the omission interactions were significant (all p . 0.050). Figure 2B group (Figure 3B; independent-samples t-test, % CRs % CRs Behavioral inhibition in veterans 39 Extinction Extinction B 100 A 100 Inhibited Delay (n = 43) Uninhibited Omission (n = 44) * * 38 28 24 33 0 0 123 45 Delay Omission Blocks (of 4 trials) Extinction, block 1 C 100 Inhibited Uninhibited 15 17 52 42 Combat Non-Combat Figure 3. Eyeblink extinction data. (A) Given their higher level of responding during acquisition, the delay group (CS and US overlap and co-terminate) showed significantly faster extinction than the omission group (CR causes omission of US) (repeated-measures ANOVA, F(1,62) ¼ 6.29, p ¼ 0.004). (B) Within the omission group, veterans with uninhibited childhood temperament showed fewer CRs than those with inhibited childhood temperament (independent-samples t-test, t(42) ¼ 2.14, p ¼ 0.039). (C) Among non-combat veterans, those with inhibited current temperament showed more CRs during the first extinction block than those with uninhibited current temperament (independent-samples t-test, t(22) ¼ 2.11, p ¼ 0.047). N is shown at the base of each bar in (B) and (C). Asterisks indicate significant difference ( p , 0.050). t(42) ¼ 2.14, p ¼ 0.039) but not in the delay Discussion group (t(41) ¼ 1.36, p ¼ 0.183). The block £ Given that avoidance reflects a learned association AMBI £ combat history was due to higher respon- between implicit or explicit cues, individual differ- ding during block 1 of extinction AMBI-inhibited ences in vulnerability to anxiety disorders such as non-combat veterans than in AMBI-uninhibited non- PTSD may at least in part reflect differences in combat veterans (Figure 3C; independent-samples t- associative learning. This study was designed to test, t(57.7) ¼ 2.11, p ¼ 0.047); there was no such investigate whether differences in associative learning effect of AMBI in combat veterans (t(22) ¼ 0.024, and extinction might be related to PTSD symptom p . 0.500). To investigate the block £ combat severity, history of combat exposure, or BI. Indeed, history £ PTSS £ group interaction, separate post hoc total conditioned responding during acquisition was tests were conducted on extinction data from the delay correlated with childhood, but not current, BI; and omission groups. In the omission group, veterans extinction was delayed in veterans with PTSS with PTSS gave significantly more CRs during regardless of current or childhood BI, although BI extinction blocks 1 and 2 (Figure 4A; independent- did interact with both combat history and training samples t-tests, all t . 2.00, all p , 0.050) but not group to affect extinction. A secondary objective of the during blocks 3–5 (all t , 1.5, all p . 0.100); the study was to determine whether the AMBI/RMBI interaction with combat did not survive post hoc scale, a self-report measure used to assess current and analysis (all p . 0.050). There was no significant childhood BI, was associated with PTSD symptoms in effect of PTSS, nor any interaction with combat veterans; the results demonstrated that current BI and history, in the delay group (Figure 4A). PTSS were correlated, although PTSS status was best % CRs % CRs % CRs 40 C. E. Myers et al. Delay group Omission group A B 100 100 PTSS (n = 12) PTSS (n = 17) * non-PTSS (n = 32) 80 80 non-PTSS (n = 26) 60 60 40 40 20 20 0 0 A1 A2 A3 A4 A5 E1 E2 E3 E4 E5 A1 A2 A3 A4 A5 E1 E2 E3 E4 E5 Blocks Blocks Figure 4. Eyeblink extinction data. (A) There was no difference in acquisition or extinction as a function of PTSS in the delay group (CS and US overlap and co-terminate) (all p . 0.050). (B) In the omission group (CR causes omission of US), veterans with PTSS showed more eyeblink-CRs than those without PTSS during extinction blocks 1 and 2 (independent-samples t-tests, all t . 2.00, all p , 0.050) but not during blocks 3–5 (all t , 1.5, all p . 0.100). PTSS, severe, current PTSD symptoms. Asterisks indicate significant differences ( p , 0.050). predicted by a combination of current BI and validation paper, nevertheless resulted in only slightly combat exposure measures. We discuss these findings more than half of all veterans in this sample being further below. classed as “inhibited” based on each scale. This indicates that, even though the veteran means are higher than those in the validation sample, the AMBI/RMBI and PTSD symptoms incidence of “uninhibited” vs. “inhibited” tempera- ment (based on either current or childhood behavior) Consistent with other studies that have demonstrated is comparable. increased vulnerability to PTSD in veterans exposed Internal consistency of AMBI/RMBI question- to combat, and in females, we found a higher naires, and correlations between AMBI/RMBI incidence of PTSS in combat veterans, and in females, subscale scores, were similar to those reported by in the current sample. PTSS was also more prevalent Gladstone and Parker (2005); however, that paper in participants who self-reported current BI based on also reported gender differences, with females show- AMBI. Furthermore, within this veteran sample, a ing higher RA than males on both AMBI (4.0 vs. 3.3) model including the individual’s history of exposure to and RMBI (3.1 vs. 2.5). There was no significant combat and the presence/absence of current BI could gender difference in this sample, although the means predict PTSS status with slightly over 80% accuracy. were similar to those observed in the validation To our knowledge, this study is the first documenting study, indicating that the lack of a significant a relationship between self-reported current BI and difference in this sample may have been due to the current PTSD symptom severity. low inclusion of females, although there may also be Although current and retrospective BI were highly unique characteristics of the female veteran popu- correlated in this sample, retrospective BI (based on lation. It is also worth noting that the internal RMBI scores) did not account for additional variance consistency of the RA subscales was relatively low in in PCL-M scores beyond what was already accounted both this sample and in the Gladstone and Parker for by current BI (based on AMBI scores). This is (2005) report, which could contribute to inconsistent broadly consistent with the conclusion of Gladstone findings. and Parker (2005), in their original validation article, A final note on the questionnaire data is that, that AMBI is more useful as a predictor of con- although the majority (94 of 126) veterans were temporaneous clinical outcomes. classed as non-combat based on CES scoring criteria, This study also provides some initial normative data the mean PCL-M score for non-combat veterans was for AMBI/RMBI scores on a veteran sample. Mean still over 30, as given in Table I, and 20 non-combat AMBI (17.0) and RMBI (12.7) in this sample were veterans met the criteria for current, severe PTSD higher than those reported in the original validation symptoms (PCL-M score 50 þ). Clearly, non-combat paper (Gladstone and Parker 2005) for healthy adult veterans can and do report experiencing PTSD controls (AMBI 12.0, SD 4.7; RMBI 8.7, SD 6.1) but lower than those reported for patients with clinical symptoms related to their military service. Given anxiety (AMBI 19.4, SD 6.3; RMBI 15.0, SD 8.7). that even individuals with subthreshold PTSD The cutoff for high inhibition (AMBI 16 þ ,RMBI symptoms are at risk for other medical and psychiatric 12 þ), based on median split of the data in the disorders, including but not limited to subsequent % CRs % CRs Behavioral inhibition in veterans 41 development of full-blown PTSD (Yarvis and Schiess Eyeblink extinction 2008; O’Donnell et al. 2009), this is an important During extinction, participants in the delay population for continued study. group showed fewer CRs (extinguished faster) than the omission group. This is consistent with the partial reinforcement extinction effect (PREE), an increased Eyeblink acquisition resistance to extinction that is observed after training with partial reinforcement, as compared to paradigms Although current BI was most strongly correlated with in which reinforcement is present on every trial during the degree of current PTSD symptoms, childhood BI training (Nation and Woods 1980; Flaherty 1985). was significantly correlated with the acquisition of Among several theories that have been put forward to eyeblink CRs. This was particularly true in veterans explain the PREE is the sequential theory of Capaldi without PTSS; as Figure 2B shows, veterans with (1966); at its simplest, this theory acknowledges that, PTSS tended to learn quickly regardless of BI. The during acquisition under conditions of partial finding that there was no main effect of PTSS in this reinforcement, subjects learn that trials on which the sample may just reflect the relatively small number of CS is not paired with the US are often followed by PTSS veterans. Still, the absence of a main effect of trials in which the CS and US are paired; thus, on any PTSS on learning in this study is broadly consistent given trial, the current CS may be paired with the US, with several prior studies documenting no effects of even if it was not so paired on the previous trial. PTSD on the acquisition of classically conditioned Hence, during the early extinction trials, when the CS CRs (Ayers et al. 2003; Orr et al. 2006; Vythilingam is no longer followed by the US, the subject is already et al. 2006), although these prior studies considered “trained” to continue responding to the CS despite a patients with a clinical diagnosis of PTSD, whereas train of CS-noUS trials. By contrast, for subjects given our study included both combat and non-combat acquisition training under delay contingencies, the veterans with PTSS assessed by self-report. first CS-noUS extinction trial is a novel event, which is The finding that childhood (RMBI), not adult more likely to cause a disruption in responding. (AMBI), temperament was associated with learning Given this interpretation of the PREE, it is speed suggests that faster learning is associated with a interesting that, in this study, although there was no preexisting character trait, rather than having been effect of PTSS on extinction following delay con- acquired later in life through normal aging or via ditioning, veterans with PTSS did show delayed exposure to combat or other stressors, although as extinction in the omission group. Specifically, during mentioned above, we cannot rule out the possibility the early extinction blocks, veterans with PTSS in the that life experiences modify an individual’s self-report omission group showed strong responding to the CS of retrospective measures. There was no increase in (Figure 4B). Similarly, there was extinction resistance UR magnitude as a function of RMBI, indicating that in the omission group among veterans with high increased sensitivity to the US is not a sufficient RMBI (Figure 3B). This suggests that there may be explanation for the relationship between childhood BI individual differences in PREE, such that certain and learning. The relationship between high child- groups, such as those with childhood BI and/or PTSS hood BI and learning is also broadly consistent with may be more resistant to extinction following partial animal models of anxiety vulnerability: specifically, reinforcement. Interestingly, persistent responding to rats bred to show high BI, assessed through open field stimuli that no longer signal important outcomes has behavior and other behavioral and physiological also been proposed as a mechanism contributing characteristics, also show facilitated acquisition of to learned helplessness and depression (Nation and conditioned eyeblink responses (Ricart et al. 2011). Woods 1980), a condition which is highly comorbid There was also faster acquisition of eyeblink CRs with PTSD (Foa et al. 2006) as well as with subclinical in the delay group than in the omission group; this PTSD (Yarvis and Schiess 2008). This raises the is consistent with findings from prior eyeblink con- question of whether some features of PTSD and ditioning studies (Logan 1951; Massaro and Moore depression might reflect the same underlying associ- 1967). In general, training curves obtained under ative learning mechanisms. To examine this issue omission contingencies often replicate those observed further, it would be interesting to assess acquisition under partial reinforcement schedules (Church 1964), and extinction with omission contingencies in patients which is often taken to support the position that with depression as well as with both depression eyeblink conditioning is truly classical rather than and PTSS. operant in nature (Coleman 1975). The presence of Extinction was also reduced for non-combat the main effect of group indicates that high-RMBI individuals do not simply produce more CRs under all veterans with inhibited temperament based on conditions, but that they and low-RMBI individuals AMBI, although this difference was significant only can both modulate their responding as a function of during block 1 of extinction (Figure 3C). It is not clear stimulus contingencies. why this effect should appear in non-combat but not 42 C. E. Myers et al. combat veterans, nor why this interaction involves increasing risk for the development of clinical PTSD, AMBI rather than RMBI. One difficulty with using subclinical PTSD poses its own associated health the AMBI/RMBI scales is that two measurements are costs; veterans with subclinical PTSD but without a provided, representing current and retrospective diagnosis of full-blown PTSD are at increased risk for inhibition, and although these two measures are comorbid diseases such as depression, alcohol abuse, generally correlated (as they were in this study), this poor health, and disability following physical injury correlation is not perfect; in addition, the use of two (Yarvis and Schiess 2008; O’Donnell et al. 2009). related scales may reduce the power of either to For this reason, although many studies of PTSD in demonstrate a significant effect. veterans have considered only combat veterans dichotomized as PTSD or non-PTSD based on clinical diagnosis, it is also important to study both Limitations and future directions combat and non-combat veterans and to consider a There are several limitations to this study, most continuum of PTSD symptom severity, including notably the reliance on participants’ memory for subclinical as well as clinical PTSD cases. retrospective measures (such as RMBI and even Despite these limitations, this study demonstrates CES). There are also limitations related to this that current BI, assessed by self-report using the sample, including the inclusion of only a small number AMBI, correlates with current, severe PTSD symp- of females, which hindered the investigation of gender toms in veterans; however, AMBI scores alone did not differences, and a range of ages and time since combat predict PTSS as well as a model that included both exposure. Since we were relying on self-report, we were AMBI and combat history as predictive variables, unable to fully investigate the effects of medication, as reflecting the fact that the development of PTSD some individuals were unable to specify their precisely symptoms depends on exposure to stressors as well as medication name or dosage. In addition, although we preexisting vulnerability. However, retrospective used CES to assess the history of exposure to combat, (RMBI) rather than current (AMBI) BI was associ- participants may have been exposed to traumatic ated with faster eyeblink conditioning. To the extent events unrelated to military service. An important that RMBI indexes childhood BI that pre-dates issue in understanding PTSD in veterans is not only combat exposure in veterans, this finding is consistent psychopathology which develops directly in response with the idea that a bias for faster associative learning to traumatic events experienced during military may play a role in establishing risk for PTSD, and service (e.g. combat exposure), but also the degree suggests that the facilitated conditioning sometimes to which prior exposure to combat and other service- observed in patients with clinically diagnosed PTSD may be related to preexisting vulnerability for PTSD, related stressors affects veterans’ risk for PTSD if exposed to further traumatic events during sub- rather than emerging selectively as a consequence sequent civilian life. Although we did not find of exposure to trauma or development of PTSD significant effects of combat history on acquisition or symptoms per se. extinction in this study, with the exception of a However, although inhibited temperament is a risk combat-AMBI interaction that was significant for only factor for PTSD, it is neither necessary nor sufficient a single block during extinction, this is likely to be due for PTSD. In this sample, there were individuals to the inclusion of rather few combat veterans in this classified as uninhibited on both AMBI and RMBI sample; studies focusing on combat veterans might who nevertheless score above the cutoff for PTSS, as more clearly address this issue. well as individuals with high AMBI/RMBI scores but Given the low number of combat veterans in this without PTSS. The finding that PTSS alone did not sample, there was a high rate of PTSS, including over significantly affect acquisition in this sample suggests one-fifth of the 94 non-combat veterans. Indeed, non- that BI is strongly linked to associative learning, combat veterans in this sample reported an average of whether or not an individual is subsequently exposed almost one cluster B symptom and more than one to trauma (e.g. combat) and/or develops PTSS. Thus, symptom each from clusters C and D (see Table I). inhibited temperament and faster conditioning may be This indicates that non-combat veterans may experi- preexisting factors that provide one (but certainly not ence severe stressors unrelated to combat at a higher the only) pathway to risk for PTSD. However, this rate than would normally be expected from the general finding of delayed extinction in PTSS veterans population. Indeed, there is some evidence that following acquisition under omission contingencies individuals who exhibit subclinical PTSD symptoms, is consistent with the idea that extinction resistance but fall short of diagnostic criteria, are at heightened may emerge as an acquired sign following exposure risk of future exposure to trauma, possibly because of to trauma and/or development of PTSD symptoms; an increase in behaviors (e.g. substance abuse) that nonetheless, milder but significant extinction resis- magnify risk for trauma and/or a decrease in normal tance also appeared in behaviorally inhibited, psychological processes for recognizing and respond- non-combat veterans in this study, suggesting that, ing to threat (Orcutt et al. 2002). In addition to at least under some conditions, extinction resistance Behavioral inhibition in veterans 43 Fincham D, Smit J, Carey P, Stein DJ, Seedat S. 2008. 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Journal

Stress: The International Journal on the Biology of Stress – Taylor & Francis

Published: Jan 1, 2012

Keywords: Behavioral inhibition; eyeblink; classical conditioning; learning; post-traumatic stress disorder (PTSD); veterans

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