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Learn more: PMC Disclaimer | PMC Copyright Notice Psychophysiology . 2026 Apr 10;63(4):e70295. doi: 10.1111/psyp.70295 Search in PMC Search in PubMed View in NLM Catalog Add to search The Impact of Error‐Related Brain Activity and Parental Attachment on Youth Posttraumatic Stress Symptoms Annabel Fuller Annabel Fuller 1 Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA 2 Department of Psychiatry and Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA Find articles by Annabel Fuller 1, 2 , Kathryn Jenkins Kathryn Jenkins 1 Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA 2 Department of Psychiatry and Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA Find articles by Kathryn Jenkins 1, 2 , Kayla Kreutzer Kayla Kreutzer 1 Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA 2 Department of Psychiatry and Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA Find articles by Kayla Kreutzer 1, 2 , Alexa House Alexa House 1 Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA 2 Department of Psychiatry and Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA Find articles by Alexa House 1, 2 , Shiane Toleson Shiane Toleson 2 Department of Psychiatry and Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA Find articles by Shiane Toleson 2 , Anthony King Anthony King 1 Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA 2 Department of Psychiatry and Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA Find articles by Anthony King 1, 2 , K Luan Phan K Luan Phan 2 Department of Psychiatry and Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA Find articles by K Luan Phan 2 , Stephanie Gorka Stephanie Gorka 1 Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA 2 Department of Psychiatry and Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA Find articles by Stephanie Gorka 1, 2, ✉ Author information Article notes Copyright and License information 1 Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA 2 Department of Psychiatry and Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA * Correspondence: Stephanie Gorka ( [email protected] ) ✉ Corresponding author. Revised 2026 Feb 10; Received 2025 May 22; Accepted 2026 Mar 20; Issue date 2026 Apr. © 2026 The Author(s). Psychophysiology published by Wiley Periodicals LLC on behalf of Society for Psychophysiological Research. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. PMC Copyright notice PMCID: PMC13069009 PMID: 41964122 ABSTRACT Exposure to traumatic events is common in youth and associated with acute and sustained posttraumatic stress symptoms (PTSS). Theory suggests that exaggerated threat sensitivity contributes to greater PTSS severity, and emerging work points to parental attachment as a potential moderator of the association between threat sensitivity and PTSS, although no study has directly tested this hypothesis. The aim of the current study is to examine the unique and interactive effects of neurobiological threat sensitivity and parental attachment on PTSS severity in trauma‐exposed youths. A total of 174 participants 16–19 years old completed self‐report questionnaires assessing parental attachment and PTSS severity and a well‐validated modified flanker task designed to probe the error‐related negativity (ERN), an event‐related potential that reflects individual differences in threat sensitivity. To test our hypotheses, we conducted a series of hierarchical linear regression analyses. Separate models were run for each PTSS cluster, with age and sex as covariates. As expected, low parental attachment was associated with increased PTSS severity across all clusters. There were no main effects of ERN amplitude. However, a significant ERN × parental attachment interaction emerged for two clusters—intrusions (B) and avoidance (C). At low levels of parental attachment only, more negative ERN amplitude was associated with increased intrusions and avoidance symptoms. These findings suggest that neurobiological threat sensitivity and parental attachment may interact to influence specific PTSS symptoms in trauma‐exposed youth. Keywords: error‐related negativity, parental attachment, post‐traumatic stress, youth Impact Statement This study reveals that enhanced neurobiological threat sensitivity, as reflected by ERN amplitude, may intensify PTSS re‐experiencing and avoidance symptoms in the context of low parental attachment. By identifying this interaction, the findings advance precision medicine in mental health by highlighting how individual differences in brain function and relational environment shape symptom severity. These insights pave the way for more targeted, mechanism‐based interventions tailored to a person's unique neurobiological and psychosocial risk profile. 1. Introduction The experience of trauma in childhood is highly prevalent among youth. A large US nationally representative survey found over 60% of adolescents aged 13–17 experienced at least one form of potentially traumatic event (DSM‐IV criterion A1) (McLaughlin et al. 2013 ). An established body of literature demonstrates that trauma exposure is linked to the development of psychopathology, including affective disorders, suicidality, substance misuse, and both acute and chronic post‐traumatic stress symptoms (PTSS) (Dye 2018 ). Studies estimate that 5%–35% of youth who have experienced a potentially traumatic event meet full diagnostic criteria for post‐traumatic stress disorder (PTSD) (Ackerman et al. 1998 ; McLaughlin et al. 2013 ; McLeer et al. 1998 ). Importantly, youth displaying subthreshold criteria for PTSD exhibit considerable functional impairment and distress, comparable to those with PTSD diagnosis (Carrion et al. 2002 ). A comprehensive understanding of individual differences in PTSS severity in youth is critical to develop personalized intervention and prevention efforts for those at threshold and subthreshold PTSD. Decades of research have explored how individual differences in neurobiological threat sensitivity contribute to the development and persistence of PTSS. Neurobiological threat sensitivity refers to an individual's nervous system reactivity to perceived dangers or stressors (Stein and Nesse 2011 ; Woody and Szechtman 2011 ). Broadly, both theoretical and empirical work suggest that within trauma‐exposed populations, heightened threat sensitivity is associated with more severe PTSS. Studies have shown that trauma exposure can alter brain development over time, particularly affecting the structure and function of threat‐responsive regions such as the hippocampus, prefrontal cortex (PFC), and amygdala (Cerqueira et al. 2007 ; Stevens et al. 2013 ; Tanriverdi et al. 2022 ; Tomoda et al. 2009 ; van Harmelen et al. 2014 ). Additionally, individuals with PTSS often exhibit increased attentional bias toward threat (Dennis‐Tiwary et al. 2019 ; Grupe et al. 2016 ; Naim et al. 2015 ), exaggerated startle responses (Grillon et al. 1998 ; Jovanovic et al. 2010 ; Morgan III et al. 1995 ), elevated cortisol production (Elzinga et al. 2003 ; Gola et al. 2012 ), and heightened skin conductance during threat anticipation (Orr et al. 2012 ). However, findings in this area have not been entirely consistent; several studies have reported null results (Jovanovic et al. 2010 ; Rabinak et al. 2013 ) or even inverse relationships between threat sensitivity markers and PTSS (Britton et al. 2005 ). These inconsistencies suggest that additional moderating factors likely influence the relationship between threat sensitivity and PTSS. One objective, neurobiological index of threat sensitivity and internal error monitoring is the error‐related negativity (ERN), an event‐related brain potential (ERP) that appears as a negative‐going deflection in the electroencephalogram (EEG) waveform following the commission of an error (Falkenstein et al. 1991 ; Gehring et al. 1993 ). The ERN is well‐validated and observed across various task paradigms, age ranges, and species (Holroyd et al. 1998 ; Lawler et al. 2001 ). There has been ongoing debate regarding the functional significance of the ERN. Prominent theories view the ERN as a neural signal reflecting cognitive control and conflict monitoring that detects errors and facilitates behavioral adjustments (Gehring et al. 1993 ; Pasion and Barbosa 2019 ; Yeung et al. 2004 ). Within this framework, the ERN arises when there is a discrepancy between intended and actual outcomes, prompting increased cognitive control to prevent future errors. In contrast, there is a substantial body of research that argues that the ERN reflects the extent to which an error is motivationally significant and therefore serves as neural index of threat sensitivity (see Weinberg et al. 2012 for review; Weinberg et al. 2015 ). Along similar lines, other theories such as the compensatory error monitoring hypothesis (CEMH; Moser et al. 2013 ) proposed that an enhanced ERN is reflective of a compensatory mechanism that serves to regulate anxiety. This framework is supported by several empirical findings that show strong associations between ERN amplitude, worry and anxious apprehension (Moser et al. 2012 ; Härpfer et al. 2022 ). At the same time, there exists other, potentially conflicting findings, including those from Gorka et al. ( 2017 ), which demonstrate that ERN amplitude is also associated with dimensions of fear and arousal, suggesting that the ERN may not be specific to any one transdiagnostic symptom domain. Despite these theoretical differences, most agree that the ERN captures functioning of the performance monitoring system that guides and shapes behavior in response to errors, and that this system has been found to be consistently hyper‐active in those with anxiety and fear‐based disorders (Hajcak 2012 ; Meyer 2017 ; Weinberg et al. 2012 ). Empirical findings on the association between ERN amplitude and PTSS have been mixed. Lieberman et al. ( 2017 ) found that a more negative ERN amplitude was associated with increased hyperarousal symptoms in a sample of community‐based young adults. Similarly, Lackner et al. ( 2018 ) reported more negative ERN amplitudes in youth with a greater history of adverse events compared to those with little or no such history. In contrast, Letkiewicz et al. ( 2023 ) found that cumulative childhood trauma predicted a less negative ERN in young adults, and a study of combat‐exposed veterans found no significant differences in ERN amplitude between those with and without PTSD (Rabinak et al. 2013 ). These conflicting findings highlight the need for further research to clarify the nature of the ERN‐PTSS relationship and to identify individual differences that may moderate this association. Emerging evidence suggests parental and family factors might moderate relationships between neurobiological threat sensitivity and PTSS, given their well‐established influence on both ERN amplitude and PTSS. According to attachment theory, an individual's attachment to their primary caregivers influences the development of emotional regulation mechanisms that guide them in times of stress or in presence of threat throughout the lifespan (Bowlby et al. 1992 ). Therefore, threat sensitivity can be buffered or exacerbated by parental factors like attachment (Mikulincer et al. 2002 ). This theory is supported by several lines of research, including studies showing that ERN amplitude is influenced by parenting and early environmental factors, which in turn contribute to internalizing symptoms (Chong et al. 2020 ; Meyer et al. 2015 ; Pinquart 2017 ). Further, research shows that attachment styles influence coping, biological stress reactivity, and PTSS following trauma exposure (Huang et al. 2017 ; O'Connor and Elklit 2008 ; Ogle et al. 2015 ). Taken together, there are well‐established relationships between parental factors such as attachment and ERN amplitude on PTSS. However, the potential interactive effects of attachment and ERN on PTSS, particularly in youth, have not been elucidated. This gap in knowledge is noteworthy given that attachment may either buffer or exacerbate the influence of threat sensitivity on PTSS in trauma‐exposed youth. PTSS comprises four qualitatively distinct symptom clusters: (B) re‐experiencing, (C) avoidance, (D) negative alterations in cognition and mood, and (E) hyperarousal (Yufik and Simms 2010 ), and threat sensitivity and attachment might influence distinct aspects of PTSS. Specific symptom clusters may have varying impacts on clinical and neurobiological outcomes, and it is therefore crucial to examine both how neural threat sensitivity and PTSS interact with parental attachment and whether these relationships differ depending on symptom subtype. To investigate mechanisms underlying PTSS symptom expression in youth, we recruited youth (ages 16–19) who were oversampled for a variety of early life traumas. This design allowed us to examine individual differences in the severity of current trauma symptoms and explore how variability in neurocognitive processes (ERN amplitude) may contribute to, or predict, symptom expression among trauma‐exposed youth. We hypothesized that a more negative ERN amplitude would be related to increased PTSS severity in symptom clusters (B) re‐experiencing and (E) hyperarousal, as they are linked to heightened threat sensitivity (Grupe et al. 2016 ; Lieberman et al. 2017 ), and that youths with low parental attachment would display a more robust association between ERN amplitude and PTSS severity than those with high attachment. 2. Methods 2.1. Participants Participants were recruited as part of a larger study examining the neurobiological mechanisms underpinning the association between trauma exposure, psychiatric symptoms, and alcohol use. Recruitment was conducted using flyers posted in the Columbus, Ohio area and social media advertisements and community engagement events. Participants were required to be between the ages of 16 and 19 and able to provide written informed consent or assent with parental consent. Participants were monetarily compensated for their time. As a part of the aims of the parent study, participants were placed into one of two groups: (1) lifetime history of interpersonal trauma exposure (i.e., physical assault, sexual assault, or immediate family violence) or (2) no lifetime history of interpersonal trauma exposure. However, all participants were over‐recruited for exposure to early life adversity so as to capture a broad range of childhood adversities. Given that the larger study was interested in the onset of alcohol use disorder, participants were required to have had minimal alcohol exposure at enrollment (i.e., self‐reported consuming > 1 but < 100 standard alcoholic drinks in their lifetime) but be at risk for the development of problematic alcohol use. Participants were considered “at risk” if they self‐reported one or both of the following: (1) affiliation with risky peers (i.e., friends who use alcohol and/or recreational drugs and engage in risky behavior such as going to parties), (2) access to and opportunities for consumption of alcohol. Exclusionary criteria included any major active medical or neurological illness, lifetime history of manic and or psychotic symptoms, active suicidal intent, deafness, traumatic brain injury, and current psychotropic medication use, lifetime history of alcohol or substance use disorder, and pregnancy. Participants completed a virtual screening session that included informed consent, diagnostic interviews, and a battery of self‐report questionnaires. Several days later, they completed a laboratory session for collection of task‐based data. All study procedures were approved by The Ohio State University Institutional Review Board. A total of 180 participants enrolled in the study and completed the baseline laboratory visit. Six were excluded from the study due to ERN data that was unusable, for example, contaminated by excessive artifact and/or the participant made less than six errors during the flanker task (Olvet and Hajcak 2008 ). The total sample size was therefore 174 participants. 2.2. Self‐Report Measures 2.2.1. Trauma Symptoms The PCL‐5 is a 20‐item self‐report measure that evaluates the degree to which an individual has experienced PTSD symptoms in the past month related to a distressing experience (Weathers et al. 2013 ). The PCL‐5 consists of four subscales for the four DSM–5 PTSD symptom clusters: intrusion (Items 1–5), avoidance (Items 6–7), alterations in cognition and mood (Items 8–14), and hyperarousal and reactivity (Items 15–20). Items are rated from 0 ( not at all ) to 4 ( extremely ) and were summed for a total severity score within each cluster. Internal consistency was good for the following PCL‐5 subscales: Intrusion ( α = 0.88), Avoidance ( α = 0.81), Negative Alterations in Cognitions and Mood ( α = 0.84), and Hyperarousal and reactivity ( α = 0.82). In addition to the PCL‐5, participants completed the trauma screener from the UCLA PTSD Reaction Index (RI) for DSM‐5 (Steinberg et al. 2004 ). The UCLA PTSD RI captures lifetime exposure to a wide range of traumatic events including: neglect/maltreatment, sexual abuse, sexual assault/rape, physical abuse, interpersonal violence, emotional abuse, domestic violence, community violence, war/political violence, life‐threatening medical illness, serious accident, school violence, disaster, terrorism, kidnapping, bereavement, separation from caregiver, and impaired caregiver. All responses were dichotomous and made on a yes versus no checklist and summed to calculate the number of lifetime trauma exposures. 2.2.2. Other Psychiatric Symptoms Current symptoms of anxiety and depression were assessed using the Beck Anxiety Inventory (BAI; Beck et al. 1988 ) and the Beck Depression Inventory‐II (BDI‐II; Beck et al. 1996 ). The BAI consists of 21 self‐report items rated on a four‐point scale ranging from 0 (“not at all”) to 3 (“severely”), with participants reporting on symptoms experienced over the past week. Total scores range from 0 to 63. Similarly, the BDI‐II includes 21 self‐report items, also rated on a four‐point scale from 0 to 3, with participants reporting on the past 2 weeks. Total BDI‐II scores likewise range from 0 to 63. Internal consistency of both measures was excellent (BAI: 0.91; BDI‐II: 0.90). 2.2.3. Parental Attachment Scale Parental attachment was assessed utilizing the Family Risk and Protective Factors questionnaire from the Communities That Care Youth Survey (Arthur et al. 2007 ). The measure consists of 38 items designed to assess risk and protective factors across multiple ecological domains. In the present study, we used the parental attachment (4‐item) subscale to test our hypotheses. Internal consistency for the parental attachment variable in the current study was acceptable ( α = 0.71). 2.3. Behavioral Task 2.3.1. Flanker Task Participants completed a modified version of the original flanker task (Eriksen and Eriksen 1974 ) to measure neural activity to error‐related negativity (ERN). During each trial, participants viewed five horizontally aligned arrows. For half of the trials, the arrows were compatible (‘>>>>>’ or ‘<<<<<’). For the other half of trails, the arrows were incompatible (‘>><>>’ or ‘<<><<’). Participants were instructed to respond as quickly and accurately as they could to indicate the directionality of the center arrow (pointing to the left or the right) by clicking the corresponding mouse button. The arrows were presented for 200 ms and participants were given up to 1800 ms to respond. Trials were followed by an intertrial interval (1000–2000 ms) during which a fixation cross appeared on the screen. The task consisted of 330 total trials, consisting of 11 blocks with 30 trials. The task encouraged fast and accurate responding by providing performance‐based feedback to participants at the end of each block. If their accuracy was 75% correct or lower, the message ‘Please try to be more accurate’ was presented; if accuracy was greater than 90%, the message, ‘Please try to respond faster’ was displayed; in all other cases, participants saw the message, ‘You're doing a great job’. 2.4. EEG Processing Continuous EEG was recorded using the ActiveTwo BioSemi system (BioSemi, Amsterdam, Netherlands). We used 34 standard electrode sites. One electrode was placed on each mastoid. Data was digitized at a sampling rate of 1024 Hz, using a low‐pass fifth order sinc filter with a −3 dB cutoff point at 208 Hz. All EEG data processing was performed through EEGLAB (Delorme and Makeig 2004 ) and ERPLAB (Lopez‐Calderon and Luck 2014 ) within the MATLAB environment (The Mathworks 2022 ). We resampled the raw EEG signals to 256 Hz with a mild antialiasing filter, an online low‐pass filter applied during data acquisition to minimize high‐frequency noise and aliasing artifacts. The signals were then re‐referenced to the average of the left and right mastoid electrodes and bandpass filtered using a Butterworth filter in the 0.10–30 Hz range. The EEGLAB algorithm was programmed to identify and remove channels exhibiting excessive noise (more than 4 standard deviations of the mean channel line noise), prolonged flatlining (over 5 s), or poor correlation with neighboring channels (< 0.85) (clean_rawdata, Kothe and Makeig 2013 ). All the channels removed were then interpolated. Data were segmented into 1500 ms epochs time‐locked to stimulus or response onset for each condition and was baseline corrected from −500 to −300 ms. We corrected eye movements and blink artifacts using the regression‐based method proposed by Gratton and Coles. This method utilizes the difference between external sensors placed above and below each eye, as well as sensors positioned laterally near the eyes (Gratton et al. 1983 ). Epochs containing artifacts were automatically identified and excluded based on three criteria in ERPLAB (Lopez‐Calderon and Luck 2014 ): (1) voltages exceeding 75 μV within a 200 ms moving window (shifting every 100 ms), (2) voltages below ±0.5 μV, or (3) voltage changes between successive samples exceeding 50 μV. Epochs were averaged by condition to extract event‐related potentials (ERPs) for analysis. The ERN and CRN were scored as the average activity on error and correct trials, respectively, from 0 to 100 ms after each response at electrode FCz, where the ERN was maximal across all subjects. To quantify the difference between error and correct trials, we followed guidelines by Meyer et al. ( 2017 ) calculating an ERN standardized residual score (ERN resid ) by saving the variance leftover in a regression where the CRN was entered predicting the ERN. The ERN resid was used as our primary variable in subsequent analyses. Behavioral data obtained from the flanker task included the number of error trials for each subject and accuracy expressed as a percentage of trials with correct responses out of the total number of trials. Split‐half reliability was calculated by correlating scores from odd‐ and even‐numbered trials and applying the Spearman‐Brown correction. Split‐half reliability was moderate for incorrect trials (ERN; r sb = 0.703) and excellent for correct trials (CRN; r sb = 0.914). Response locked ERN and ERN waveforms and scalp maps are presented in Figure 1 . FIGURE 1. Open in a new tab Response locked ERP waveforms and scalp maps. The red line corresponds to correct responses, the black dashed line corresponds to error responses, and the blue line corresponds to the ΔERN or the error minus correct difference waveform. Topographic scalp maps depict neural activity of the ERN and CRN at 0‐100 ms following the response. 2.5. Data Analysis Plan We performed a series of hierarchical linear regression analyses with each PCL‐5 subscore as a unique dependent variable. All continuous predictors were mean‐centered prior to analyses. Biological sex (dummy coded) and age were included as covariates and entered in block 1. Biological sex and age were assessed via self‐report and included as covariates due to well‐established age and sex differences associated with PTSS (Christiansen 2017 ; McGinty et al. 2021 ). Parental attachment and ERN amplitude were entered in block 2 to assess main effects of these variables. An (Attachment × ERN amplitude) interaction term was made by multiplying the predictor terms to create the product term. This interaction term was then entered in the final block of our hierarchical regression model to examine potential moderation effects. Significant two‐way interactions were followed up using a standard simple slopes approach (Aiken et al. 1991 ). An interaction term was created, and post hoc additional follow‐up linear regression models were run at high and low levels of parental attachment. PTSS often overlaps with other psychiatric symptoms, particularly depression and anxiety (Brady et al. 2000 ). We therefore conducted follow‐up sensitivity analyses to examine the unique and interactive effects of ERN amplitude and parental attachment on severity of depression (BDI‐II total) and anxiety (BAI total) symptoms. Models were consistent with those described above. Interpersonal trauma group membership was not included in the present analyses as it was not central to the study hypotheses and substantially overlapped with the primary outcome variable. Given our dimensional approach to modeling PTSS, we prioritized continuous symptom scores rather than categorical group comparisons. All analyses were conducted using SPSS v27 (IBM). We conducted exploratory post hoc analyses to test for potential moderation by biological sex. Specifically, we repeated the above models and included all possible two‐way interactions involving sex, as well as a three‐way sex × attachment × ERN amplitude interaction. In addition, we conducted supplemental post hoc analyses examining the ERN and CRN separately, rather than using the residualized ERN score. This was done to explore potential distinctions between the two components, as prior work has suggested that they may reflect partially distinct processes (e.g., Riesel et al. 2023 ). 3. Results 3.1. Sample Characteristics and Descriptives Demographic and descriptive statistics of the sample are presented in Table 1 . On average, participants endorsed a total of 3.09 ± 2.42 lifetime traumatic events. A total of 42 individuals (24.14%) met criteria for lifetime PTSD and 8 individuals (4.6%) met criteria for current PTSD. There were no differences in age ( F = 0.38, p = 0.54), ethnicity ( χ 2 = 1.95, p = 0.38), or race (% White; χ 2 = 0.05, p = 0.83) between individuals enrolled in the trauma versus no trauma group; however, the trauma group had a significantly greater proportion of biological females (76.9%; χ 2 = 6.92, p = 0.01) than the no trauma group (58.8%). Regarding behavioral performance during the flanker task, participants committed an average of 33.67 errors, which corresponds to 81.22% accuracy. TABLE 1. Participant demographics and characteristics. Demographics Mean (SD) or percent Age (years) 18.16 (0.90) Sex (% female) 68.40% Ethnicity (% Hispanic) 9.80% Race White 62.10% Black 13.20% Asian 10.90% Biracial, Other or Unknown 13.80% Lifetime SCID/KSAD diagnoses Major depressive disorder 56.3% Generalized anxiety disorder 9.80% Social anxiety disorder 20.10% Panic disorder 0.60% Specific phobia 2.90% Post‐traumatic stress disorder 24.00% Current SCID/KSAD diagnoses Major depressive disorder 9.80% Generalized anxiety disorder 8.60% Social anxiety disorder 13.20% Specific phobia 1.72% Post‐traumatic stress disorder 6.30% Open in a new tab 3.2. Unique and Interactive Effects of Parental Attachment and ERN Amplitude The results of each linear regression are presented in Table 2 and study variable means (and standard deviations) are presented in Table 3 . Results revealed that there were main effects of parental attachment on all four PTSS symptom clusters. As expected, parental attachment was moderately negatively correlated with PTSD symptom severity (PCL‐5 total; r = −0.328, p < 0.01), consistent with prior findings linking lower attachment to greater trauma‐related distress. Lower levels of parental attachment were associated with increased intrusions, avoidance, alterations in cognition and mood, and hyperarousal symptoms. There were also main effects of biological sex such that females reported greater intrusions and avoidance symptoms relative to males. Results revealed two‐way interactions between ERN amplitude and parental attachment in two models—intrusion symptoms (Cluster B) in addition to avoidance symptoms (Cluster C). TABLE 2. Linear regression analyses testing moderating impact of parental attachment on the association between ERN amplitude and PTSS symptoms. β t p Adj. R 2 R 2 change F change p ‐value change Intrusions (Cluster B) Step 1 0.03* 0.04 3.92 0.02 Sex 0.20* 2.73 0.01 Age 0.06 0.82 0.41 Step 2 0.07* 0.05 4.44 0.01 ERN residual −0.04 −0.51 0.61 Attachment −0.21* −2.85 0.01 Step 3 0.10* 0.03 6.07 0.02 ERN × Attachment 0.18 2.46 0.02 Avoidance (Cluster C) Step 1 0.04* 0.05 4.67 0.01 Sex 0.22* 2.90 < 0.01 Age 0.09 1.21 0.23 Step 2 0.09* 0.06 5.74 < 0.01 ERN residual −0.07 −0.98 0.33 Attachment −0.23* −3.10 < 0.01 Step 3 0.13* 0.04 8.69 < 0.01 ERN × Attachment 0.21* 2.95 < 0.01 Cognition and Mood (Cluster D) Step 1 0.01 0.02 1.40 0.25 Sex 0.11 1.41 0.17 Age 0.08 1.01 0.31 Step 2 0.13* 0.13 13.44 < 0.01 ERN residual 0.04 0.58 0.56 Attachment −0.37* −5.19 < 0.01 Step 3 0.13 0.00 0.09 0.76 ERN × Attachment 0.02 0.30 0.76 Hyperarousal (Cluster E) Step 1 < 0.01 0.01 1.09 0.34 Sex 0.09 1.23 0.22 Age 0.07 0.92 0.36 Step 2 0.05* 0.06 5.08 0.01 ERN residual 0.06 0.73 0.47 Attachment −0.24* −3.17 < 0.01 Step 3 0.05 0.00 < 0.00 0.97 ERN × Attachment −0.01 −0.04 0.97 Open in a new tab Note: Attachment = parental attachment subscale. Abbreviation: ERN, error‐related negativity. TABLE 3. Means and standard deviations for study variables. Scales Minimum Maximum Mean Standard deviation Beck Anxiety Index 0 52 14.03 10.10 Beck Depression Index 0 41 11.94 9.40 Attachment 1 4 2.59 0.73 PTSD Checklist for DSM‐5 0 71 20.07 15.59 Cluster B 0 20 4.7 4.58 Cluster C 0 8 2.87 2.50 Cluster D 0 26 7.27 6.20 Cluster E 0 23 5.24 4.99 Open in a new tab Abbreviation: PTSD, post‐traumatic stress disorder. Follow‐up analyses revealed that at low levels of parental attachment, a more negative ERN amplitude was associated with increased PTSS intrusion ( β = −0.24, t = −2.18, p = 0.031) and avoidance symptoms ( β = −0.31, t = −2.86, p = 0.005). At high levels of parental attachment, there was no association between ERN amplitude and PTSS intrusion ( β = 0.14, t = 1.37, p = 0.169) or avoidance symptoms ( β = 0.14, t = 1.38, p = 0.168). These results are illustrated in Figure 2 . FIGURE 2. Open in a new tab Interaction between ERN residual scores and parental attachment on posttraumatic stress symptom (PTSS) clusters B (Intrusion), C (Avoidance), D (Negative alterations in cognition/mood), and E (Hyperarousal). Each panel illustrates the relationship between increased and decreased ERN amplitude and PTSS severity at high and low levels of parental attachment. Colored dots reflect individuals at high or low levels of parental attachment. * p < 0.05. 3.3. Sensitivity Analyses We also ran the same analytic models using severity of depression (BDI score) and anxiety (BAI score) as separate outcomes. Lower parental attachment was associated with greater depression severity ( β = −0.38, t = −5.20, p < 0.001). There was no main effect of ERN amplitude ( β = 0.07, t = 0.93, p = 0.353), and no significant two‐way interaction ( β = 0.04, t = 0.51, p = 0.611). Consistent findings were observed for anxiety symptoms. Lower parental attachment was associated with greater anxiety severity ( β = −0.22, t = −2.97, p = 0.003). There was no main effect of ERN amplitude ( β = −0.01, t = −0.12, p = 0.906), and no significant two‐way interaction ( β = 0.04, t = 0.57, p = 0.567). Lastly, we conducted exploratory post hoc analyses testing for potential moderations by biological sex. We found no significant two‐ or three‐way interactions between sex, ERN amplitude, and attachment on PTSD symptom clusters. We also conducted supplemental analyses examining the ERN and CRN individually. These analyses revealed largely null results across all PTSD cluster models. However, there was a main effect of the ERN on Cluster C symptoms ( β = −0.15, t = −2.07, p = 0.04), such that a more negative ERN was associated with greater avoidance symptoms. No significant two‐way interactions with attachment were observed (all p s > 0.28). 4. Discussion Following a traumatic event, symptoms of PTSS are influenced by brain‐based individual difference factors as well as environment (Ogle et al. 2016 ; Tanriverdi et al. 2022 ; van Harmelen et al. 2014 ). Prior studies have demonstrated that neurobiological threat sensitivity and parental attachment impact PTSS (Chong et al. 2020 ; Huang et al. 2017 ), yet how these factors may interact to influence PTSS severity, particularly within youth, has not been previously reported. The aim of the current study was to explore the unique and interactive effects of ERN amplitude and parental attachment on PTSS in a cohort of youth oversampled for a diverse array of early life adversities. As hypothesized, results revealed a significant two‐way interaction between ERN amplitude and parental attachment in predicting intrusion symptoms (Cluster B). Interestingly, a similar interaction pattern also emerged for avoidance symptoms (Cluster C), although this association was not initially hypothesized. In contrast, the interaction did not significantly predict negative alterations in cognitions and mood symptoms (Cluster D), and contrary to our hypothesis, it also did not predict hyperarousal symptoms (Cluster E). At low levels of parental attachment, a more negative ERN amplitude was associated with increased intrusion and avoidance symptoms. At high levels of parental attachment, there was no association between ERN amplitude and PTSS. Sensitivity analyses revealed that there were no significant ERN amplitude by parental attachment interactions on depression or anxiety symptom severity. These findings suggest that ERN amplitude may influence specific PTSS symptom clusters, but only in the context of other risk factors such as low parental attachment. Taken together, these findings underscore the importance of considering both neurobiological and parental factors in understanding vulnerability to PTSS. Lower parental attachment was consistently linked to greater PTSS severity across all symptom clusters, aligning with prior research showing its association with detrimental mental health outcomes, including increased PTSS (Allen 2008 ; Amatya and Barzman 2012 ). Attachment theory underscores the importance of parental attachment on children's socioemotional development, as early primary caregiver interactions contribute to resilience in the presence of threat throughout the lifespan (Bowlby 1969 ). Social bonds like parental attachment are thought to influence the development and maintenance of PTSS by affecting a person's response to a traumatic event (Charuvastra and Cloitre 2008 ). The robust main effect observed between low parental attachment and increased symptom severity across all clusters suggests low parental attachment may be a significant risk factor for increased PTSS severity, consistent with previous research (O'Connor and Elklit 2008 ), emphasizing the critical role of early attachment in shaping psychological resilience. Furthermore, high levels of parent attachment may serve as a protective buffer, potentially mitigating the severity of PTSS. This buffering effect highlights the potential value of fostering secure attachment relationships, both in preventive efforts and as part of trauma‐informed interventions aimed at enhancing recovery. Notably, our findings also revealed a significant interaction between parental attachment and ERN amplitude on two specific PTSS clusters: intrusions and avoidance. A more negative ERN, which is typically associated with heightened sensitivity to perceived threats, was associated with increased avoidance and intrusion symptoms at low but not high levels of attachment. This suggests that children with lower parental attachment may lack the necessary buffers, such as parental support, to effectively manage their heightened sensitivity, thereby contributing to more severe intrusion and avoidance symptoms. It is possible this relationship stems from the role parents play in guiding their children's ability to recognize and respond to errors and threats, whether through verbal or non‐verbal reactions to mistakes or by exhibiting controlling behavior during their children's performance. As parental attachment can have substantial impacts on psychological resilience (Ding et al. 2023 ), those with low parental attachment may report more intrusion and avoidance symptoms due to a controlling or punitive parenting style. The absence of a secure parental buffer likely contributes to the emergence of the expected relationship between heightened threat sensitivity and PTSS in these adolescents. Symptom clusters D (negative alterations in cognition and mood) and E (hyperarousal) were not significantly influenced by the interaction between parental attachment and ERN amplitude. The lack of effect for cluster D was hypothesized, as cluster D symptoms, such as anhedonia and low positive affect, overlap with depressive features. Previous research suggests that heightened threat sensitivity is more strongly linked to fear‐related symptoms than to distress‐related symptoms (Shankman et al. 2013 ), which may help explain the absence of an association with this cluster. In contrast, the null interaction for cluster E was contrary to our hypotheses. In a previous study, Lieberman et al. ( 2017 ) found that a more negative ERN amplitude was correlated with increased hyperarousal symptom severity in adults. Our results did not find a significant unique effect of ERN amplitude on hyperarousal symptoms, nor an ERN by attachment interaction. Hyperarousal symptoms are multifaceted (Blevins et al. 2015 ) and may present differently in youth while threat systems are still maturing (Weinberg et al. 2016 ). Further research is needed to clarify the underlying processes that contribute to this symptom cluster. The current study had several strengths, including being a large, representative youth cohort that was oversampled for complex trauma history and a reliable, well‐validated neural index of threat responding. Limitations of the study include exclusion of youths taking psychotropic medications in the sample, potentially restricting the symptom severity of this population and impacting the generalizability of the findings. The current study was cross‐sectional and therefore the temporal and causal relationships between trauma exposure, ERN amplitude, parental attachment, and PTSS severity cannot be inferred. Furthermore, our measures of parental attachment and PTSS were based on self‐report, which may be subject to biases such as social desirability or inaccurate recall. Future longitudinal studies that incorporate multimodal assessments are needed to better understand the observed relationships. Notably, this study was a secondary analysis conducted as part of a larger NIH‐funded parent project and was not preregistered. Although our hypotheses were theory‐driven and informed by prior research, the absence of preregistration introduces the potential for analytic flexibility, which should be considered when interpreting the findings. 5. Conclusion In sum, our findings suggest that heightened neurobiological threat sensitivity, as indexed by ERN amplitude, may contribute to greater re‐experiencing and avoidance symptoms of PTSS in the context of low parental attachment. By identifying this interactive effect, the study advances our understanding of the heterogeneous pathways through which PTSS can develop and be maintained. These results underscore the importance of considering both neural and parental influences in shaping trauma‐related outcomes and point to the potential for more targeted, mechanism‐informed interventions tailored to individual risk profiles. Author Contributions Annabel Fuller: conceptualization, writing – original draft, writing – review and editing, formal analysis. Kathryn Jenkins: investigation, writing – original draft, writing – review and editing, formal analysis, visualization. Kayla Kreutzer: project administration, writing – review and editing. Alexa House: writing – review and editing, investigation, data curation. Shiane Toleson: writing – review and editing, data curation, investigation. Anthony King: writing – review and editing, conceptualization. K. Luan Phan: conceptualization, funding acquisition, writing – review and editing, supervision. Stephanie Gorka: conceptualization, investigation, funding acquisition, writing – original draft, supervision, formal analysis, writing – review and editing, project administration. Funding This work was supported by the National Institute on Alcohol Abuse and Alcoholism (grant number R01AA028225; principal investigator: S. M. Gorka). Conflicts of Interest The authors declare no conflicts of interest. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. References Ackerman, P. T. , Newton J. E., McPherson W. B., Jones J. G., and Dykman R. 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