Executive function in posttraumatic stress disorder (PTSD) and the influence of comorbid depression

Neurobiology of Learning and Memory xxx (2014) xxx–xxx

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Executive function in posttraumatic stress disorder (PTSD) and the influence of comorbid depression Miranda Olff a,b,⇑, A. Rosaura Polak a, Anke B. Witteveen a, Damiaan Denys a,c a

Department of Psychiatry, Academic Medical Center (AMC), University of Amsterdam (UvA), Amsterdam, The Netherlands Arq Psychotrauma Expert Group, Nienoord 5, 1112 XE Diemen, The Netherlands c The Netherlands Institute for Neuroscience (NIN), An Institute of the Royal Netherlands Academy of Arts and Sciences, Meibergdreef 47, 1105 BA Amsterdam, The Netherlands b

a r t i c l e

i n f o

Article history: Received 17 July 2013 Revised 4 January 2014 Accepted 6 January 2014 Available online xxxx Keywords: PTSD Neurocognitive Neuropsychology Executive function Comorbid depressive disorder Symptom clusters

a b s t r a c t Background: Posttraumatic stress disorder (PTSD) has been associated with neurocognitive deficits, such as impaired verbal memory and executive functioning. Less is known about executive function and the role of comorbid depression in PTSD. Recently, studies have shown that verbal memory impairments may be associated with comorbid depressive symptoms, but their role in executive function impairments is still unclear. Objective: To examine several domains of executive functioning in PTSD and the potentially mediating role of comorbid depressive symptoms in the relationship between executive function and PTSD. Method: Executive functioning was assessed in 28 PTSD patients and 28 matched trauma-exposed controls. The Cambridge Neuropsychological Test Automated Battery (CANTAB) with subtests measuring response inhibition (SST), flexibility/set shifting (IED), planning/working memory (OTS) and spatial working memory (SWM) was administered in PTSD patients and trauma-exposed controls. Regression analyses were used to assess the predictive factor of PTSD symptoms (CAPS) and depressive symptoms (HADS-D) in relation to executive function when taking into account the type of trauma. Pearson’s correlations were used to examine the association between PTSD symptom clusters (CAPS) and executive function. The mediating effects of depression and PTSD were assessed using regression coefficients and the Sobel’s test for mediation. Results: Our findings indicate that PTSD patients performed significantly worse on executive function than trauma-exposed controls in all domains assessed. PTSD symptoms contributed to executive functioning impairments (SST median correct, IED total errors, OTS latency to correct, SWM total errors and SWM strategy). Adding depressive symptoms to the model attenuated these effects. PTSD symptom clusters ‘numbing’ and to a lesser extent ‘avoidance’ were more frequently associated with worse executive function (i.e., IED total errors, OTS latency to correct and SWM total errors) than ‘reexperiencing’ and ‘hyperarousal’. Depressive symptoms mediated the relation between PTSD and executive function on some executive function measures (IED total errors and OTS latency to correct), whereas PTSD did not mediate the relation between depression and executive function. Conclusions: PTSD patients perform worse on executive function. The impairments seem to be mostly associated with the less specific PTSD symptom cluster of ‘numbing’. Depressive symptoms seem to mediate the relationship between PTSD and executive function. These findings may have clinical implications with regard to treatment indication and prognosis. Ó 2014 Elsevier Inc. All rights reserved.

1. Background Posttraumatic stress disorder (PTSD) has increasingly been associated with impairments in neurocognitive domains such as

⇑ Corresponding author at: Department of Psychiatry, Academic Medical Center (AMC), University of Amsterdam (UvA), Amsterdam, The Netherlands. E-mail addresses: [email protected] (M. Olff), [email protected] (A.R. Polak), [email protected] (A.B. Witteveen), [email protected] (D. Denys).

verbal memory (Johnsen & Asbjornsen, 2008) and executive functioning (Samuelson et al., 2006; Stein, Kennedy, & Twamley, 2002; Polak, Witteveen, Reitsma, & Olff, 2012). The widely adopted model on neurocircuitry of PTSD suggests a hyperactive amygdala and hypoactivation of the medial prefrontal cortex (Patel, Spreng, Shin, & Girard, 2012; Quide, Witteveen, El-Hage, Veltman, & Olff, 2012). A structural finding that was repeatedly found among PTSD patients was hippocampal volume reduction (Hull, 2002). Consistent with the involvement

1074-7427/$ - see front matter Ó 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.nlm.2014.01.003

Please cite this article in press as: Olff, M., et al. Executive function in posttraumatic stress disorder (PTSD) and the influence of comorbid depression. Neurobiology of Learning and Memory (2014), http://dx.doi.org/10.1016/j.nlm.2014.01.003

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M. Olff et al. / Neurobiology of Learning and Memory xxx (2014) xxx–xxx

of frontal areas, several studies have shown impairment in differential domains of executive functioning in PTSD, such as attention and working memory (El-Hage, Quidé, Radua, & Olff, 2013; Gilbertson, Gurvits, Lasko, Orr, & Pitman, 2001; Jenkins, Langlais, Delis, & Cohen, 2000; Meewisse et al., 2005; Samuelson et al., 2006), inhibitory functions (Jenkins et al., 2000; Koso & Hansen, 2006; Leskin & White, 2007) and flexibility and planning (Beckham, Crawford, & Feldman, 1998; Jenkins et al., 2000; Stein et al., 2002). Although impairment in executive functioning was not consistently found over studies (Crowell, Kieffer, Siders, & Vanderploeg, 2002; Twamley, Hami, & Stein, 2004; Zalewski, Thompson, & Gottesman, 1994), a recent review and meta-analysis indicated an overall dysfunction in executive functioning in PTSD when compared to trauma-exposed and healthy controls (Polak, Witteveen, Visser, et al., 2012). PTSD symptoms could directly lead to deficits in executive functioning; reexperiencing, sleeping problems, problems with concentration or hyperarousal may interrupt with working memory performance and inhibitory functions (Vasterling et al., 2002). Another possibility is that subtle impairments may predate PTSD, and that impaired executive function, and especially difficulty inhibiting stimuli, and difficulty disengaging from threatening stimuli may lead to developing PTSD symptoms such as reexperiencing and hyperarousal symptoms after trauma exposure (Aupperle, Melrose, Stein, & Paulus, 2012). The authors imply that difficulty inhibiting may consequently result in other coping strategies such as avoidance in order to be able to decrease reexperiencing and hyperarousal symptoms. Although several studies have focused on executive function impairment in PTSD, there is less knowledge on the exact causal pathway of this relationship. Results of other studies indicate that verbal memory impairments in PTSD are associated with comorbid depressive symptoms (Burris, Ayers, Ginsberg, & Powell, 2008; Johnsen, Kanagaratnam, & Asbjornsen, 2008). Likewise, executive dysfunction in PTSD patients may be associated with comorbid depression. Previously, major depressive disorder without any psychiatric comorbidity showed to be associated with executive function impairments (Austin, Mitchell, & Goodwin, 2001; Elliott et al., 1996; Gohier et al., 2009). These impairments could be explained by several factors, such as reduced motivation, abnormal catastrophic responses to negative feedback and attentional biases, i.e., difficulty with inhibiting interfering irrelevant negative material (Porter, Bourke, & Gallagher, 2007). It is possible that comorbid depression in PTSD may also influence the relation between PTSD and executive function and (partly) mediate the relationship of PTSD and executive function. Recent studies point towards that possibility, i.e., a meta-analysis of (Polak, Witteveen, Visser, et al., 2012) found an effect of depressive symptoms on executive function tests. Furthermore, a study with a sample of veteran participants with PTSD indicated that self-reported anxiety and depressive symptoms mediate the relation of PTSD and working memory impairments (Dretsch et al., 2012). The authors of this study only focused on one domain of executive function, namely working memory, and suggested that comorbid depressive symptoms may mediate the relation between PTSD and executive function though were unable to determine the interrelationship between PTSD and depression in detail. Currently, the exact relation between PTSD, comorbid depression and executive function is still uncertain. This prompted us to look more closely at executive function and the association between PTSD, its symptom clusters (‘reexperiencing’, ‘avoidance’ and ‘numbing’ and ‘hyperarousal’), and executive function and to explore whether comorbid depression mediates the relationship between PTSD and executive function or whether PTSD is a (partial) mediating variable of an actual relationship between depression and executive function.

In the current study the performance in several domains of executive functioning (i.e., response inhibition, flexibility and set shifting, planning and working memory) in PTSD patients is compared with trauma-exposed controls. Also, the role of comorbid depressive symptoms is examined, i.e., the association of PTSD symptom clusters and executive function as well as the mediating role of depression in the relationship between executive function and PTSD. We hypothesize that PTSD patients perform worse on all domains of executive function measures in comparison with controls, as this is in line with previous data (Polak, Witteveen, Visser, et al., 2012; Koso & Hansen, 2006; Samuelson et al., 2006; Stein et al., 2002). Secondly, we expect that depression has a prominent role in executive dysfunction and in relation to that, we expect to find that ‘numbing’ in particular is associated with executive dysfunction, as these symptoms are closely related to depression (i.e., disinterest in activities and numbing). Furthermore, we hypothesize that depressive symptoms partly mediate the relation between PTSD and executive function. 2. Method 2.1. Participants PTSD patients were recruited from the outdoor clinic of the Academic Medical Center (AMC) in Amsterdam, the Netherlands and were enrolled in a currently ongoing randomized controlled trial (Polak, Witteveen, Visser, et al., 2012). The initial PTSD sample comprised of 47 patients. Inclusion criteria for PTSD patients were: age between 18 and 65 years and primary diagnosis of PTSD according to the DSM-IV criteria. Severe comorbid depressive disorder was an exclusion criterion as well as comorbid schizophrenia, bipolar disorder or depression with psychotic features or substance dependence or abuse. Nineteen patients were excluded based on the following criteria: presence of comorbid axis II disorders (n = 4), presence of excessive substance or alcohol use over the past two months (n = 1), current use of psychotropic medication (n = 7), a neurological disorder (n = 1), previous loss of consciousness of more than 30 min (n = 1), a serious medical condition (n = 1), not meeting all PTSD symptoms according to the DSM-IV criteria at time of the measurement (n = 3), and no informed consent present (n = 1). After these exclusions, 28 PTSD patients remained for the analysis. Of the included patients, 13 patients had a comorbid depressive disorder and 15 patients did not have a depressive disorder, according to the DSM-IV criteria. Furthermore, two patients were diagnosed with a comorbid pain disorder and one patient with a comorbid specific phobia. Psychopathology was assessed with the M.I.N.I.-Plus. Trauma-exposed controls were matched with the PTSD group according to gender, age and years of education. The initial sample comprised of 43 controls. Controls with any current psychiatric disorder as measured with the M.I.N.I.-Plus were excluded, including anxiety disorders, depressive disorder, schizophrenia, bipolar disorder and substance dependence or abuse. Fifteen controls were excluded based on the following criteria: substance (alcohol or drugs) dependence or abuse (n = 6) or current psychotropic medication (n = 1). Controls with a history of a diagnosis of PTSD (n = 3) were also excluded. Some trauma-exposed controls were excluded due to neurological disorders (n = 1) or loss of consciousness of more than 30 min (n = 4). The final sample after exclusions consisted of 28 trauma-exposed controls. 2.2. Procedures Patients were seen at the outpatient clinic by psychiatrists and psychologists in order to assess axis I and axis II DSM-IV diagnoses which was confirmed using the M.I.N.I.-Plus (Sheehan et al., 1998).

Please cite this article in press as: Olff, M., et al. Executive function in posttraumatic stress disorder (PTSD) and the influence of comorbid depression. Neurobiology of Learning and Memory (2014), http://dx.doi.org/10.1016/j.nlm.2014.01.003

M. Olff et al. / Neurobiology of Learning and Memory xxx (2014) xxx–xxx

Patients were asked to participate, when all inclusion criteria were met and an appointment for a research measurement was made. After informed consent was given, clinical measurements and neuropsychological tests were administered by the researcher and research assistants that were well trained by the second author. All participants have given written informed consent. The research protocol of the treatment study was approved by the ethical committee of the AMC, Amsterdam. 2.2.1. Clinical measures M.I.N.I. International Neuropsychiatric Interview-Plus was used to assess psychopathology (Sheehan et al., 1998). The M.I.N.I.-Plus is a widely used structured clinical interview that can diagnose past and present DSM-IV psychiatric disorders, such as mood disorders (i.e., major depressive or dysthymic disorder), anxiety disorder (i.e., panic disorder or obsessive-compulsive disorder) or substance related disorders. Every module consists of screening questions which, if responded positively, leads to additional examination for diagnosing the specific disorder. Clinician-Administered PTSD Scale (CAPS) was used for diagnosing PTSD according to DSM-IV and assessing PTSDsymptom severity (Blake et al., 1995) and is one of the most widely used structured clinical interviews (Weathers, Keane, & Davidson, 2001). The CAPS distinguishes between the estimated frequency (range: 0–4) and intensity (range: 0–4) of the various symptoms. Frequency and intensity scores are added up to a total CAPS score (range: 0–136). Hospital Anxiety and Depression Scale (HADS) was used to assess the level of depression and anxiety symptoms (Zigmond & Snaith, 1983). It is a well-established 14-item scale containing two subscales: HADS-A (Anxiety, 7 items, range: 0–21) and HADS-D (Depression, 7 items; range: 0–21). Alcohol Use Disorders Identification Test (AUDIT) was developed by the World Health Organization (WHO) in 1982 and was used to assess excessive drinking patterns. The screening consists of 10 questions concerning recent alcohol use, alcohol dependence symptoms and alcohol-related problems (Saunders, Aasland, Babor, de la Fuente, & Grant, 1993). Scores range from 0 to 4. A score of 8 or more is associated with harmful or hazardous drinking; a score of 13 (for women) or 15 (for men) could indicate alcohol dependence. 2.2.2. Neuropsychological measures Neuropsychological functioning was measured using The Cambridge Automated Neuropsychological Test Battery (CANTAB), a well-established computerized neuropsychological touch-screen test battery that examines a range of domains, such as executive function, working memory and planning. The test is culture- and language-independent, because the battery mainly uses nonverbal stimuli. The CANTAB tests have good test–retest reliability and parallel forms (Lowe & Rabbitt, 1998) and are graded in difficulty to avoid ceiling and floor effects. All participants received the test in the same order. The test battery consisted of the following tests (in order): 2.2.2.1. Response inhibition. Stop Signal Task (SST) was used to measure the ability to inhibit a prepotent response. The test is a classic stop signal response inhibition test and uses staircase functions to generate an estimate of stop signal reaction time. Participants were instructed to press a press-pad as quickly and accurate as possible when an image of an arrow was shown, but to avoid anticipating when a beep sound was presented. The test consisted of 5 blocks of 64 trials, with 16 stop trials per block. Outcome measures were the proportion of successful stops for the last half, the (median) reaction time (milliseconds) on GO trials and the Stop Signal Reaction Time (SSRT), an estimate of the length of time between

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the go stimulus and stop stimulus at which the particpant can successfully inhibit the response on 50% of the trials. 2.2.2.2. Flexibility/set shifting. The Intra/Extra Dimensional Set Shift (IED) task was used to asses rule acquisition and reversal. It features visual discrimination and attentional set formation maintenance, shifting and flexibility of attention. The test is sensitive to changes to the fronto-striatal areas of the brain (Robbins et al., 1998) and is a computerized analogue of the Wisconsin Card Sorting Test (WCST). Participants were required to attend a reinforced stimulus (shapes; intra-dimensional shift or IDS), and subsequently shift to a previously irrelevant stimulus (lines; extra-dimensional shift, EDS). The test consists of a set of criteria of learning (nine stages in total). The number of errors made prior to the extra-dimensional shift (Pre-ED errors), the number of errors in the extra-dimensional stage (EDS errors) and the total number of errors (adjusted for the number of stages completed) were recorded. 2.2.2.3. Planning/working memory. One Touch Stockings of Cambridge (OTS) is a spatial planning task. Participants were asked to solve 24 problems by indicating the number of moves necessary to mimic a display (colored balls on stockings) to a template display. This task is a computerized analogue of the Tower of London (TOL) task, but with a greater demand on working memory as participants are requested to visualize the solution rather than moving the balls themselves. Outcome measures were mean choices to correct (for problems of 4 moves), mean latency to correct moves (for problems of 4 moves) and mean latency to first choice (for problems of 4 moves). 2.2.2.4. Working memory Spatial Working Memory (SWM) is a test to assess the ability to retain spatial information and to manipulate remembered items in working memory by finding tokens hidden in displayed boxes. The test is a self-ordered task, which also assesses heuristic strategy. The outcome measures were total errors, summarized for 8 move problems, that is the number of times a box is selected that is certain not to contain a blue token (i.e., ‘between error’ revisiting a box in which a token was presented or a ‘within error’ revisiting a box already found empty during the same search) and the strategy being used. 2.3. Statistical analysis Chi-squared tests for categorical variables were used to compare demographic and clinical characteristics between the two groups. Independent t-tests for continuous variables were used for normally distributed characteristics. When not normally distributed, a Mann–Whitney test was used. All neuropsychological measures were tested for normality and a log transformation was applied when necessary. Analyses of variance (ANOVA) were used for continuous measures. Statistical tests for ANOVA were one-tailed and p values of <.05 were considered statistically significant. Multiple regression analyses were performed in the entire sample of PTSD patients and trauma-exposed controls together, with several parameters of executive function as outcome measures and PTSD (CAPS) and depressive (HADS-D) as predictors. The regression models were controlled for type of trauma, as the groups differed on this factor. Dummy variables of trauma types were entered in the first block of the regression models, while the second and third block consisted of the variable PTSD (CAPS) and depression (HADS-D), respectively. Including the factors in this order allowed us to determine the influence of depressive symptoms (HADS-D) on the predictive value of PTSD symptoms (CAPS). Associations of executive function and PTSD symptom clusters

Please cite this article in press as: Olff, M., et al. Executive function in posttraumatic stress disorder (PTSD) and the influence of comorbid depression. Neurobiology of Learning and Memory (2014), http://dx.doi.org/10.1016/j.nlm.2014.01.003

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M. Olff et al. / Neurobiology of Learning and Memory xxx (2014) xxx–xxx

(‘reexperiencing’, ‘avoidance’, ‘numbing’ and ‘hyperarousal’) were examined using the Pearson’s correlation coefficient with p values of <.01. We chose to split ’avoidance’ and ’numbing’ as this is concurrent with the factors found in previous studies (Olff, Sijbrandij, Opmeer, Carlier, & Gersons, 2009; Rademaker et al., 2012) and the DSM-5 (APA, 2013). Furthermore, by splitting the symptom clusters in this way, the overlap of PTSD and depression are primarily related to the ‘numbing’ cluster and less to the other clusters. To determine the extent to which depression mediated the relationship between PTSD symptoms and executive function, Sobel’s tests (Hayes, 2009) were performed. First, we performed a regression analysis with PTSD symptoms (CAPS) as the independent variable (IV) and depressive symptoms (HADS-D) as the dependent variable (DV) and regression analyses with the HADS-D as the independent variable (IV) and the executive outcome measures as the dependent variable (DV) controlling for CAPS symptoms. Second, the potential mediating effect could be examined by the Sobel’s test. Likewise, we also conducted regression analyses and Sobel’s tests to determine the extent to which PTSD mediated the relationship between depressive symptoms and executive function. Statistical tests for regression were considered statistically significant with p values of <.05, unless mentioned otherwise. All statistical analyses were conducted with the Statistical Package for the Social Sciences (SPSS) version 20. 3. Results

the other hand, PTSD patients had a higher proportion of successful stops (SST) than trauma-exposed controls (t(54) = 2.22, p < .05). Though performing better on response inhibition (SST), measures on median RT on go trials (t(38.4) = 3.20, p < .05) and SSRT(t(54) = 1.73, p < .05) indicated that PTSD patients had slower reaction times than controls.

3.3. PTSD symptoms, depressive symptoms and executive function In order to evaluate the association between PTSD symptomatology and executive function in the entire sample of PTSD patients and trauma-exposed controls, we conducted a regression analysis with three blocks, and included type of trauma (model 1), CAPS (model 2) and HADS-D (model 3). Although gender, age and years of education may influence neuropsychological functioning (Clark et al., 2006; De Luca, Cinzia, Leventer, & Richard, 2008; Sarosi et al., 2008), these variables were, however, not associated with executive function in the current sample and groups did not differ on these factors. Therefore, we chose not to control for these demographic variables. Table 3 shows the results of the regression analyses with the main executive function outcome measures (SST median correct, IED total errors; OTS latency to correct; SWM total errors (8 boxes) and SWM strategy). CAPS showed significantly predictive for all executive function measures, but the relation was not significant anymore when adding depressive symptoms to the model.

3.1. Demographics The demographic and clinical characteristics are presented in Table 1. Groups did not differ on age, gender, years of education or alcohol use. Trauma type differed significantly between PTSD and trauma-exposed controls (p of the Fisher exact <.05), i.e., 21.4% and 50.0% motor vehicle accidents in PTSD and trauma-exposed respectively, and 50.0% and 10.7% (sexual) assault in PTSD and trauma-exposed respectively. As expected, PTSD patients had more PTSD symptoms, indicated by higher scores on the CAPS (U = 0.00; z = 6.43; p < .05). Group differences on depressive symptoms (HADS-D) were also present (U = 45.50; z = 5.70; p < .05). As mentioned earlier, 13 patients were previously diagnosed with a comorbid depressive disorder according to the DSM-IV, whereas 15 patients were not. No controls were diagnosed with a depressive disorder. As expected, high HADS scores showed to be indicative for comorbid depression and low HADS scores for the absence of comorbid depressive disorder and HADS scores differed significantly between depressive and non-depressive participants (U = 18.5; z = 5.08; p < .05).

3.4. The relation between executive function and PTSD symptom clusters In order to evaluate which specific PTSD symptoms were associated with executive function impairment, we evaluated the PTSD symptom clusters separately. The clusters were split in accordance with a previous study (Olff et al., 2009), i.e., ‘reexperiencing’, ‘numbing’, ‘avoidance’ and ‘hyperarousal’. Table 4 shows the results of the Pearson’s correlations. The findings indicate that mainly ‘numbing’ (i.e., IED total errors, r = .36, p = .007; OTS mean latency to correct, r = .43, p = .001; SWM total errors, r = .43, p = .001) and to a lesser extent ‘avoidance’ (IED total errors, r = .40, p = .002; SWM total errors, r = .36, p = .008) were related to worse executive function. Symptom clusters ‘reexperiencing’ (SWM total errors, r = .36, p = .008) and ‘hyperarousal’ were less often associated with impaired executive functioning. When controlling for depressive symptoms (HADS-D), no associations were found.

3.2. Neuropsychological measurements The neuropsychological performance is presented in Table 2. PTSD patients scored significantly worse in comparison with the control group on measures of flexibility and set shifting, measured with the IED. PTSD patients made more mistakes than the traumaexposed control group in the phase prior to the extra-dimensional shift (t(33.6) = 1.83, p < .05) and in the test as a whole (t(33.1) = 3.85, p < .05), but not in the extra-dimensional stage (t(40.3) = 1.62, p = .06). Also on working memory and planning (OTS), PTSD patients performed worse in comparison with trauma-exposed controls with more choices made (t(43.4) = 2.39, p < .05) and longer latency to correct choice (t(52) = 3.40, p < .05). On another test measuring working memory (SWM) more mistakes were made (t(52) = 3.14, p < .05) and a less efficient strategy (t(46.1) = 3.03, p < .05) was used in the PTSD group. On

3.5. Depressive symptoms as a mediator in the relation between PTSD and executive function In order to examine whether depressive symptoms mediated the relationship between PTSD and executive function, we conducted regression analyses and a Sobel’s test. The results are depicted in Table 5a. The findings indicate that depressive symptoms mediated the relation between PTSD and executive function in some measures of executive function, namely IED total errors (Z = 2.06, p < .05) and OTS latency to correct (Z = 2.08, p < .05). We also investigated the possibility of PTSD symptoms mediating the relation between depression and executive function. Table 5b shows the results of the regression analyses and Sobel’s test. The findings indicate that PTSD symptoms did not mediate the relation between depression and executive function.

Please cite this article in press as: Olff, M., et al. Executive function in posttraumatic stress disorder (PTSD) and the influence of comorbid depression. Neurobiology of Learning and Memory (2014), http://dx.doi.org/10.1016/j.nlm.2014.01.003

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M. Olff et al. / Neurobiology of Learning and Memory xxx (2014) xxx–xxx Table 1 Demographic and clinical characteristics of PTSD patients and trauma-exposed controls. TCa

PTSD N

Mean (SD)

Min–max

N

Mean (SD)

Min–max

Age, years

28

38.93 (12.25)

19–62

28

39.29 (11.48)

23–61

Female (n,%)

28

12 (42.9)

28

12 (42.9)

Years of education

28

16.75 (1.94)

28

17.00 (1.74)

Trauma (n,%) MVAb War related Assault Sexual assault Otherc Time since trauma

28

28

Test statistic1

P

U = 381.50 Z = .17 v2 = .00 df = 1 U = 367.00 Z = .46

.87

CAPSd CAPS – B CAPS – C CAPS – D HADS-De

28

28

79.82 24.86 29.07 25.89 13.57

AUDITf

28

3.07 (2.49)

(22.73) (8.15) (11.70) (6.74) (5.47)

.66 .004*

28 6 (21.4) 1 (3.6) 7 (25.0) 7 (25.0) 7 (25.0) 139.21 (164.75)

1.00

14 (50.0) 0 (0) 3 (10.7) 0 (0) 11 (39.3) 72.50 (60.57)

263 38–116

28

1–20

28

7.07 0.82 2.00 4.25 2.64

(6.77) (1.56) (3.86) (4.56) (2.42)

0–10

28

3.96 (2.35)

U = 361.50 Z = .043 U = 0.00 Z = 6.43

0–24

0–9

U = 45.50 Z = 5.70 U = 311.50 Z = 1.34

0–11

2

.97 <.001*

<.001* .19

a

TC: trauma-exposed controls. Motor vehicle accident. c Other: disaster, trauma exposure during profession (i.e., police; ambulance), accident. d CAPS: Clinician-Administered PTSD Scale. e HADS-D: Hospital Anxiety and Depression Scale. f AUDIT: Alcohol Use Disorders Identification Test. 1 Mann–Whitney test was used for continuous variables. Chi-square tests were used for categorical variables. 2 Fisher’s Exact test. 3 Of two patients, time since trauma was unknown. Indicates significance of p < .05. b

*

Table 2 Executive function in PTSD patients and trauma-exposed controls. PTSD

TC

Test statistica

P

N

Mean (SD)

N

Mean (SD)

SST Proportion of successful stops (last half) Median correct RT on go trials SSRT (last half)

28 28 28

0.6 (0.1) 710.8 (439.8) 281.2 (235.3)

28 28 28

0.5 (0.1) 466.2 (115.2) 204.5 (46.9)

t= t= t=

2.22, df = 54 3.20, df = 38.4 1.73, df = 54

.016* .002** .045*

IED Pre-EDS errors EDS errors Total errors

28 28 28

10.7 (8.6) 10.4 (11.9) 35.3 (35.3)

28 28 28

7.5 (3.0) 4.0 (3.5) 12.8 (4.5)

t= t= t=

1.83, df = 33.6 1.62, df = 40.3 3.85, df = 33.1

.038* .057 <.001**

OTS Choices to correct (4 moves) Latency to correct (4 moves) Latency to first choice (4 moves)

27 27 27

1.7 (0.6) 25599.9 (15104.8) 15549.5 (8829.3)

27 27 27

1.3 (0.4) 15050.4 (8211.6) 12601.1 (5813.3)

t= t= t=

2.39, df = 43.4 3.40, df = 52 1.66, df = 52

.011* <.001** .052

SWM Total errors (8 boxes) Strategy

26 26

24.0 (13.3) 34.5 (3.8)

28 28

13.9 (10.2) 30.4 (6.1)

t= t=

3.14, df = 52 3.03, df = 46.1

.002** .002**

a * **

t-Tests for two independent samples were performed. When not normally distributed, log transformations were performed. Indicates significance of p < .05. Indicates significance of p < .01 (one-tailed).

4. Discussion Our aim was to examine the performance in several domains of executive functioning (i.e., response inhibition, flexibility and set shifting, planning and working memory) in PTSD patients compared to trauma-exposed controls and to examine the potentially mediating role of comorbid depressive symptoms in the relationship between executive function and PTSD.

The main results of this study indicate that PTSD patients have poorer executive function than trauma-exposed controls. This was the case for various domains, i.e., flexibility and set shifting, planning and working memory. Although PTSD patients unexpectedly had higher successful proportion rates on response inhibition, reaction times were slower. This overall impairment on executive function is in line with previous findings on impaired executive function in PTSD (Polak, Witteveen, Visser, et al., 2012; Samuelson

Please cite this article in press as: Olff, M., et al. Executive function in posttraumatic stress disorder (PTSD) and the influence of comorbid depression. Neurobiology of Learning and Memory (2014), http://dx.doi.org/10.1016/j.nlm.2014.01.003

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M. Olff et al. / Neurobiology of Learning and Memory xxx (2014) xxx–xxx

Table 3 Regression analyses on PTSD patients and trauma-exposed controls with model 2 (CAPS) and model 3 (HADS-D). Predictor variable

Model 2 B

Model 3 SE B

B

SE B

2.603 .001 .003

.036 .001 .007

1.075 .001 .025

.071 .003 .014

OTS Latency to correct (4 moves) (n = 54) Constant 4.111 .058 CAPS .003 .001 .465** HADS-D

4.100 .000 .015

.058 .002 .011

.059 .417

SWM Total errors (8 boxes) (n = 54) Constant 10.516 2.921 CAPS .118 .043 HADS-D

.365**

10.504 .115 .017

2.980 .107 .585

.356 .009

.310*

29.112 .055 .070

1.345 .048 .264

.395 .088

SST Median correct (n = 56) Constant 2.605 CAPS .002 HADS-D

.036 .001

IED Total errors (n = 56) Constant 1.091 CAPS .003 HADS-D

.072 .001

SWM Strategy (n = 54) Constant 29.062 CAPS .043 HADS-D

1.319 .019

b

**

.363

**

.448

b

.260 .104

.106 .564

Model 2 and Model 3 were adjusted type of trauma (other, assault, sexual assault and war related), Model 1. Trauma types were compared with MVA using dummy variables. Note: SST (median correct): R2 = .33 for model 1, p < .001; change R2 = .11 for model 2 (p = .003); change R2 = .002 for model 3 (p = .71) IED (total errors): R2 = .09 for model 1; p = .30; change R2 = .16 for model 2 (p = .002); change R2 = .05 for model 3 (p = .07) OTS (latency to correct): R2 = .09 for model 1; p = .32; change R2 = .18 for model 2 (p = .001); change R2 = .03 for model 3 (p = .18) SWM (total errors): R2 = .18 for model 1; p = .04; change R2 = .11 for model 2 (p = .008); change R2 = .00 for model 3 (p = .98) SWM (strategy) R2 = .14 for model 1; p = .12; change R2 = .08 for model 2 (p = .03); change R2 = .001 or model 3 (p = .79) * p < .05. ** p < .01. *** p < .001.

et al., 2006; Stein et al., 2002). The finding that not only working memory, but also other domains of executive function are impacted in PTSD patients in comparison with controls is in line with previous studies on depressive patients. Studies on major depressive disorder alone indicate, that besides working memory (Gohier et al., 2009), also other impairments on executive function, i.e., slower reaction times in response inhibition (Gohier et al., 2009), planning (Elliott et al., 1996) and set shifting (Austin et al., 2001; Purcell, Maruff, Kyrios, & Pantelis, 1997) are present. The findings of our study suggest, that comorbid depression may play an important role in worse impaired neurocognitive functioning in PTSD. First, PTSD symptoms were related to poorer executive functioning, but when taking into account depressive symptoms, the relation disappeared. Furthermore, mainly the cluster ‘numbing’ was associated with worse executive function.

Table 5a Regression analyses and Sobel’s tests on mediator depressive symptoms.

HADS-D (DV) CAPS (IV)

B

SE B

b

.154

.010

.895***

Test statistica

SE B

SST Median correct (n = 56) (DV) HADS-D (IV) .011 .007

.446

1.56

.001

IED Total errors (n = 56) HADS-D (IV) .025

.552*

2.06

.002*

OTS Latency to correct (4 moves) (n = 54) (DV) HADS-D (IV) .021 .010 .575*

2.08

.002**

SWM Total errors (8 boxes) (n = 54) (DV) HADS-D (IV) .257 .537 .137

.48

.08

SWM Strategy (n = 54) (DV) HADS-D (IV) .040 .239

.17

.04

.012

.050

Regression analysis with independent variable (IV) (CAPS) predicting mediator (HADS-D) and regression analyses with the independent variable (IV) (CAPS) and mediator (HADS-D) predicting the dependent variable (DV) (executive function measure). * p < .05. ⁄⁄ p < .01. *** p < .001. a Test statistic for Sobel’s test.

Interestingly, especially this PTSD symptom cluster shows some overlap with depressive symptomatology, such as numbing and emotional disinterest, irritability, problems with sleep and concentration. The fact that ‘reexperiencing’ symptoms, the core symptoms of PTSD and important diagnostic criteria of PTSD, but not of depressive symptomatology, are much less related to worse executive function is consistent with this suggestion. The fact that mediation analyses showed depression to mediate the relation between PTSD symptoms and executive function, whereas PTSD symptoms did not show to mediate the relationship between depression and executive function is also consistent with the suggestion that depression may play an important role in the neurocognitive impairments in PTSD. As there has been increasing evidence that indeed part of the PTSD symptoms reflect depressive type of symptoms and several factor analyses have shown that in particular the avoidance cluster should be split up (e.g. Olff et al., 2009; Rademaker et al., 2012), within the DSM-5 (APA, 2013), the avoidance cluster has been split into active avoidance and a cluster with items on negative cognitions and mood. With more explicit attention for depressive symptoms in PTSD patients future research will be able to better address the relative contribution of depression related symptoms to neurocognitive functioning. Impaired executive functioning is known to affect daily functioning, e.g., occupational functioning (Kalechstein, Newton, & van Gorp, 2003). As executive functioning is essential for processing complex information, it is very likely that executive function is also crucial for participating in cognitive behavioral therapy (see also Quide et al., 2012) and in relation to that, it is possible that impaired executive functioning may influence treatment outcome.

Table 4 Correlations (Pearson’s r) between symptom clusters and executive function outcome measures.

SST Median correct (n = 56) IED Total errors (n = 56) OTS Latency to correct (4 moves) (n = 54) SWM Total errors (8 boxes) (n = 54) SWM Strategy (n = 54) ** ***

CAPS reexperiencing

CAPS avoidance

CAPS numbing

CAPS hyperarousal

.282 .274 .340 .356** .316

.305 .396** .272 .355** .332

.333 .358** .434** .428** .309

.221 .250 .346 .301 .227

p < .01. p < .001.

Please cite this article in press as: Olff, M., et al. Executive function in posttraumatic stress disorder (PTSD) and the influence of comorbid depression. Neurobiology of Learning and Memory (2014), http://dx.doi.org/10.1016/j.nlm.2014.01.003

M. Olff et al. / Neurobiology of Learning and Memory xxx (2014) xxx–xxx Table 5b Regression analyses and Sobel’s tests on mediator PTSD symptoms.

CAPS (DV) HADS-D (IV)

B

SE B

b

5.210

.353

.895***

Test statistica

SE B

SST Median correct (n = 56) (DV) CAPS (IV) .000 .001

.068

0

.005

IED Total errors (n = 56) CAPS (IV) .000

.055

0

.01

OTS Latency to correct (4 moves) (n = 54) (DV) CAPS (IV) .001 .002 .103

.002

.50

.01

SWM Total errors (8 boxes) (n = 54) (DV) CAPS (IV) .091 .093 .282

.98

.49

SWM Strategy (n = 54) (DV) HADS-D (IV) .039

.95

.21

.041

.279

Regression analysis with independent variable (IV) (HADS-D) predicting mediator (CAPS) and regression analyses with the independent variable (IV) (HADS-D) and mediator (CAPS) predicting the dependent variable (DV) (executive function measure). ⁄ p < .05,  p < .01. *** p < .001. a Test statistic for Sobel’s test.

This possibility is underscored by several recent studies on verbal memory (Nijdam, de Vries, Gersons, & Olff, 2012; Wild & Gur, 2008). Furthermore, Wild and Gur (2008) and Nijdam et al. (2012) showed that attentional measures may predict treatment outcome. Although studies on executive function impairment in PTSD affecting treatment response and the relation with depressive symptoms is scarce, these impairments may have implications for clinical practice of PTSD patients with comorbid depression. Firstly, this could imply that some patients should be given preference to other treatment options than CBT (e.g., medication). Secondly, it may be a possibility to firstly train patients in attaining cognitive control before exposure and consecutively enhance treatment effects. Recent research indicates that attentional modification programs may be beneficial in the treatment of anxiety disorders (Amir et al., 2009; Amir, Beard, Burns, & Bomyea, 2009). They found that attention modification, in which individuals were trained to respond faster to probes away from negative stimuli, may improve working memory and attention and showed to be effective in reducing symptoms of social anxiety, generalized anxiety and obsessive–compulsive disorder. There are some limitations to our study that need to be addressed. Firstly, as this study consists of cross-sectional data, it is rather difficult to identify the direction of the associations between executive function, PTSD and depression and we cannot draw conclusions on causality and be conclusive on the possibility that executive function impairments already predated PTSD as previously suggested (Aupperle et al., 2012). Also, due to the small sample size we were not able to analyze differences in depression severity by comparing PTSD patients with comorbid depression and without comorbid depression/mild depression. Secondly, based on our regression analyses, explained variance for the models is low, and therefore we have to keep in mind that also other factors that we did not take into account, may predict executive function measures. Thirdly, we have to note that, although clinician-rated structured interviews were used for excluding severe depression, our analyses were based on a self-reported depressive questionnaire (i.e., HADS-D scores) rather than on a clinician-rated structured interview. We however do not expect that this may have had implications for our results, as the HADS scores were indicative for the presence of depression in this sample. This is in line with previous findings suggesting a strong correlation

7

between these outcome measures (Domken, Scott, & Kelly, 1994). Despite the abovementioned drawbacks, the pattern of our data shows a clear role of depressive symptoms in the relationship between PTSD symptoms and several executive function measures in PTSD patients and trauma-exposed controls. Future research on prospective data should, however, further elucidate the role of mediating factors such as depression or other factors (i.e., trauma type or drinking habits) in the relationship between executive function and PTSD. In conclusion, we have shown that PTSD patients perform worse on several domains of executive function, i.e., set shifting, planning, working memory and have slower reaction times on response inhibition. Our findings clearly indicate that mainly depression like symptoms account for the executive function impairments in PTSD, as the predictive value of PTSD was attenuated by (partly) overlapping depressive symptoms. Furthermore, particularly ‘numbing’ symptoms and not ‘reexperiencing’ symptoms or ‘hyperarousal’ symptoms were associated with significantly influenced executive function. Lastly, depressive symptomatology showed to mediate the relation between some executive function measures, whereas this was not the case for PTSD symptoms. The results of this study have given further clarity on executive function impairments in PTSD and have elucidated the mediating role of factors such as depressive symptoms in the relationship between impairments in executive function and PTSD. As executive functioning may be important for treatment success these findings are of significant relevance for clinical practice and hopefully stimulate research into improvement of evidence based treatment options for PTSD patients with comorbid depression. Acknowledgments None. References Amir, N., Beard, C., Burns, M., & Bomyea, J. (2009). Attention modification program in individuals with generalized anxiety disorder. Journal of Abnormal Psychology, 118, 28–33. Amir, N., Beard, C., Taylor, C. T., Klumpp, H., Elias, J., Burns, M., et al. (2009). Attention training in individuals with generalized social phobia: A randomized controlled trial. Journal of Consulting and Clinical Psychology, 77, 961–973. Aupperle, R. L., Melrose, A. J., Stein, M. B., & Paulus, M. P. (2012). Executive function and PTSD: Disengaging from trauma. Neuropharmacology, 62, 686–694. Austin, M. P., Mitchell, P., & Goodwin, G. M. (2001). Cognitive deficits in depression: Possible implications for functional neuropathology. British Journal of Psychiatry, 178, 200–206. Beckham, J. C., Crawford, A. L., & Feldman, M. E. (1998). Trail making test performance in Vietnam combat veterans with and without posttraumatic stress disorder. Journal of Traumatic Stress, 11, 811–819. Blake, D. D., Weathers, F. W., Nagy, L. M., Kaloupek, D. G., Gusman, F. D., Charney, D. S., et al. (1995). The development of a clinician-administered PTSD scale. Journal of Traumatic Stress, 8, 75–90. Burris, L., Ayers, E., Ginsberg, J., & Powell, D. A. (2008). Learning and memory impairment in PTSD: Relationship to depression. Depression and Anxiety, 25. Clark, C. R., Paul, R. H., Williams, L. M., Arns, M., Fallahpour, K., Handmer, C., et al. (2006). Standardized assessment of cognitive functioning during development and aging using an automated touchscreen battery. Archives of Clinical Neuropsychology, 21, 449–467. Crowell, T. A., Kieffer, K. M., Siders, C. A., & Vanderploeg, R. D. (2002). Neuropsychological findings in combat-related posttraumatic stress disorder. The Clinical Neuropsychologist, 16, 310–321. De Luca, C. R., Cinzia, R., Leventer, R., & Richard, J. (2008). Developmental trajectories of executive functions across the lifespan. In Taylor & Francis (Eds.), Executive functions and the frontal lobes: A lifespan perspective (pp. 3–21). Washington, DC. Domken, M., Scott, J., & Kelly, P. (1994). What factors predict discrepancies between self and observer ratings of depression? Journal of Affective Disorders, 31, 253–259. Dretsch, M. N., Thiel, K. J., Athy, J. R., Irvin, C. R., Sirmon-Fjordbak, B., & Salvatore, A. (2012). Mood symptoms contribute to working memory decrement in activeduty soldiers being treated for posttraumatic stress disorder. Brain and Behavior, 2, 357–364. El-Hage, W., Quidé, Y., Radua, J., & Olff, M. (2013). Neural correlates of memory dysfunctions in PTSD: Preliminary findings of a systematic review and a mixed

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Please cite this article in press as: Olff, M., et al. Executive function in posttraumatic stress disorder (PTSD) and the influence of comorbid depression. Neurobiology of Learning and Memory (2014), http://dx.doi.org/10.1016/j.nlm.2014.01.003