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. Author manuscript; available in PMC: 2022 Oct 1.
Published in final edited form as: Drug Alcohol Depend. 2021 Jul 28;227:108929. doi: 10.1016/j.drugalcdep.2021.108929

Posttraumatic Stress Symptom Clusters Differentially Predict Late Positive Potential to Cocaine Imagery Cues in Trauma-Exposed Adults with Cocaine Use Disorder

Heather E Webber 1, Danielle A Kessler 2, Emma C Lathan 1, Margaret C Wardle 3, Charles E Green 4, Joy M Schmitz 1, Scott D Lane 1, Anka A Vujanovic 5
PMCID: PMC8464512  NIHMSID: NIHMS1731226  PMID: 34340161

Abstract

Background.

While studies have investigated the effects of posttraumatic stress disorder (PTSD) symptoms on substance use, information on these associations in the context of drug cue reactivity is lacking, which can provide meaningful information about risk for relapse. The current study assessed the associations between PTSD symptom clusters and reactivity to cues in trauma-exposed adults with cocaine use disorder.

Methods.

We recorded electroencephalogram on 52 trauma-exposed participants (Mage = 51.3; SD = 7.0; 15.4% women) diagnosed with cocaine use disorder while they viewed pleasant (i.e., erotic, romantic, sweet foods), unpleasant (i.e., mutilations, violence, accidents), neutral, and cocaine-related images. Reactivity was measured with the late positive potential (LPP), an indicator of motivational relevance. It was hypothesized that individuals with greater PTSD avoidance and negative alterations in cognition and mood (NACM) symptoms, as determined by the PTSD Checklist for DSM-5 (PCL-5), would have higher LPPs to cocaine-related images, indicating greater cue reactivity.

Results.

Linear mixed modeling indicated that higher NACM symptomatology was associated with higher LPPs to cocaine cues and higher arousal/reactivity was associated with lower LPPs to cocaine cues.

Conclusions.

These results highlight the potential clinical utility of the LPP in assessing drug cue reactivity in trauma-exposed adults with substance use disorder.

Keywords: trauma, PTSD, late positive potential, cocaine use disorder, mood, cue reactivity

1. INTRODUCTION

Substance use disorders (SUD) and posttraumatic stress disorder (PTSD) are complex psychiatric conditions that commonly co-occur and have a difficult-to-treat clinical presentation (Mccauley et al., 2012). Rates of both diagnostic and subclinical (PTSD symptoms without full diagnostic criteria) PTSD among individuals with substance use disorder are substantial (Mclaughlin et al., 2015; Najavits et al., 2003; Pietrzak et al., 2011a, 2011b) and the presence of PTSD leads to poorer treatment outcomes compared to those with SUD alone (Ouimette et al., 2003, 1998). Exposure to trauma cues can increase emotional distress and drug craving, indicating negative emotionality plays a critical role in drug craving, which could contribute to treatment difficulties (Coffey et al., 2002; Coffey and Stasiewicz, 2007). A more nuanced investigation of how different PTSD symptoms enhance drug cue reactivity may inform theory and improve evidence-based clinical practice.

One physiological measure of cue reactivity is the late positive potential (LPP), an event-related potential (ERP) component observed over the central-parietal electrodes. The LPP typically begins around 300 milliseconds after the presentation of a cue or stimulus and measures brain activation or attention to emotionally evocative stimuli (Schupp et al., 2000). For example, pleasant and unpleasant images, words, faces, and facial expressions all have been shown to increase LPP amplitude (Hajcak et al., 2010; Keil et al., 2002; Schupp et al., 2004). As such, the LPP is thought to represent level of brain reactivity in response to events that capture attention and signify the motivational relevance an event.

As drug cues are motivationally salient, they typically elicit an LPP. For example, the LPP is enhanced to cocaine-related compared to neutral images, and this difference is larger in cocaine users compared to controls (Dunning et al., 2011; Moeller et al., 2012). The LPP to cocaine images is also positively associated with cocaine craving levels (Franken et al., 2008) and could indicate risk for relapse. In a large cross-sectional study, Parvaz, Moeller, and Goldstein (2016) found the LPP to be largest after one month of abstinence and smallest after two days and one year after abstinence, indicating a potential quadratic effect of time on LPP response to drug cues (Parvaz et al., 2016). Further, as addiction is often accompanied by a relative lack of interest in non-drug rewards (Hatzigiakoumis et al., 2011; Volkow et al., 2011; Volkow and Morales, 2015), one study found that the LPP response was reduced to pleasant images in comparison to drug images at the start of treatment, but this pattern reversed post-treatment (Parvaz et al., 2017a).

A smaller body of literature indicates that individuals who have experienced trauma show differences in LPP amplitude to unpleasant images. For example, earthquake-exposed undergraduates displayed an enhanced LPP to earthquake compared to neutral images, an effect that was not observed in controls (Zhang et al., 2015). Furthermore, higher PTSD symptoms among undergraduate students have been related to increased LPP amplitude in response to unpleasant images (Lobo et al., 2015). A similar pattern was documented among combat veterans, such that those with higher PTSD symptom severity showed greater increases in the LPP response to angry faces (Macatee et al., 2020). In addition to increased reactivity to unpleasant stimuli, decreased positive affect is common among those with PTSD (Fonzo, 2018); however, a nascent literature suggests there is no difference between individuals with and without PTSD in LPP amplitude to pleasant images (Saar-Ashkenazy et al., 2015; Wessa et al., 2005). Therefore, more research in larger samples of individuals with PTSD symptoms would be useful in clarifying the relationship between PTSD and the LPP to emotional images.

Trauma and substance cues each tend to increase craving and distress among individuals with comorbid PTSD and cocaine use disorder (CUD) (Coffey et al., 2002). Consistent with the self-medication theory, individuals with PTSD may use mood-altering drugs like cocaine to dampen trauma-related distress (Ruglass et al., 2017; Tull et al., 2011; Vujanovic et al., 2016; Wojciechowski, 2018). Indeed, an emergent literature suggests that individuals with comorbid SUD and PTSD, as compared to SUD-alone, are more likely to use substances in response to unpleasant emotional states (Tull, Gratz, et al., 2016; Vujanovic & Back, 2019; Waldrop et al., 2007). This body of work supports the negative reinforcement model of substance use, which posits that the avoidance of or escape from emotional distress is a primary motive for continued substance use (Baker et al., 2004). Thus, over time, substances – and by extension substance imagery cues – may gain added motivational significance (Tull et al., 2011), thereby driving LPP reactivity even more strongly among individuals with comorbid CUD and PTSD vs. CUD alone.

To inform clinical interventions, it is also important to understand which PTSD symptoms may induce cue-elicited reactivity and craving, and ultimately, substance use. Evidence suggests that certain PTSD symptoms are more closely related to substance use, and that this may differ by substance type. It is hypothesized that those with hyperarousal or intrusion symptoms may seek depressant substances to reduce anxiety (Stewart et al., 1998). Accordingly, several studies have reported associations between hyperarousal and intrusion symptoms and alcohol/opioid misuse (Avant et al., 2011; Somohano and Bowen, 2019; Tull et al., 2010; Walton et al., 2017). One study also noted that the most common PTSD symptoms observed in a cocaineusing sample were alterations in affect, detachment, and irritability (Najavits et al., 2003), suggesting that avoidance or negative alterations in mood may prompt stimulant-seeking behavior (but see Dworkin et al., 2018). In addition, among women with interpersonal trauma, avoidance was greater in illicit drug users as compared to alcohol users (Sullivan and Holt, 2008). Importantly, some major changes have been made to the assessment and measurement of PTSD within the DSM-5. One study specifically utilized the PTSD Checklist for DSM-5 (PCL-5) in order to identify which revised PTSD symptom clusters (i.e., intrusion, avoidance, negative alterations in cognition and mood, and arousal/reactivity) are related to alcohol misuse in a veteran sample (Walton et al., 2017). Intrusion, negative alterations in cognition and mood (NACM) and arousal/reactivity predicted alcohol misuse, while avoidance did not.

The current study aimed to address important gaps in the literature. First, while available studies have investigated the differential effects of PTSD symptoms with substance use, there is little information on these associations in the context of drug cue reactivity or trauma cue reactivity, which can provide meaningful information about risk for relapse. Second, while PTSD symptoms and SUD have been related to the LPP separately, the associations between PTSD symptoms and the LPP has not been investigated in a sample of adults with SUD. The goal of the current study was to assess the predictive validity of PTSD symptom cluster severity with regard to cue reactivity in a sample of adults with CUD and to identify if particular symptom clusters are more related brain reactivity to cocaine cues and/or trauma cues. Specifically, we examined if the PTSD clusters would interact with image type. There is limited research on whether the PTSD symptom clusters should differentially predict trauma cue reactivity; however, based on previous literature in substance users, we expected that higher PTSD NACM and avoidance symptoms would be related to an increased LPP amplitude to cocaine imagery cues.

2. MATERIALS AND METHODS

2.1. Design

The study sample consisted of participants enrolled in an ongoing randomized clinical trial involving psychosocial and medication-based treatment for CUD (NCT02896712) who completed electroencephalogram (EEG) testing at baseline. The UTHealth IRB (HSC-MS-15-0595) approved this study in accord with both the Declaration of Helsinki and the Belmont Report. Consenting participants completed an intake visit during which time a structured clinical interview was administered, along with self-report questionnaires. The intake visit was followed by a baseline visit where ERP data were recorded before entry into the clinical trial. Results from the main study involving cluster analysis of LPP responses in CUD are presented elsewhere (Webber et al., in Press).

2.2. Participants

The current study included 52 participants who were between 18–60 years of age and meeting criteria for a current diagnosis of moderate-to-severe CUD, as determined by the DSM-5. Participants were excluded if they met DSM-5 criteria for an additional SUD with the exception of cannabis, nicotine, or alcohol use disorder not requiring medical detoxification. Further exclusion criteria included individuals with hairstyles preventing valid EEG recordings, reported history of epilepsy, seizure disorder, or loss of consciousness in the last five years.

2.3. Measures

2.3.1. Structured Clinical Interview for DSM-5 (SCID-5; First, Williams, Karg, & Spitzer, 2015).

The SCID-5 is a well-established structured diagnostic interview designed to assess major DSM-5 psychiatric disorders. For purposes of the present study, the SCID-5 was used to establish study inclusionary/exclusionary criteria, as noted above, and to assess for the presence of current and lifetime psychiatric disorders.

2.3.2. Addiction Severity Index-Lite (ASI; McLellan et al., 1992).

The ASI-Lite is a well-established, multi-dimensional, interview-based measure for SUD that assesses the respondent’s lifetime and past-month status across seven domains (e.g., alcohol and drug use, employment/self-support). The ASI was used to collect sample characteristics including gender, age, race, ethnicity, income, years of education, and cocaine use severity based on recent (number of days of use in the past 30 days) and lifetime (total years) cocaine use.

2.3.3. The Life Events Checklist for DSM-5 (LEC-5; Weathers et al., 2013).

The LEC-5 is a self-report questionnaire used to screen for potentially traumatic events experienced at any time throughout the lifespan. Respondents are presented with 16 potentially traumatic events (e.g., natural disasters, sexual assault, transportation accident) as well as an additional item assessing for ‘other’ potentially traumatic events not listed. Respondents are asked to indicate (via check mark) whether each listed event “happened to me,” “witnessed it,” “learned about it,” “part of my job,” or “not sure.” If participants endorsed “happened to me” or “witnessed it” for a given item, this was coded as positive exposure to the particular traumatic event type. Trauma load, or the total number of different trauma types experienced or witnessed, was created and assessed as a potential covariate in the main analysis.

2.3.4. PTSD Checklist for DSM-5 (PCL-5; Blevins, Weathers, Davis, Witte, & Domino, 2015; Weathers et al., 2013).

The PCL-5 is a 20-item self-report questionnaire that measures PTSD symptom severity. Each item reflects a symptom of PTSD according to the DSM-5 (APA, 2013). Respondents are asked to rate each item on a 5-point scale (0 = Not at all to 4 = Extremely) in regard to the frequency in which they have been bothered by the symptom in the past month (e.g., “In the past month, how much have you been bothered by repeated, disturbing, and unwanted memories of the stressful experience?”). Total symptom severity scores range from 080, with higher scores indicating higher symptom severity. A probable PTSD diagnosis may be indicated by PCL-5 total scores greater than 33 (Blevins et al., 2015). The PCL-5 has demonstrated good psychometric properties (Blevins et al., 2015; Briere, 2001; Morey, 2007; Weathers et al., 1993). Internal consistency of the total PTSD symptom severity (PCL-5 total score) in the current sample was excellent (α = .94). As specified by the DSM-5 and assessed by the PCL-5, the symptom clusters of PTSD include the following subscales, which also showed excellent internal consistency: intrusion (α = .86), avoidance (α = .84), NACM (α = .90), and arousal/reactivity (α = .83; American Psychiatric Association, 2013).

2.3.5. Picture Viewing Task.

Participants completed a Picture Viewing Task during the EEG recording. Participants viewed a 20-minute slideshow (Versace et al., 2012a) containing pleasant images, unpleasant images, neural images, and cocaine images. The pleasant images contained the following subcategories of images: erotic (ERO), romantic (ROM), and sweet foods (SWE). The unpleasant images contained the following subcategories of images: mutilations (MUT), violence (VIO), and accidents (ACC). The neutral images (NEU) included two categories averaged together: random household objects and humans with neutral expressions. The cocaine images included images of types of cocaine (powder and crack cocaine), paraphernalia such as a pipe, and people using cocaine (COC). Sixteen images from each of the nine categories (144 total) were presented to each participant in a random order. The images were presented in four separate blocks. Each block contained an equal number of images from each category. Within each block, images were randomly presented to each participant, however, the blocks were always presented in the same order. The pleasant, unpleasant, and neutral images were selected from the International Affective Picture System (IAPS), while the cocaine images were selected from previous studies investigating the LPP in cocaine users (Dunning et al., 2011; Lang et al., 1997; Moeller et al., 2009; Parvaz et al., 2017b). The images, presented with E-Prime 2 Professional software (Pittsburg, PA), appeared on the screen for four seconds. Each photo was separated by a black screen with a white fixation cross located in the center that appeared for an inter-trial-interval average of 3750 ms.

2.4. EEG Analysis

EEG data were recorded using a 64-channel actiCAP active electrode cap, amplified using BrainAmp MR, and digitized using Brain Vision Recorder (Brain Products, Munich). Electrode impedances were kept lower than 100 kΩ prior to recording the data. Data sampling occurred at a rate of 500 Hz and filtered with 0.1 Hz high-pass and 100 Hz low-pass filters. Eye blinks and movements were corrected using an automatic artifact detection, which uses a spatial filtering method as implemented in Brain Electrical Source Analysis (BESA 6.1; MEGIS Software, GmbH, Gräfelfing, Germany). Brain Vision Analyzer was used to further evaluate the data. Data filtration occurred offline with a 0.1 Hz low-pass and a 40 Hz high-pass filter. The data were segmented beginning 100 ms before the image onset and ending 1000 ms after the image onset giving 1100 ms epochs. The data were baseline-corrected to the 100 ms pre-stimulus period and re-referenced to the average reference. Artifacts including eye blinks, facial movements, and bad electrodes were detected and if more than 10% of the sensors within a segment were contaminated by artifacts, segments were rejected. The LPP was calculated by averaging electrode amplitudes at a time window of 400–800 ms post-stimulus. The electrodes of interest (Figure 1) were a group of centro-parietal electrodes selected based on previous LPP studies (Parvaz et al., 2017b; Versace et al., 2012b). The LPP was averaged across all subcategories to create four main image content types: pleasant, unpleasant, cocaine, and neutral.

Fig 1.

Fig 1.

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Late positive potential to unpleasant, pleasant, cocaine, and neutral images. UNP = unpleasant, PLE = pleasant, NEU = neutral, and COC = cocaine.

2.5. Data Analysis Plan

Potential confounds, including age, gender, race, ethnicity, education, trauma load (LEC5), and cocaine use severity (number of cocaine use days, past-month; number of years of cocaine use) were evaluated as potential covariates. None of these variables was related to either PCL-5 symptom cluster scores or LPP amplitudes, so the final analysis did not include covariates (Assmann et al., 2000; Pocock et al., 2002). Image Type, defined as which category of image was presented (Versace et al., 2012b), and PCL-5 intrusion, avoidance, NACM, and arousal/reactivity clusters served as the independent variables (Tull et al., 2010; Walton et al., 2017). The dependent variable was LPP amplitude.

A linear mixed-effects model was used to assess the effects of PCL-5 symptom cluster scores and Image Type on LPP amplitude. Fixed effects were Image Type, PCL-5 symptom cluster scores, and their interactions. lmer and lmertest were used to perform analyses in R, and the Satterthwaite method was used for degrees of freedom (Bates et al., 2014; R Core Team, 2020). PCL-5 symptom cluster scores were mean-centered and the mean-centered variables were used to calculate the interactions. Random-effect models were established by generating a maximal model and iteratively reducing it using the RePsychLing package (Baayen et al., 2015; Bates et al., 2015; Matuschek et al., 2017). Following significant interactions, we performed simple effects post-hoc tests with the emmeans package that estimated the difference between each experimental (pleasant, unpleasant, cocaine) image type and neutral image type at −1SD below and +1SD above mean PCL-5 cluster score (Lenth, 2019). All significant follow-up tests survived Holm-Bonferroni correction for multiple comparisons. Finally, multicollinearity was assessed and all VIF values were < 4, indicating no issues (O’Brien, 2007). Analyses were repeated with just the total PCL-5 score as a single predictor.

3. RESULTS

The sample primarily included low-income, inner-city African American males. Participant characteristics are summarized in Table 1. About 27% of the sample met probable PTSD criteria, based on the PCL-5. Participants most commonly experienced natural disasters, fires/explosions, physical/weapon assault, and transportation/serious accidents. The trauma history characteristics of the sample are summarized in Table 2. Correlations among PCL-5 clusters are presented in Table 4.

Table 1.

Sample Characteristics

Characteristic M (SD) / n, Range
Age (years)1 51.3 (7.0)
Education (years)1 12.5(1.5)
Sex1 Male 44
Female 8
Race1 African American 43
White 6
Other/Not Reported 3
Ethnicity1 Hispanic 4
Not Hispanic 48
Cocaine use1 Past 30 days 18.9(9.5), 2–30
Years of use 19.5(10.1), 3–40
Other SUD Diagnoses Alcohol 16
Cannabis 8
Current SCID Diagnoses Major Depressive Disorder 2
Generalized Anxiety Disorder 1
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Note. Total n = 52.

1

Data derived from the Addiction Severity Index-Lite.

Table 2.

Trauma History and PTSD symptoms

n
PCL-51 PTSD Diagnosis (≥33) 14
SCID-52 PTSD Diagnosis 7
Cluster M(SD)
PCL-51 Intrusions 4.8(4.6)
Avoidance 2.5(2.6)
NACM3 7.0(7.0)
Arousal/Reactivity 6.5(5.6)
LEC-5: Total Trauma load (number of traumatic event types)3 5.2(3.2)
LEC-5 Trauma Event Type Participant Experienced Participant Witnessed
Natural Disaster 30 17
Fire or Explosion 11 12
Transportation Accident 32 7
Serious Accident 13 8
Exposure to Toxic Substances 2 0
Physical Assault 26 11
Weapon Assault 24 8
Sexual Assault 12 1
Unwanted Sexual Experience 9 1
Combat Exposure 3 1
Captivity 6 1
Life Threatening Illness 4 6
Severe Human Suffering 2 7
Sudden Violent Death 0 12
Accidental Death 2 9
Serious Harm Caused by Participant 4 4
Other 11 6
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Note.

1

PCL-5: PTSD Checklist for DSM-5.

2

SCID-5: Structured Clinical Interview for DSM-5.

3

NACM: Negative Alterations in Cognitions and Mood Symptoms of PTSD per PCL-5.

3

LEC-5:Life Events Checklist for DSM-5, Number of trauma types =experienced or witnessed per Life. Values are the number of participants who indicated experiencing each event (n = 52).

Table 4.

Correlations among PCL-5 Clusters

PCL-51 Cluster Intrusions Avoidance NACM2 Arousal/Reactivity
Intrusions --- .52** .60** .48**
Avoidance --- .65** .68**
NACM --- .76**
Arousal/Reactivity ---
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Note.

**

= p < .01.

1

PCL-5 = PTSD Checklist for DSM-5.

2

NACM = Negative alterations in cognition and mood.

There was a typical LPP response that was larger for pleasant, unpleasant, and cocaine-related images compared to neutral. EEG waveforms for the whole sample are displayed in Figure 1. The linear mixed effect model revealed a significant main effect of Image Type such that pleasant, unpleasant, and cocaine images elicited more positive LPPs than neutral (See Table 3 for full omnibus effects). No differences were observed between the emotional and cocaine images (p’s > .05). There was a significant interaction effect between the PCL-5 NACM cluster severity score and Image Type on the LPP. As shown in Figure 2, follow-up tests revealed that within low PCL-5 NACM individuals, unpleasant (p < 0.001) and pleasant (p < 0.001) images elicited larger LPPs than neutral images, but there was no difference between cocaine and neutral images (p = 0.97). Within high PCL-5 NACM individuals, cocaine images elicited larger LPPs compared to neutral (p = .001), but there was no difference between pleasant (p = 0.84) and unpleasant images (p = 0.94) compared to neutral images. There was also a significant interaction effect between the PCL-5 arousal/reactivity cluster severity score and Image Type on the LPP in the opposite direction as NACM. Follow-up tests revealed that within low PCL-5 arousal/reactivity individuals, cocaine images elicited larger LPPs compared to neutral (p < .001), but there was no difference between pleasant (p = 0.14) and unpleasant (p = 0.59) compared to neutral images. Within high PCL-5 arousal/reactivity individuals, unpleasant (p < 0.001) and pleasant (p < 0.001) images elicited larger LPPs than neutral images, but there was no difference between cocaine and neutral images (p = 0.91).

Table 3.

Effect of Image Type and PTSD Symptom Clusters on LPP Amplitude

Main Category Analysis
IV Sum of Squares df F P
Image Type 36.93 3/70 12.82 <0.01*
PTSD Intrusions 0.03 1/47 0.03 0.86
PTSD Avoidance 0.09 1/47 0.10 0.76
PTSD NACM 1.56 1/47 1.62 0.21
PTSD Arousal/Reactivity 0.27 1/47 0.29 0.59
Image Type * Intrusions 4.26 3/70 1.48 0.23
Image Type * Avoidance 2.37 3/70 0.82 0.49
Image Type * NACM 23.52 3/70 8.17 <0.01*
Image Type * Arousal/Reactivity 16.14 3/70 5.60 <0.01*
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Note.

*

indicates p < 0.01. NACM = negative alterations in cognition and mood.

Fig 2.

Fig 2.

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Late positive potential means by Image Type, depicted at −1/+1 SD above/below mean PCL-5 cluster severity scores. A) Interaction between NACM cluster severity score and Image Type. Individuals with higher PCL-5 NACM scores had an increased LPP to cocaine images. B) Interaction between PCL-5 arousal/reactivity and Image Type. The LPP to cocaine images was smaller for those with greater arousal/reactivity symptoms. UNP = unpleasant, PLE = pleasant, NEU = neutral, and COC = cocaine, NACM = Negative alterations in mood and cognition.

Finally, the when including just the PCL-5 total score as a sole predictor, PCL-5 total score did not significantly predict the LPP (F(1, 50) = 2.11, p = 0.15) or interact with Image Type (F(3, 50) = 1.21, p = .31).

4. DISCUSSION

The results of the current study revealed several primary findings. First, when controlling for all symptom and image types, those with greater PCL-5 NACM symptoms displayed larger LPP amplitudes to cocaine-related images. Conversely, those with greater PCL-5 arousal/reactivity symptoms displayed smaller LPP amplitudes to cocaine images. Second, the LPP to both emotional images (pleasant and unpleasant) appeared to relate to PCL-5 scores in an opposite manner compared to the cocaine images. Specifically, the LPP to emotional images was increased in those with higher PCL-5 arousal/reactivity scores, but decreased in those with higher PCL-5 NACM scores. Finally, the PCL-5 total score did not solely predict the LPP, emphasizing the roles of the individual cluster severity scores.

Greater PCL-5 NACM symptom severity was related to increased reactivity to cocaine-related images, even when controlling for the other PTSD symptom clusters. Thus, individuals with CUD who experience greater trauma-relevant negative mood states and/or maladaptive trauma-related cognitions (e.g., self-blame) may be more likely to experience cocaine use as especially rewarding given the absence of perceived or actual environmental rewards (Vujanovic et al., 2017). This aligns with previous motivational theories of addiction suggesting negative affect is a defining feature of CUD (Klein et al., 2020; Stritzke and Mcevoy, 2007). This finding expands upon prior research suggesting that substance users with PTSD show increased reactivity to drug cues (Tull, Gratz, et al., 2016; Tull, McDermott, et al., 2016; Vujanovic et al., 2016, 2019) and rate cocaine-related stimuli as more arousing (Coffey et al., 2002). In the current study, NACM specifically emerged as the strongest predictor of brain reactivity to cocaine cues, highlighting the importance of assessing individual PTSD symptom clusters.

These results are also consistent with and expand upon current functional magnetic resonance imaging (fMRI) studies on drug cue reactivity. Drug cues are known to increase both craving and brain activity in the extended visual system, insular cortex, limbic system, and prefrontal cortex in substance users (Childress et al., 1999; Engelmann et al., 2012; Hanlon et al., 2018). It is possible that exposure to trauma and/or experiencing PTSD symptoms can increase this response: fMRI studies indicate that trauma severity in substance users is related to increased activity in the limbic system and visual cortex when viewing drug images (Elton et al., 2015; Regier et al., 2017). As the LPP is thought to arise from a complex network of brain areas, including the visual cortex, amygdala, prefrontal cortex, and insula (Liu et al., 2012; Sabatinelli et al., 2007), the LPP may be a practical and informative alternative option to fMRI for measuring cue reactivity in larger intervention trials. Importantly, neuroimaging studies have shown that medication interventions can affect brain reactivity to cocaine cues differently depending on trauma history. Compared to cocaine-dependent individuals who did not experience childhood trauma, cocaine-dependent women who experienced childhood trauma showed increased brain activity in the amygdala in response to cocaine cues after oxytocin administration, which has been shown to decrease reactivity (Joseph et al., 2020). Additionally, interventions involving exposure to trauma-related cues can reduce drug craving (Back et al., 2019; Nosen et al., 2014). As the LPP is a direct and easily obtained measure of brain activity, it could be a useful and practical tool to assess PTSD symptom-related reactivity to drug cues as a mechanism of change in future SUD/PTSD clinical trials.

Arousal/reactivity symptoms were also associated with the LPP to cocaine cues, but in an opposite pattern – greater arousal/reactivity symptoms were associated with a smaller LPP to cocaine cues. Even though all participants were cocaine users, these finding suggests that those reporting higher arousal/reactivity symptoms may not attribute higher motivational relevance to cocaine-related cues. Notably, these findings are inconsistent with at least one study that found that increased subjective distress following trauma script exposure was positively related to attentional bias to cocaine cues among individuals with cocaine use disorder (Tull et al., 2011). These inconsistencies could also be due to the differences in conceptualization of arousal/reactivity and attentional bias and suggest the association between PTSD arousal/reactivity symptoms and cocaine cue reactivity should be explored further. Previous studies have primarily found positive relationships between arousal/reactivity and opioid and alcohol use (Avant et al., 2011; Somohano and Bowen, 2019; Tull et al., 2010). The current study sample only included individuals with CUD, but future studies should compare these associations across individuals with various substance use disorders and PTSD symptomatology.

Surprisingly, PCL-5 cluster scores were not specifically related to an increased LPP to unpleasant images. Instead, both pleasant and unpleasant images increased the LPP in those with higher arousal/reactivity scores. Therefore, the presence of arousal/reactivity symptoms may enhance attention toward all types of emotional images rather than just toward unpleasant images. This finding highlights the need for more research comparing types of emotional cues, as prior neuroimaging studies typically only focus on unpleasant trauma-specific cues and have not compared them to pleasant cues (Bremner et al., 1999b, 1999a; Dannlowski et al., 2012; Ehlers et al., 2010). However, it is possible that the association between PTSD symptom severity and the LPP to unpleasant images is dampened in individuals with SUD. Furthermore, while there was variability in the PCL-5 scores, only a few participants met full DSM-5 criteria for PTSD. Therefore, these findings could be a reflection of the overall lower level of PTSD symptom severity in this sample as compared previous studies (Lobo et al., 2014). Another consideration in this line of inquiry is the degree of ‘match’ (i.e., trauma-relatedness) between the trauma histories of participants and imagery cue content. For example, individuals with PTSD due to earthquake exposure showed increased LPP amplitudes to earthquake-related stimuli compared to earthquake-exposed individuals without PTSD (Zhang et al., 2015). The present sample was comprised of individuals with diverse trauma histories. As we did not specifically query the ‘worst’ or index traumas directly, it is possible that the most salient traumas did not match the unpleasant image types presented in the study, leading to the less robust LPP to unpleasant images observed.

Finally, frequency of cocaine use in the past 30 days was not associated with LPP amplitude to cocaine cues, which is consistent with previous literature (Dunning et al., 2011). The LPP may be more related to length of abstinence. One study found a parabolic trajectory of cue reactivity as a function of duration of abstinence in individuals with CUD (Parvaz et al., 2016), with cue-induced LPP amplitudes the lowest in individuals who have been abstinent for 2 days or less and one year or more and cue-induced LPP amplitudes the highest in individuals who have been abstinent for one month. All the participants in our sample had used cocaine at least once in the 30 days prior to the study, so based on the findings in previous studies, we would not expect a relationship between LPP amplitude and cocaine use recency. Importantly, the LPP may provide additional information beyond that of self-reported days of use.

Current findings should be considered in light of study limitations. First, the study sample primarily consisted of low-income, Black/African American male participants, including only eight female participants who experienced predominantly interpersonal traumas. This limits the extent to which these findings might generalize to women and non-interpersonal trauma survivors with CUD and varying levels of PTSD. Second, the current study also had a relatively low number of participants meeting the DSM-5 criteria for a PTSD diagnosis based on the SCID-5 and PCL. Although the sample showed a representative range of PCL-5 scores, the study should be replicated in a sample of participants with more severe PTSD. Third, craving in response to the Picture Viewing Task was not assessed, so the relative contribution of cue-induced craving could not be evaluated. Fourth, previous studies that have investigated the relative contribution of PTSD symptom clusters and substance use had larger sample sizes compared to the current study that was based on 52 participants. However, a relative strength of the current study included the use of a laboratory-based study that elicited brain reactivity in response to cues. Fifth, generalizability is limited to those that meet the inclusion criteria for participating in EEG studies (i.e., no history of seizure disorder, no major neurological conditions, and no major head injury with loss of consciousness). Finally, participants in the current study were treatment-seeking adults with CUD, further limiting the generalizability of findings to non-treatment-seeking populations. Despite the limitations, the current study assessed an objective biomarker of arousal in response to drug and emotional stimuli in a clinical population with moderate-to-severe CUD, diverse trauma histories, and subclinical to clinical PTSD.

In conclusion, the current study showed that, among adults with CUD, greater NACM symptom severity was related to greater reactivity to cocaine imagery cues, while greater arousal/reactivity symptom severity was related to less reactivity to cocaine cues. If replicated, these findings could have clinical utility. The LPP could be used as a potential objective indicator of reactivity to cocaine cues in future clinical trials. Cognitive-behavioral interventions designed to target specific PTSD symptoms clusters may aid in lowering reactivity to substance cues, which could be helpful in the treatment of trauma-exposed individuals with SUD.

Highlights.

  • PTSD symptoms are related to increased cocaine cue reactivity

  • Relations of PTSD to late positive potential to cocaine imagery cues were evaluated

  • PTSD cognition/mood symptoms were associated with increased cocaine cue reactivity

  • PTSD arousal/reactivity was associated with decreased response to cocaine cues

Acknowledgements

The authors would like to acknowledge Sarah McKay for her help in collecting the EEG data.

Funding

NIDA 1F32DA048542 (HEW), NIDA R01DA039125 (JMS)

Footnotes

Author Disclosures

Role of Funding Source: The funding source had no role in the design and conduct of the study, the analysis and interpretation of data, or in the preparation, review, or approval of the manuscript.

Conflict of Interest

The authors declare that they have no conflict of interest.

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