Neural correlates of error processing: Linking adverse childhood experience to adolescent inhibitory control and internalising and externalising symptoms

Neural correlates of error processing: Linking adverse childhood experience to adolescent inhibitory control and internalising and externalising symptoms | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 27 January 2026 V1 Latest version Share on Neural correlates of error processing: Linking adverse childhood experience to adolescent inhibitory control and internalising and externalising symptoms Authors : Satwika Rahapsari , Kubra Ulusoy 0009-0006-0649-0321 , Richard Rowe , Myles Jones , and Liat Levita 0000-0001-6002-6817 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.176951755.57729381/v1 191 views 66 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This study explored the understudied neurocognitive mechanisms underlying the relationships between adverse childhood experiences (ACEs), inhibitory control processes, and internalising and externalising symptoms in adolescents aged 14 to 17 years (n = 50). To that end, Electroencephalography (EEG) data were collected as participants performed a Go/No-go task. Inhibitory control was assessed through error processing, measured behaviourally by commission error rate (frequency of incorrect ”Go” responses when withholding was required) and neurally by error-related negativity (ERN), a frontal event-related potential (ERP) linked to error-monitoring processes. Greater exposure to ACEs was associated with elevated internalising, but not externalising, symptoms. ACEs were also related to larger ERN amplitudes, in the absence of differences in behavioural response inhibition as indexed by commission error rates. In turn, enhanced ERN amplitudes were linked to higher internalising symptoms, although ERN did not mediate the relationship between ACEs and internalising outcomes. Together, this pattern indicates that heightened neural error monitoring may function as a correlated marker of vulnerability following ACE exposure rather than a direct mechanistic pathway. Overall, these findings demonstrate that heightened neural error monitoring in adolescents exposed to ACEs is linked to internalising symptoms independently of behavioural inhibition task performance. This dissociation underscores the potential value of neural markers of error processing for identifying adolescents at risk for internalising difficulties following early adversity. Neural correlates of error processing: Linking adverse childhood experience to adolescent inhibitory control and internalising and externalising symptoms Satwika Rahapsari 1a, 2 , Kubra Ulusoy 1a,3 , Richard Rowe 1 , Myles Jones 1 , Liat Levita 1a , 4* 1 School of Psychology, University of Sheffield 1a Formally, School of Psychology, University of Sheffield 2 Faculty of Psychology, Universitas Gadjah Mada 3 Departement of Psychology Hacettepe University 4 School of Psychology, University of Sussex *Corresponding author: Dr. Liat Levita School of Psychology, University of Sussex https://orcid.org/0000-0001-6002-6817 ; Email: [email protected] Dr. Satwika Rahapsari Faculty of Psychology, Universitas Gadjah Mada, Indonesia https://orcid.org/0000-0001-6798-1745 ; Email: [email protected] Dr. Kubra Ulusoy Department of Psychology, Hacettepe University, Turkey https://orcid.org/0009-0006-0649-0321; Email: [email protected] Professor Richard Rowe School of Psychology, University of Sheffield https://orcid.org/0000-0001-5556-3650; Email: [email protected] Dr. Myles Jones School of Psychology, University of Sheffield https://orcid.org/0000-0002-4580-7559; Email: [email protected] Corresponding author Dr. Liat Levita Institution: School of Psychology, University of Sussex Email: [email protected] CRediT author statement Satwika Rahapsari: Conceptualization, Investigation, Formal analysis, Data Curation, Writing- Original draft preparation. Kubra Ulusoy, Software; Methodology; Writing- Reviewing and Editing. Richard Rowe, Supervision, Writing- Reviewing and Editing. Myles Jones, Supervision, Writing- Reviewing and Editing. Liat Levita, Conceptualization, Supervision, Project administration, Writing- Reviewing and Editing Acknowledgements This research was funded by the Beasiswa Pendidikan Indonesia (BPI) program, Centre for Higher Education Funding and Assessment, Ministry of Higher Education, Science, and Technology of the Republic of Indonesia (202101120142, 1615/BPPT/BPI.LG/VI/2023), granted to SR’s doctoral study, supervised by LL. Abstract This study explored the understudied neurocognitive mechanisms underlying the relationships between adverse childhood experiences (ACEs), inhibitory control processes, and internalising and externalising symptoms in adolescents aged 14 to 17 years (n = 50). To that end, Electroencephalography (EEG) data were collected as participants performed a Go/No-go task. Inhibitory control was assessed through error processing, measured behaviourally by commission error rate (frequency of incorrect ”Go” responses when withholding was required) and neurally by error-related negativity (ERN), a frontal event-related potential (ERP) linked to error-monitoring processes. Greater exposure to ACEs was associated with elevated internalising, but not externalising, symptoms. ACEs were also related to larger ERN amplitudes, in the absence of differences in behavioural response inhibition as indexed by commission error rates. In turn, enhanced ERN amplitudes were linked to higher internalising symptoms, although ERN did not mediate the relationship between ACEs and internalising outcomes. Together, this pattern indicates that heightened neural error monitoring may function as a correlated marker of vulnerability following ACE exposure rather than a direct mechanistic pathway. Overall, these findings demonstrate that heightened neural error monitoring in adolescents exposed to ACEs is linked to internalising symptoms independently of behavioural inhibition task performance. This dissociation underscores the potential value of neural markers of error processing for identifying adolescents at risk for internalising difficulties following early adversity. Keywords : Adolescence, Adverse childhood experiences (ACEs), cognitive control, inhibitory control, error-related negativity (ERN), internalising symptoms, externalising symptoms, Go/No-go task, EEG Introduction Adverse Childhood Experiences (ACEs), such as abuse, neglect, and household dysfunction, are robust predictors of later-life psychopathology (McKay et al., 2022; Sahle et al., 2022; Wade et al., 2022), including both internalising (e.g., anxiety, depression) and externalising (e.g., aggression, conduct disorders, substance use) symptoms in adolescence (Anderson et al., 2022; Bevilacqua et al., 2021; Hales et al., 2024; March-Llanes et al., 2017). To inform the development of targeted, preventative mechanisms, it is crucial to elucidate the neurocognitive mechanisms that link early adversity to increased vulnerability for mental health issues (Teicher & Samson, 2016). A key pathway potentially disrupted by ACEs involves alterations in cognitive control, the executive functions essential for self-regulation, attention maintenance, and goal-directed behaviour, which in turn, could increase susceptibility to mental health problems (Berens et al., 2017; McCrory et al., 2017; McCrory & Viding, 2015). A core component of cognitive control, inhibitory control, or the capacity to suppress automatic or impulsive reactions (Gratton et al., 2018), is consistently found to be negatively impacted by ACEs across the lifespan (Rahapsari & Levita, 2024). Notably, inhibitory control is a key factor associated with the development of both internalising and externalising psychopathologies (for review, see Santens et al., 2020). Hence, investigating the mechanisms through which ACEs influence inhibitory control and internalising/externalising symptoms is essential for understanding the pathways that contribute to mental health problems. This is particularly relevant during adolescence, a stage of development characterised by increased emotional sensitivity, an increase in social and academic demands, and evolving cognitive capacities, making inhibitory control during this stage vital for managing stress, regulating emotions, and maintaining attention amidst these challenges (Schweizer et al., 2020). Some evidence suggests that alterations in neural systems supporting inhibitory control, primarily assessed using neuropsychological tasks and functional magnetic resonance imaging (fMRI), may partly account for associations between ACEs and internalising and externalising symptoms (e.g., Fava et al., 2019; Hallowell et al., 2019). However, the extent to which these mechanisms generalise across developmental stages and neural measures remains unclear. Consistent with this line of work, Karlsgodt et al. (2018) demonstrated that internalising and externalising symptoms in young individuals have been linked to distinct patterns of brain activation during the Multi-Source Interference Task (MSIT), a task that assessed inhibitory control. Using fMRI, the authors found that externalising behaviours were linked to reduced activation in brain regions involved in inhibitory control, including the prefrontal cortex (PFC), anterior cingulate cortex (ACC), and parietal cortex, while internalising behaviours showed altered activation in emotional processing areas, such as the amygdala and ventromedial PFC. Although Karlsgodt et al. (2018) did not explicitly examine childhood adversity, these neural patterns align with a broader body of research suggesting that early adverse experiences can disrupt typical brain development in these same regions. For instance, Bick and Nelson (2016) reviewed evidence showed that early-life stress, including neglect and maltreatment, is associated with structural and functional changes in the PFC, ACC, and amygdala, areas implicated in emotion regulation, cognitive control, and stress reactivity. Supporting this, McLaughlin et al. (2014) reported that childhood adversity is linked to reduced volume and altered connectivity in frontolimbic circuits, potentially contributing to risk for both internalising and externalising psychopathology. These findings converge on the hypothesis that ACEs may contribute to the emergence of behavioural and emotional difficulties through their impact on the neurodevelopment of brain systems governing cognitive control and emotion regulation. A growing body of fMRI research has investigated how ACEs are associated with alterations in neural mechanisms underlying inhibitory control and related behavioural outcomes. These studies have identified functional and structural differences in the PFC, ACC, and amygdala (Herzberg & Gunnar, 2020; McLaughlin et al., 2015; Tottenham, 2009). While fMRI provides high spatial resolution for identifying brain regions implicated in inhibitory control and emotion processing, its limited temporal resolution constrains insight into the timing and dynamics of neural processes associated with ACEs. In contrast, electroencephalography (EEG) offers millisecond-level temporal resolution, making it particularly well suited to capturing the fast and dynamic neural processes underlying cognitive control (Gyurkovics & Levita, 2021). Moreover, EEG’s ability to track rapid neural activity renders it an ideal tool for investigating the temporal dynamics of inhibitory control and error processing (Gratton et al., 2018) in relation to ACEs and behavioural outcomes, yet empirical evidence applying EEG to this question remains limited. Specifically, EEG can measure inhibitory control by assessing how individuals adjust their performance following errors (Gehring et al., 1993). Error processing involves utilising feedback, both internal and external, to detect mistakes and modify behaviour to avoid further errors. Recognising errors is crucial to signal the need for behavioural adjustments to improve future outcomes (Falkenstein et al., 2000; Holroyd & Coles, 2002). This ability to detect mistakes and initiate corrective actions plays a vital role in adapting to changing environments and effective decision-making (Ullsperger et al., 2014). Error-related negativity (ERN) is commonly used to assess error processing (Lackner et al., 2018), it is an event-related potential (ERP) that captures neural activity occurring following an error, typically within 0 to 50 milliseconds (Luck, 2014). The ERN is believed to represent a component of cognitive control that signals when behavioural adjustments are needed, particularly in response to increased response conflict, such as slowing down after a mistake (Tamnes et al., 2013). Originating in the ACC, the ERN appears to mark the early detection of conflict and the initiation of inhibitory control mechanisms (Herrmann et al., 2004; Luu et al., 2004; Vanveen & Carter, 2002). It reflects a rapid, transient adjustment in cognitive control, helping individuals to react and adjust behaviour based on situational demands. A greater or more pronounced negative ERN amplitude is associated with better cognitive control, particularly in inhibition and attentional regulation (Grammer et al., 2014; Larson & Clayson, 2011). Furthermore, the ERN is also believed to reflect how individuals direct their attention to internal threats, including how threatening they perceive errors to be (Weinberg et al., 2012, 2016). Children and adolescents who experience physical and/or emotional abuse may exhibit heightened ERN, possibly due to an increased need to monitor possible threats or mistakes that may result in negative outcomes (Banica et al., 2019; Meyer et al., 2015). Indeed, heightened ERN amplitude during inhibitory control tasks has been reported in children with experiences of maltreatment (Lim et al., 2015), those who were raised by parents exhibiting demeaning, excessively punitive, rigid, or overly controlling parenting behaviours (Brooker, 2018; Chong et al., 2020), children exposed to interpersonal stress (Mehra et al., 2022) and adolescents with high levels of trauma (Lackner et al., 2018). Furthermore, Banica et al. (2019) found that the impact of ACEs on error processing continues into early adulthood. Given that ACEs are known to heighten sensitivity to threat and disrupt regulatory processes (Marusak et al., 2015; McLaughlin et al., 2019), the observed increase in ERN among individuals with ACEs may reflect an adaptive, albeit heightened, response to perceived danger (when making an error), potentially shaped by early-life adversity (Herzog & Schmahl, 2018; Lackner et al., 2018). Indeed, errors can activate defensive reflexes similar to those triggered by the stress of threats, such as exposure to harmful stimuli (Riesel et al., 2012). Such brain responses may activate defensive mechanisms to mitigate potential harm (Riesel et al., 2012). However, the relationship between ACEs and error processing is complex, with some studies reporting conflicting relationships or no relationship at all. Thus, rather than a heightened ERN, reduced ERN amplitudes following errors have been observed in children and adolescents (11–16 years old) exposed to neglect and deprivation-related ACEs (Buzzell et al., 2020; Troller‐Renfree et al., 2016). Other studies suggest that cumulative ACEs exposure is associated with ERN blunting and impaired error processing in youth aged 8–15 (Fava et al., 2019; Tabachnick et al., 2018), as well as in adults (Letkiewicz et al., 2023). In contrast, some studies report no association. For example, McDermott et al. (2012) found no evidence of an association of ACEs with ERN amplitude in 8-year-old children, and more recently, Compton et al. (2024) reported null findings in young adult participants. Taken together, these inconsistencies underscore the need for further investigation into whether alterations in the ERN are associated with ACEs and whether they may be functionally linked to downstream outcomes, particularly in the domain of mental health. As, beyond its association with ACEs, the ERN has been widely studied as a neural correlate of internalising and externalising symptoms. Associations of ERN and internalising and externalising problems have been documented in several studies. In individuals with internalising symptoms such as anxiety and depression, a larger ERN is often observed after making errors, which may reflect increased sensitivity to mistakes and an overactive performance-monitoring system (Cavanagh et al., 2017; Meyer & Gawlowska, 2017). This heightened response may serve as a neural marker for excessive worry and fear of failure, characteristics of internalising disorders (Weinberg et al., 2010, 2016). Notably, research has indicated that ERN mediates the association between strict, punitive parenting and heightened anxiety symptoms (Chong et al., 2020). This implies that alteration in ERN linked to ACEs may contribute to the emergence of internalising difficulties. In contrast, externalising symptoms, including impulsivity, aggression, drug abuse, and conduct problems, are typically linked to a blunted ERN response to errors (Gorka et al., 2019; Heritage & Benning, 2013; Meyer & Klein, 2018; Pasion & Barbosa, 2019). This reduced neural response has been suggested to result from a deficit in performance monitoring and diminished sensitivity to errors, potentially contributing to maladaptive behaviours such as risk-taking and poor self-regulation (Hall et al., 2007; Pasion & Barbosa, 2019). Further, two empirical studies (Letkiewicz et al., 2023; Troller‐Renfree et al., 2016) have directly tested the hypothesis that ACEs influence internalising and externalising symptoms through impaired neural activity, as reflected in ERN abnormalities. Letkiewicz et al. (2023) reported that adults who experienced early-life adversity exhibit reduced ERN, indicative of diminished error-monitoring capabilities. This study also identified ERN amplitude as a mediator of the association between ACEs and externalising symptoms, highlighting error-monitoring deficits as a possible pathway between ACEs and behavioural difficulties. Similarly, Troller‐Renfree et al. (2016) examined children aged 11–12 years who experienced institutional care and found that this adversity disrupted error-monitoring processes, as measured by blunted ERN amplitude during the Flanker task, a measure of inhibitory control where participants respond to a target stimulus while ignoring surrounding distracting stimuli. The blunted ERN was associated with greater externalising problems, including ADHD-related symptoms, but not with internalising behaviours (Troller‐Renfree et al., 2016). While evidence supports associations between ACEs, ERN, and internalising and externalising behaviours, the complex interconnections among these constructs, particularly in adolescents, remain underexplored. Further, the complex interplay between ACEs, ERN, response inhibition and behavioural outcomes underscores the importance of considering additional factors. These include benevolent childhood experiences (BCEs) which encompass supportive and nurturing experiences like strong familial support, positive peer relationships, and community connection. BCEs have been shown to serve as protective factors that can foster resilience and buffer against the detrimental impacts of ACEs (Hou et al., 2022; Masten & Cicchetti, 2010). It is possible that BCEs shape the direction of the associations between ACEs, inhibitory control, and internalising/externalising symptoms. Additionally, individual differences in pubertal maturation have emerged as another factor influencing the impact of ACEs on developmental outcomes. Research suggests that the pubertal stage may provide a more developmentally salient indicator of neurobiological maturation than chronological age, particularly in relation to brain function and mental health, (Blakemore et al., 2010; Vijayakumar et al., 2018). For example, studies have shown that pubertal stage predicts changes in neural activation within brain regions implicated in cognitive control, emotion regulation, and reward sensitivity, such as the amygdala, medial PFC, and ventral striatum, which are also known to be affected by ACEs (Braams et al., 2015; Forbes et al., 2011; Pfeifer et al., 2011; Urošević et al., 2012). Biological sex has also been identified as an important moderator of the impact of ACEs on psychological and neurocognitive outcomes. Studies suggest that females are more likely to experience internalising symptoms in response to adversity, whereas males often exhibit externalising symptoms (Rice et al., 2015; Zahn-Waxler et al., 2008). This difference in response patterns may stem from a combination of social (e.g., gender roles and expectations) and biological (e.g., hormonal) factors, which could influence how ACEs manifest and affect developmental outcomes (Ho et al., 2024; Nolen-Hoeksema, 2012). Moreover, there is evidence that variability in the ERN and its association with anxiety differ across biological sex (Moser et al., 2016). Hence, it is key to take into account of these moderators, as they are essential for understanding the nuanced relationships between ACEs and developmental outcomes. 1.1 Current Study Consequently, this study was designed to examine the impact of adverse childhood experiences (ACEs) on response inhibition and error-related negativity (ERN) in adolescents aged 14–17, while also considering the potential moderating effects of benevolent childhood experiences (BCEs), pubertal stage, and biological sex. To our knowledge, no previous research has specifically focused on this age group. This developmental period is particularly critical, as ERN amplitude is hypothesised to become more pronounced during mid-to-late adolescence, a time when neural responses associated with cognitive control are thought to undergo significant maturation (Davies et al., 2004; Ladouceur et al., 2007). Understanding the role of ERN amplitude during adolescence is, therefore, crucial as this stage also represents a time of increased susceptibility to the emergence of psychopathology (Ladouceur, 2012; Paus et al., 2008). Building on these considerations, the present study investigated whether inhibitory control performance and ERN amplitude mediate the association between ACEs and adolescent internalising and externalising symptoms in adolescence. It was hypothesised that higher levels of self-reported ACEs would be associated with greater internalising and externalising symptoms, and that individual differences in inhibitory control performance and ERN amplitude would be related to these symptom domains. In line with prior evidence, larger ERN amplitudes were expected to be associated with higher levels of internalising symptoms. To strengthen the validity of mediation analyses, this study controlled for potential confounding variables known to influence both cognitive and mental health outcomes. Specifically, intelligence quotient (IQ) and socioeconomic status (SES), age, sex, and race were included as covariates. Controlling for IQ accounts for general cognitive ability, which may affect inhibitory control performance and ERN amplitude independently of adversity exposure (Best & Miller, 2010; Friedman et al., 2006). Similarly, SES is a well-established contextual factor associated with both early life adversity and developmental outcomes, including psychopathology and cognitive control (Hackman & Farah, 2009; Noble et al., 2005). Including age, sex, and race as covariates further helps to account for demographic influences that may affect neurocognitive development and mental health outcomes, thereby providing a more rigorous test of the hypothesised mediation pathways. Additionally, moderator analyses were performed to test whether BCEs, pubertal stage, and biological sex moderate the association between ACEs, inhibitory control (both behavioural performance and ERN amplitudes) and internalising/externalising symptoms. These moderation analyses were pre-registered as part of the study’s analytic plan based on theoretical prediction. It was predicted that higher levels of BCE may buffer the negative effects of ACEs on inhibitory control, potentially enhancing resilience in cognitive control processes (Han et al., 2023; Masten & Tellegen, 2012; Narayan et al., 2018). Similarly, BCE have been proposed to buffer the impact of ACEs on internalising and externalising symptoms by fostering resilience (Feiler et al., 2023; Somefun et al., 2023), and supporting adaptive emotional and behavioural regulation (Crandall et al., 2020; Hays-Grudo & Morris, 2020). However, given the substantial conceptual and empirical overlap between ACEs and BCE, their effects are likely to reflect partially shared variance rather than independent and opposing processes. Further, a more advanced pubertal stage has been hypothesised to amplify the associations between ACEs and inhibitory control difficulties, given evidence that pubertal neurodevelopment may heighten stress sensitivity and challenge emerging self-regulatory capacities (Dahl & Gunnar, 2009; Tottenham & Galván, 2016). It may also intensify the direct effects of ACEs on psychopathological symptoms through increased emotional reactivity and hormonal changes (Colich et al., 2020; Patton & Viner, 2007). Finally, biological sex is anticipated to moderate these pathways differentially, with females potentially exhibiting stronger associations between ACEs and internalising symptoms, consistent with higher rates of internalising problems among adolescent girls (Zahn-Waxler et al., 2008), while males may show stronger links between ACEs and externalising symptoms (Liu et al., 2013). In addition, sex differences in brain development and stress responsivity may also influence the relationship between ACEs and inhibitory control, as evidence suggests differential maturation trajectories and neurobiological stress responses between sexes (Ordaz & Luna, 2012). 2. Methods 2.1. Participants An a priori power analysis was conducted using G*Power software (Faul et al., 2007) to estimate the required sample size for the study. Although G*Power does not have a specific function for mediation analysis, the power analysis was based on a linear multiple regression model (fixed model, R 2 deviation from zero) as an approximation. This approach is commonly used in mediation research to estimate the sample size needed to detect effects in the individual paths (i.e., X M and M Y) as well as the overall model (Fritz & MacKinnon, 2007; Thoemmes et al., 2010). Based on theoretical considerations and previous research examining the associations between ACEs and neurocognitive outcomes and psychopathology (McLaughlin et al., 2014), a small effect size (f 2 = 0.02), an alpha level of 0.05, and a desired power of 0.80 were specified, which indicated that a target sample size of 65 was required. Participants were recruited from local secondary schools and youth organisations across Sheffield, UK, through posters, online advertisements, and outreach to youth-focused community groups. Interested individuals were directed to contact the research team and complete an initial screening form to assess eligibility. The screening ensured participants met the inclusion criteria, which required that they have no current medical, psychiatric, or neurological conditions and not be taking any medication. Eligible participants were then invited to a laboratory session. A total of 67 mid-adolescents (14-17 years old) were initially recruited. However, EEG data from two participants were not recorded due to technical issues, and 15 participants had an inadequate number of error trials for ERN analysis. As a result, the final analytical sample comprised 50 participants (Table 1, demographic information). All participants were fluent in English, had normal or corrected-to-normal vision, and reported no neurological, developmental, or psychiatric condition or use of medication. This study was approved by the University of Sheffield School of Psychology Research Ethics Committee (060847). ———– Insert Table 1 ———– 2.2. Measures 2.2.1. Go/No-go Task Participants took part in the Zoo task (Figure 1), a validated adaptation of the Go/No-Go paradigm designed for younger populations (Grammer et al., 2014; Kavanaugh et al., 2024). In this Zoo task, participants were asked to assist a zookeeper in capturing escaped animals. The task comprised two trials: Go trials and No-Go trials. During Go trials, participants were required to press the spacebar as quickly and accurately as possible upon seeing any animal except an orangutan. Orangutans, depicted as helpers for the zookeeper, required participants to inhibit their response upon seeing them (No-Go trials). Prior to the main task, participants completed a series of practice trials to confirm their understanding of the instructions. The practice session comprised 12 trials, including three featuring orangutans and nine involving other zoo animals. Following the practice trials, the researcher reviewed participants’ responses to check their understanding and provided feedback if necessary to clarify any uncertainties. The main task consisted of 320 trials; 75% Go trials and 25% No-Go trials. Trials were segmented into eight blocks, each consisting of 40 trials, including 10 orangutan pictures and 30 pictures of zoo animals. Each trial began with a picture of an animal, which was displayed for 750 ms, followed by a 500 ms blank screen during which participants were expected to respond by pressing the spacebar. A fixation cross appeared before each animal image, with the inter-trial interval randomly varying between 200-300 ms with jittered timing to reduce anticipatory responses. During the trials, after each block of the task, participants received performance feedback, either “Try to catch them even faster next time!” or “Watch out for the orangutan friends!” based on their responses. The feedback provided to participants was automatically adjusted based on their accuracy in the previous block to help maintain their performance and keep the error rate around 10%. This adjustment ensured a sufficient number of errors, which is important for capturing a stable error-related waveform. Additionally, to enhance adherence and minimise movement during EEG recording, participants were provided with short breaks between task blocks. Participants were also provided with information on their progress through a “Zoo Map” prior to the task initiation and following task blocks. Breaks were provided to allow participants to rest and track their progress throughout the task (see Figure 1B). EEG data were recorded throughout the task using E-Prime software version 3.0 (E-Prime, 2020). The Zoo task script was adapted from Grammer et al. (2014), with minor adjustments made to accommodate EEG recording using the Biosemi ActiveTwo system used in this study. ———– Insert Figure 1 ———– 2.2.2 Adverse Childhood Experiences (ACEs) Participants completed the self-reported Youth and Childhood Adversity Scale (YCAS), developed by Schlechter et al. (2021). The scale includes 13 items that capture diverse domains of adversity during childhood and adolescence. These domains encompass loss and bereavement (e.g., death of a very close friend or family member), family disruption (e.g., major upheaval between parents, such as divorce or separation), traumatic sexual experiences (e.g., rape or molestation), and experiences of direct victimisation (e.g., being physically abused, mugged, or assaulted). It also includes witnessing violence toward close family members, serious personal illness or injury, and severe illness or injury of a parent, sibling, or significant other. Additional domains include parental or close family member mental illness, prolonged separation from a parent, long-term parental unemployment, severe substance abuse in the family, and criminal activities by family members that caused significant stress or worry. The final item allows participants to report any other major upheaval they believe significantly shaped their life or personality. Participants were instructed to reflect on and report any such experiences up until the point of their participation in the current study, with clear guidelines provided to ensure they understood the timeframe for recalling these adversities. The questionnaire employs a dichotomous response format (Yes/No), facilitating straightforward quantification of the frequency and types of adversities reported. The total score on the YCAS represents the cumulative burden of adverse experiences, which was used in subsequent analyses. The YCAS demonstrated good reliability and validity, with omega reliability values ranging from 0.80 to 0.89, and coefficient alpha ranged from 0.78 to 0.89, indicating strong internal consistency (Schlechter et al., 2021). In this study, Cronbach’s alpha was 0.69. 2.2.3 Internalising and Externalising Symptoms To assess both externalising and internalising symptoms, participants completed the Youth Self-Report (YSR; Achenbach, 1991). The YSR is a widely used, standardised self-report questionnaire designed to assess a range of emotional and behavioural issues in youths aged 11 to 18. Internalising symptoms were assessed through subscales of Anxious/Depression (10 items), Somatic Complaints (6 items), and Withdrawn (6 items). The Anxious/Depressed subscale includes items like “I am nervous or tense” and “I feel worthless or inferior.” The Somatic Complaints subscale evaluates physical symptoms often linked to emotional distress, such as “I have trouble sleeping” or “I feel sick often.” The Withdrawn subscale assesses emotional withdrawal and lack of interest in activities, with example items like “I don’t feel like doing anything” and “I am withdrawn.” For externalising symptoms, the YSR includes Aggressive Behaviour (13 items) and Rule-Breaking Behaviour (10 items) subscales. The Aggressive Behaviour subscale includes items such as “I get into fights,” “I argue a lot,” and “I scream a lot.” The Rule-Breaking Behaviour subscale measures violations of rules and social norms, with example questions like “I break the rules at home or school” and “I lie or cheat.” Participants rated the applicability of each behaviour using a 3-point Likert scale (0 = Not True, 1 = Sometimes True, 2 = Very True), reflecting their experiences over the past six months. Separate scores were generated for internalising and externalising behaviours. The YSR has shown excellent psychometric properties, including robust reliability and validity (Achenbach, 1991). The scale has shown test-retest reliability with correlations ranging from 0.80 to 0.90 over a period of several months (Achenbach, 1991). In this present study, Cronbach’s alpha was 0.90 for both internalising and externalising symptoms. 2.2.4 Pubertal Stage Pubertal stage was assessed using the Pubertal Developmental Scale (PDS; Petersen et al., 1988), a self-report measure designed to evaluate the physical signs of puberty. The PDS includes five items addressing physical and physiological changes associated with puberty. For example, females report on breast development and onset of menstruation, while males report on voice changes. Both sexes respond to questions about general physical growth, body hair development, and changes in skin condition. Adolescents are asked to rate their current developmental stage on a 4-point scale (1 = has not yet begun, to 4 = seems completed). For items specific to males or females, a response of “yes” for a question (e.g., menstruation onset) is scored as 4. Total scores are derived by adding up all relevant items. Higher scores reflect more advanced stages of pubertal development. These scores are then averaged to determine a mean pubertal developmental score. The PDS has demonstrated strong reliability and validity in assessing pubertal stage, with good internal consistency (𝛼 = 0.78 – 0.92) and test-retest reliability ( r = 0.75 – 0.95) across different age groups (Dorn & Biro, 2011; Petersen et al., 1988). In this current study, Cronbach’s alpha for females was 0.65, and for males, it was 0.76. 2.2.5 Benevolent Childhood Experiences To assess positive childhood experiences, participants completed the Benevolent Childhood Experiences (BCE) questionnaire (Narayan et al., 2018). The BCE questionnaire aims to evaluate the presence of supportive and nurturing experiences in childhood that can serve as protective factors against the harmful impacts of ACEs. The BCE comprises 10 items, each requiring participants to respond with a dichotomous choice (Yes/No), indicating whether they experienced specific positive interactions or supportive relationships during their childhood. The questionnaire covers various aspects of benevolent experiences, such as parental support, encouragement, and the presence of caring adults beyond the immediate family. Example items include: “Growing up, I had at least one caregiver with whom I felt safe,” “Growing up, I had a predictable home routine, like regular meals and a regular bedtime.” The total score derived from the BCEs provides a cumulative measure of positive childhood experiences. The BCE has shown strong psychometric properties, including good reliability (𝛼 = 0.78 – 0.82) and correlating positively with other measures of social support and mental health outcomes (Narayan et al., 2018). Cronbach’s alpha for the current study was 0.64. 2.2.6 Intelligence Quotient (IQ) To evaluate cognitive functioning, participants underwent the Wechsler Abbreviated Scale of Intelligence , Second Edition (WASI-II) (Wechsler (2018) assessment. The WASI-II is a standardised, brief intelligence test designed to measure general cognitive ability in individuals aged 6 to 90 years. The test comprises two primary components: the Verbal Comprehension Index and the Perceptual Reasoning Index. The Full-Scale Intelligence Quotient (FSIQ), or the estimate of participants’ overall intellectual functioning, was derived by combining T-scores from the two subtests, with a mean of 100 and a standard deviation of 15. 2.2.7 Socioeconomic Status (SES) For SES measurement, the adolescent perception of Family Financial Security (PFS; Hammon et al., 2021) was used. A single question was asked: “How much money does your family have?” Response categories include (1) “not enough to get by”, (2) “just enough to get by”, (3) “we only have to worry about money for fun or extras”, and (4) “we never have to worry about money”. 2.3 Procedure Prior to study participation, both a consent form (for parents/guardians) and an assent form (for the participant) were required. Upon arrival at the laboratory, the researcher explained the aims and procedures of the study, provided the information sheets, and answered any questions from the participants and/or their guardians. Consent and assent forms were then signed to confirm participation. The session began with participants completing self-report questionnaires via Qualtrics ( Qualtrics , 2024) on a laboratory computer: (1) Demographic Questionnaire: included items on biological sex, age, race/ethnicity, SES, and pubertal development. After completing these questionnaires, participants were given a 5-minute break before completing the WASI-II cognitive ability assessment. Following this, another 5-minute break was provided. Next, participants moved to the EEG room to complete the Go/No-go task, during which their brain activity was recorded. Participants were asked to relax and minimise body movement during the recording. After confirming that the EEG setup was functioning properly, participants performed the Go/No-go task. Following the EEG task, participants completed the self-report questionnaires via Qualtrics (2024): As a brief positive mood induction, participants were shown a series of six cute animal pictures on the computer screen after completing the questionnaires. This was conducted to help regulate participants’ emotional state and reduce any potential distress that may have arisen from answering sensitive questions. The entire laboratory session lasted approximately two hours. After finishing the study, participants were informed about the study’s purpose during the debriefing and were given a £20 Amazon voucher as compensation for their time. 2.4. EEG Data Recording and Pre-processing EEG data were continuously recorded during the Go/No-Go task using a 64-channel ActiveTwo BioSemi System (Biosemi, Amsterdam, the Netherlands). The 64 electrodes were positioned according to the 10/20 electrode placement system (Jurcak et al., 2007) and BioSemi’s standard cap layout (Biosemi, 2021). To ensure signal quality, a sampling rate of 2048 Hz was used to record EEG signals and electrode offset values were kept within a range of ± 25μV. EEG data processing was performed using EEGLAB v2024.0 and ERPLAB v10.11 toolboxes within MATLAB R2024a (Delorme & Makeig, 2004; Lopez-Calderon & Luck, 2014). As part of offline preprocessing, the data were down sampled to 512 Hz via the Biosemi Decimator software. To eliminate low-frequency drifts, an infinite impulse response (IIR) Butterworth filter was applied, with a half-amplitude cutoff range of 0.1 – 30 Hz and a slope of 12 dB per octave. Additionally, the Cleanline Toolbox (Mullen, 2012) was utilised to reduce 50 Hz line noise. Finally, a visual inspection was performed to detect and remove trials contaminated by eye blinks and movement-related artifacts. Channels displaying excessive noise or muscle-related artifacts, such as involuntary muscle contractions or deglutition, were identified through visual inspection and subsequently removed. The number of eliminated channels per participant ranged from 0 to 7, accounting for a maximum of 10% of all channels. On average, 1.84 channels were removed ( SD = 2.34). The average number of removed channels did not differ significantly between male ( M = 1.32, SD = 1.86) and female participants ( M = 2.25, SD = 2.61) across all participants, t (47.59) = -1.47, p = .074. After visual inspection, the data were first re-referenced using the average reference method, followed by independent component analysis (ICA). Next, to detect and remove components related to ocular artifacts, the ADJUST toolbox (Mognon et al., 2011) was used to identify and eliminate blinks, horizontal eye movements, and cardiac activity. Additionally, spherical spline interpolation was used to interpolate any channels that had been previously excluded (Perrin et al., 1989). 2.5 ERP Analysis Following the pre-processing steps, ERPs time-locked to responses were extracted from -400 to 800 ms for error trials (ERN) and correct trials (CRN) and averaged separately. Epochs displaying voltage deflection exceeding 100 μV were discarded, and the retained data segments were averaged to generate ERP waveforms (ERN, CRN) for statistical analysis. Consistent with prior research on adolescent data (e.g. Clayson et al., 2023) and based on visual examination of the grand average ERP waveforms, the ERN and CRN were quantified using mean amplitude measures. Baseline correction, which adjusts neural activity relative to a pre-response period to reduce variability, was applied from -400 to -200 ms, and amplitudes were computed at the midline electrode sites (Fz, FCz, Cz). Electrode sites selection was guided by prior research employing the Zoo Go/No-Go task with children and at-risk population (Bruce & Kim, 2022; Grammer et al., 2014; Loman et al., 2013), and further informed by visual inspection of the ERP waveforms within the current adolescent sample. These midline sites are also commonly used in ERN research due to their proximity to the anterior cingulate cortex, considered as the primary neural generator of the ERN (Gehring et al., 1993; Meyer et al., 2015; D. Olvet & Hajcak, 2008) The ERN mean amplitude was measured in error-response no-go trials by averaging activity within the 0 to 100 ms post-response window at the FCz electrode. The choice of this time window was guided by both visual inspection of peak ERN responses across participants and existing literature (e.g., Clayson et al., 2023; Kujawa et al., 2016; Suor et al., 2021). Additionally, FCz was selected as the primary electrode site for analysis based on preliminary findings indicating greater negativity for error trials at this location. The CRN was calculated using the same approach but applied to correct-response trials. Next, to isolate ERP activity specifically related to error processing, the ERN was statistically adjusted by regressing the ERN (as the outcome variable) onto the CRN amplitude (as the predictor variable), generating standardised ERN residual scores for further analysis (Meyer et al., 2017). Heightened error sensitivity is reflected in a more negative ERN residual score. This approach accounts for and removes overlapping variance between ERN and CRN, thereby minimising the influence of general cognitive processes unrelated to error processing, such as attentional control and response preparation (Meyer et al., 2017). 2.6 Behavioural Measures Behavioural data were collected by recording the number and percentage of correct and error trials, along with reaction times for each participant. Following the methodology of the original Zoo Go/No-go task study to examine error processing (Grammer et al., 2014), accuracy was assessed for both Go and No-go trials. Participants responded correctly in Go trials if they pressed the spacebar when any animal other than the orangutan appeared, while in No-Go trials, they were correct if they withheld their response when an orangutan was shown. In this study, the commission error rate—the percentage of error trials (i.e., instances where participants mistakenly pressed the spacebar in response to an orangutan)—was used as the primary index of inhibitory control performance. A higher commission error rate indicates weaker inhibitory control. Reaction times were also recorded independently for correct and error trials. To ensure the reliability of the ERP analysis, participants who had fewer than six error trials were excluded from the final dataset (n = 15). This exclusion criterion was implemented in accordance with the original task design outlined by Grammer et al. (2014) to maintain an adequate number of errors for analysis. No significant differences were observed based on age, sex, race, SES, IQ, pubertal stage, ACEs, commission error rate, internalising symptoms, and externalising symptoms between participants with sufficient error trials and those excluded due to insufficient errors (see Supplementary information 1). 2.7 Data Analysis Participants’ behavioural and ERP data were initially assessed for those with sufficient EEG data and an adequate number of error trials (n = 50). Prior to the main analysis, repeated measures ANOVAs were conducted in IBM SPSS Version 22.0 (IBM Corp, Armonk, NY) to examine all ERP components and identify which electrodes exhibited the most prominent signals for ERN in three electrodes (Fz, FCz, Cz, Figure 2 and Table 2). Response-locked waveforms were examined at Fz, FCz, and Cz. Among these locations, the ERN and CRN amplitudes were most pronounced at FCz, ( F (1, 49) = 26.47, p = <.001, η p 2 = 0.351), ( F (1, 49) = 50.481, p = <.001, η p 2 = 0.51), compared to Fz and Cz sites. This result indicates that the ERN was maximal at the FCz site, as suggested by Gehring et al. (2012). Therefore, the ERN and CRN mean amplitudes from the FCz site were used for further analysis (i.e., calculating the ERN residual). The use of residualised ERN scores allows for the isolation of variance specifically attributable to error processing by statistically controlling for activity during correct response (i.e., CRN). This approach reduces confounding influences of general response tendencies or shared noise across conditions and provides a more precise measure of error-specific neural processes (Meyer et al., 2017; D. M. Olvet & Hajcak, 2009). The ERN residuals were subsequently included in the analysis as the mediator variable of the association between ACEs and internalising/externalising symptoms in adolescents. ————- Insert Table 2 ————- ————- Insert Figure 2 ————- The analyses were conducted in two sequential steps. First, a mediation model was estimated to examine whether behavioural inhibition (measured by commission error rate, CER) and neural error monitoring (measured by ERN amplitude) mediated the association between ACEs and adolescent internalising and externalising symptoms. The hypothesised model specified ACEs as the exogenous (predictor) variables, CER and ERN amplitude as mediators, and internalising and externalising symptoms as outcome variables. Direct paths from ACEs to both outcomes were included to allow for the estimation of partial mediation. Covariates included age, sex, race, socioeconomic status (SES), and intelligence quotient (IQ), which were regressed onto all mediators and outcome variables to control potential confounding influences. In the second step, moderation analyses were added to the path model to test whether the relationships between ACEs, mediators (CER, ERN), and mental health symptoms varied as a function of individual characteristics, specifically BCE, pubertal development, and sex. Interaction terms were created between ACEs and each moderator, and between each mediator and the moderators, and included in the model accordingly. The model was estimated using the lavaan package in R version 4.2.3 (Rosseel, 2012). Maximum likelihood estimation with bootstrapped standard errors (5000 resamples) was used to obtain robust confidence intervals (95%) for indirect effects (Preacher & Hayes, 2008). Model fit was evaluated using multiple indices: chi-square statistics (χ²), root mean square error of approximation (RMSEA), comparative fit index (CFI), Tucker-Lewis’s index (TLI), and standardised root mean square residual (SRMR). Acceptable model fit was indicated by CFI and TLI values above 0.90, RMSEA below 0.08, and SRMR below 0.08 (Hu & Bentler, 1999). 2.8 Protocol Pre-registration This study was pre-registered on OSF (https://osf.io/8gxqk), and all data are available at https://osf.io/9643b/. A deviation from the pre-registration occurred regarding the ERP components analysed. Initially, the plan was to examine the ERP components of N2 and P3 as indices of inhibitory control. However, due to a stimulus event recording error, these components could not be extracted. As a result, the current study used the ERP component as an index of inhibitory control (i.e., the ERN) for analysis. 3. Results 3.1. Sample characteristics See Table 3 for sample means, standard deviations, score range, and the score differences between males and females for the measurement of ACEs, internalising and externalising behaviour measures, BCE, puberty stage, and IQ. On average, adolescents in the present sample reported exposure to approximately three types of ACEs. This level of exposure is broadly comparable to that reported in community-based adolescent samples in prior research, which typically show mean ACEs scores ranging from two to four adversities (e.g., Felitti et al., 1998; Hughes et al., 2017). The observed variability in ACEs scores further indicates a heterogeneous distribution of adversity exposure within the sample, ranging from no reported ACEs to moderately elevated exposure. Females reported significantly higher internalising symptoms than males, whereas no significant sex differences were observed in externalising symptoms. Benevolent Childhood Experiences (BCE) were generally high in this sample, suggesting that many participants reported frequent exposure to positive relational and environmental factors during childhood, with no significant differences between males and females. Pubertal development, as measured by the Pubertal Developmental Scales (PDS), shows more advanced pubertal status in females than males, consistent with expected sex differences in developmental timing. Finally, Full Scale IQ reflected a wide but generally normative distribution of cognitive functioning. ————- Insert Table 3 ————- 3.2. Behavioural Performance All participants engaged with and completed the inhibitory control task successfully. On average, participants responded correctly on 94.52% of trials. The mean commission error rate (i.e., failure to withhold responses on No-Go trials) was 19.55%, which is comparable to rates observed in prior Go/No-Go paradigms with youth samples (Van Royen et al., 2022). Response times were slower for correct trials than for error trials ( F (1, 49) = 221.03, p <.01; η p 2 = 0.819), and females reaction times were faster than males in both error and correct Go trials. However, task performance was the same in males and females and was not correlated with age (Supplementary Table 2). ————- Insert Table 4 ————- 3.2. Mediation Analyses Associations Between ACEs, Inhibitory Control, and Mental Health Symptoms A path analysis was conducted to determine whether ACEs predicted internalising and externalising symptoms via behavioural (commission error rate) and neural (ERN amplitude) markers of inhibitory control. Age, sex, race, SES, and IQ were included as covariates. Model fit indices indicated excellent model fit: χ²(1) = 0.91, p = .339; CFI = 1.00; TLI = 1.09; RMSEA = 0.00, 90% CI [0.00, 0.37]; SRMR = 0.02. As illustrated in Figure 3, mediation analyses first revealed a significant total effect of ACEs on internalising symptoms, such that higher levels of ACEs were associated with greater internalising symptomatology ( β = 0.33, p = .033, 95% CI [0.01, 0.63]). ACEs were also significantly associated with ERN amplitude, with higher ACEs exposure predicting larger (i.e., more negative) ERN responses ( β = -0.41, p = .023, 95% CI [-0.77, -0.08]). In turn, ERN amplitude significantly predicted internalising symptoms ( β = -0.33, p = .012, 95% CI [-0.61, -0.07]). However, despite these significant associations, the indirect effect of ACEs on internalising via ERN was not statistically significant ( β = 0.13, p = .129, 95% CI [0.006, 0.366]), indicating that the hypothesised mediation pathway was not supported. Similarly, as shown in Figure 3, behavioural inhibitory control (as measured by commission error rate) did not mediate the relationship between ACEs and internalising symptoms. The indirect effect of ACEs on internalising symptoms via commission errors was non-significant. The paths from ACEs to commission error rate ( β = -0.28, p = .187, 95% CI [-0.63, 0.17]) and from commission error rate to internalising symptoms ( β = -0.07, p = .600, 95% CI [-0.35, 0.19]) were non-significant, as was the overall indirect effect ( β = 0.22, p = .620, 95% CI [-0.06, 0.11]). With respect to externalising symptoms (see Figure 3), ACEs were not significantly associated with externalising symptoms ( β = 0.33, p = .082, 95% CI [-0.03, 0.71]). Consistent with the dashed paths shown in Figure 3, no significant mediation effects were observed. The indirect path from ACEs to externalising symptoms via ERN amplitude was non-significant ( β = -0.09, p = .211, 95% CI [-0.26, 0.03]), as was the indirect path via commission error rate ( β = -0.05, p = .430, 95% CI [-0.20, 0.05]). Furthermore, neither ERN amplitude ( β = 0.23, p = .117, 95% CI [-0.06, 0.52]) nor commission error rate ( β = 0.17, p = .330, 95% CI [-0.14, 0.55]) significantly predicted externalising symptoms. ————- Insert Figure 3 ————- 3.2.1. Covariates Sex was significantly associated with internalising symptoms ( β = 0.84, p = .003, 95% CI [-0.29, 1.40]), with females reporting higher internalising symptoms than males. The other covariates were not significantly associated with any of the variables. 3.2.2. Moderators There was no significant evidence that BCE, pubertal stage, or sex moderated the associations between ACEs and inhibitory control indices (commission error rate and ERN amplitude), nor did these variables moderate the associations between these inhibitory control measures and internalising or externalising symptoms (see the statistical report in Supplementary Information 3). 4. Discussion This study investigated the associations between ACEs, inhibitory control, as indexed by error processing (commission error rate as a behavioural performance measure and ERN amplitude as a neural correlate), and internalising and externalising symptoms in adolescents. 4.1. ACEs, Inhibitory Control, ERN, and Internalising Symptoms As predicted, the findings showed that ACEs were associated with both ERN amplitude and internalising symptoms: higher levels of adversity were linked to larger ERN amplitudes, and larger ERN amplitudes were associated with higher levels of self‑reported internalising symptoms. In contrast, behavioural inhibitory control performance, indexed by commission error rate, was not significantly associated with ACEs or internalising symptoms and therefore did not serve as an indirect pathway in the present analysis. Despite the observed associations between ACEs, ERN amplitude, and internalising symptoms, the hypothesised indirect effect, where ERN amplitude would mediate the ACE–internalising relationship, was not supported. Given the modest sample size, it is possible that statistical power was insufficient to detect subtle mediation effects, a recognised challenge in developmental and psychological research (Fritz & MacKinnon, 2007). Another possibility is that the lack of mediation reflects the multifaceted nature of the pathways linking ACEs to the development of internalising symptoms. Although, alterations in ERN amplitudes are often interpreted as indicators of difficulties in error monitoring and self-regulation (Checa et al., 2014; Lackner et al., 2018; D. Olvet & Hajcak, 2008), this neural marker captures only one aspect of the broader emotional and cognitive dysregulation associated with early adversity. ACEs have been shown to contribute to maladaptive cognitive patterns, such as rumination and negative self-evaluation, which could independently contribute to the development of internalising symptoms, including anxiety and depression (Gruzman et al., 2024; Peters et al., 2019; Sokołowski et al., 2022). These processes may not be well indexed by ERN amplitude, suggesting that other neural mechanisms, particularly those involving regions central to emotion regulation (e.g., prefrontal cortex), could play a more substantial mediating role in the ACE–internalising relationship. Another important consideration is that the ERN may not fully capture the diversity of neural responses to stress and cognitive control demands. Recent evidence indicates that, beyond the ERN, the event related potentials, P3 (attentional updating) and Pe (conscious error evaluation) add explanatory power for how individuals monitor, appraise, and adapt to errors under stress, with Pe increasing with chronic stress and P3 reductions associated with internalising and transdiagnostic psychopathology (e.g. Schrijvers et al., 2010; Wu et al., 2014, 2019). Taken together, these findings suggest that multiple electrophysiological pathways may be relevant, even when mediation via ERN alone does not emerge. In this broader context, the simple associations observed in the present study reinforce several key relationships. In particular, ACEs significantly predicted internalising symptoms in adolescents. Consistent with the extensive literature documenting heightened vulnerability to adverse mental health outcomes following early adversity. For example, ACEs can disrupt normative developmental processes and increase risk for internalising symptoms (Bevilacqua et al., 2021; Muniz et al., 2019), including post-traumatic stress symptoms, anxiety, depression, suicide tendencies, and substance abuse (Giampetruzzi et al., 2024; Goodday et al., 2019; Hicks et al., 2021; Nelson et al., 2021). This underscores the need for targeted interventions and prevention strategies tailored to mitigate the impact of early adversity. This study also demonstrated that ACEs significantly predicted the amplitude of the ERN, a neural marker of inhibitory control, specifically error processing. The sizeable effect size suggests robust links, indicating that greater adversity exposure is associated with a more negative (larger) ERN amplitude, reflecting heightened error-related neural activity. The relatively strong effect found underscores the potential significance of adversity in shaping error processing during adolescence. This finding aligns with and extends previous research that shows that ACEs are associated with altered neural responses to errors, particularly in the form of heightened ERN, which is often interpreted as an index of increased sensitivity to errors. For example, studies reported that harsh parenting, childhood trauma, and exposure to adversity are linked to amplified ERN in youth (e.g., Chong et al., 2020; Lackner et al., 2018; Meyer et al., 2015). Elevated ERN in adolescents with higher ACEs further supports the notion that early adversity may sensitise individuals to error-detection processes (Riesel et al., 2019). Yet, our findings contrast with previous research suggesting that ACEs are associated with a blunted or attenuated ERN response, not increased as found in the current study, particularly among individuals exposed to deprivation (e.g., Letkiewicz et al., 2023; Loman et al., 2013; Troller‐Renfree et al., 2016). Early trauma or chronic stress has been proposed to reduce neural sensitivity to errors, possibly reflecting an adaptive coping mechanism in response to overwhelming or unpredictable environments (Kaufman et al., 2000; Meyer, 2017). Specifically, individuals with ACEs may show diminished error-processing abilities as a result of emotional numbing or disengagement from stressful stimuli, potentially as a means of avoiding further distress (Dvir et al., 2014; Fani et al., 2012; Mueller et al., 2010). The current finding of a heightened ERN, therefore, presents an interesting divergence, suggesting that ACEs may, in some cases, heighten rather than dampen sensitivity to errors. Methodological or developmental differences may help explain these discrepancies. For instance, this study focused on adolescents, whereas prior research has often examined younger children (Troller‐Renfree et al., 2016) or adult (Letkiewicz et al., 2023) populations, in which the neural and psychological impacts of ACEs may manifest differently. Moreover, the type, timing, and duration of ACEs likely contribute to variability in ERN responses. For example, in a large adult sample, greater exposure to childhood emotional neglect and sexual abuse each uniquely predicted blunted ERN amplitude, even after controlling for other trauma types (Letkiewicz et al., 2023). Taken together, these findings highlight that the specific factors underlying variations in ERN amplitude among individuals with a history of ACEs remain poorly understood. At present, it is unclear what mechanisms lead to reduced versus increased ERN amplitudes, or what the functional implications of these patterns may be. Such differences may reflect alterations in neural systems supporting error monitoring, potentially differentially influenced by prolonged stress exposure or dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis (Gunnar & Quevedo, 2007; McLaughlin & Lambert, 2017). Future research should aim to disentangle these complex relationships, examining how developmental stage, adversity type, and stress physiology interact to shape error-processing trajectories across adolescence A second key finding was that ERN amplitude significantly predicted internalising symptoms, indicating that heightened neural sensitivity to errors is associated with higher levels of internal emotional distress. Specifically, adolescents with more negative ERN amplitudes reported elevated internalising symptoms. Although this association is consistent with models proposing that heightened error-monitoring processes contribute to the development or maintenance of internalising psychopathology, the correlational nature of the data precludes causal inferences. It is also possible that internalising symptoms heighten error monitoring, or that shared underlying factors, such as heightened trait anxiety or negative affectivity, contribute to both increased ERN amplitudes and internalising symptoms. Nonetheless, the observed association aligns with prior research showing that heightened ERN amplitudes are characteristic of anxiety and related internalising disorders (e.g. Meyer, 2017; Riesel et al., 2019), potentially reflecting increased error sensitivity and enhanced self-monitoring during performance evaluation. In support of this idea, research suggests that maladaptive emotional regulation strategies, including increased self-criticism and struggles with error management, play a key role in the development of anxiety and depression in adolescents. For instance, emotional dysregulation has been consistently associated with heightened vulnerability to internalising disorders, particularly in response to setbacks or mistakes (Klinge et al., 2023). The ERN, a neural marker of error processing, is thought to reflect difficulties in this area, as alterations in ERN responses have been linked to difficulties in coping with errors and increased self-critical thoughts (Holroyd & Coles, 2002; D. Olvet & Hajcak, 2008). This evidence aligns with prior research highlighting the role of cognitive biases, such as rumination and negative self-reflection, in the development and progression of internalising disorders (e.g., Nolen-Hoeksema, 2000). Lastly, despite evidence linking ERN to ACEs and internalising symptoms, this study did not find a significant association between commission error rate, a behavioural measure of inhibitory control, and either ACEs or internalising symptoms. One possible explanation is that neural and behavioural assessments of inhibitory control may reflect distinct underlying cognitive processes. Notably, ERN amplitude was not significantly correlated with commission error rates in this sample, suggesting that these two indicators may reflect distinct aspects of inhibitory control. While commission errors provide a behavioural measure of response inhibition, ERN represents a neural index of error monitoring processes, which may involve more subtle, internal cognitive evaluations or adaptive processes that do not necessarily manifest in overt behaviour. Supporting this dissociation, prior research has shown that neural and behavioural indices of inhibitory control are only modestly related and may engage partially separate cognitive domains (Hoffmann et al., 2014; Iannaccone et al., 2015), indicating that neural measures may identify cognitive variations that behavioural tasks cannot reveal. The relationship between ACEs and internalising symptoms may be driven more by heightened self-monitoring, error-related anxiety, or increased worry about errors, rather than by actual deficits in impulse control. This could explain why neural measures, such as ERN, are associated with ACEs and internalising symptoms, whereas behavioural measures are not. Future research could examine whether neural hyperactivity in error monitoring regions, such as the anterior cingulate cortex (ACC) (Hoffmann et al., 2014; Iannaccone et al., 2015), contributes specifically to excessive worry and rumination, which are hallmark features of internalising disorders (Taylor & Snyder, 2021). Such investigations may offer valuable insights into the distinct cognitive and emotional pathways linking ACEs exposure to mental health symptoms. Another potential explanation for these null behavioural findings might relate to task-specific factors, particularly the inhibitory control task’s level of difficulty or cognitive demand relative to the adolescent age group studied. If the task was insufficiently challenging, it may have lacked sensitivity to detect meaningful differences in inhibitory control associated with ACEs. 4.2 ACEs, Response Inhibition, ERN, and Externalising Symptoms No significant associations were found between ACEs, externalising symptoms and response inhibition, as indexed by both behavioural commission error rate and ERN, in this adolescent sample. Although it was hypothesised that a blunted ERN might mediate the link between ACEs and externalising symptoms, the data did not support this pattern. This null finding may reflect broader complexity in interpreting the ERN across different dimensions of psychopathology. Whereas enhanced ERN amplitudes are observed in internalising disorders, often interpreted as heightened threat sensitivity and error monitoring (Meyer et al., 2012; Moser et al., 2012), evidence linking reduced ERN to externalising symptoms is more inconsistent. Findings in this area vary considerably as a function of developmental age, sample characteristics, and task demands, making ERN-externalising associations less robust and more heterogenous (Buzzell et al., 2020; D. Olvet & Hajcak, 2008). A related explanation concerns the distinct motivational and regulatory systems that characterise internalising versus externalising symptomology. Internalising symptoms have often been linked to heightened sensitivity to errors and hyperactivation of performance monitoring networks, whereas externalising behaviours are more commonly associated with reduced sensitivity to negative feedback, disengagement from performance monitoring, and diminished responsivity to punishment cues (Hall et al., 2007; Meyer et al., 2012). However, these patterns are not necessarily mutually exclusive or linearly inverse within individuals. Adolescents may show features of both profiles simultaneously, for example, heightened emotional reactivity in some contexts but reduced behavioural monitoring in others, which may contribute to the inconsistent associations between ERN amplitude and externalising behaviours observed across studies. Indeed, internalising and externalising symptoms are well documented to be moderately correlated and are increasingly understood as reflecting a shared underlying vulnerability to psychopathology (Caspi & Moffitt, 2018). This overlap may be particularly pronounced during adolescence, a developmental period characterised by substantial heterogeneity in self-regulation and emotion processing (Casey et al., 2008), especially within non-clinical or mixed-symptom samples. Factors such as comorbidity and task demands could moderate ERN-expression patterns, potentially obscuring clear group-level associations. Another possibility is that the lack of an association between ACEs and externalising symptoms may reflect the nature or timing of adversity experienced by participants. Some types of adversity (e.g., deprivation or neglect) may exert stronger effects on socioemotional processing and internalising pathways, while other forms (e.g., threat-based ACEs like physical abuse) may be more strongly linked to behavioural dysregulation and externalising outcomes (Lambert et al., 2017; McLaughlin et al., 2014). It is possible that in the current sample, the specific types or combinations of ACEs may have exerted a more salient impact on neural systems underlying internalising symptoms, such as error monitoring, than those implicated in impulsivity or behavioural control. However, this interpretation is speculative and should be tested in future research that directly examines the dimensions of adversity experiences (e.g., threat vs. deprivation) and their neural correlates. Moreover, externalising symptoms may also be more closely linked to other neurocognitive systems, such as those involved in reward processing or delay aversion, than to error detection per se. For instance, blunted reward anticipation and altered ventral striatal responses have been more reliably implicated in externalising pathways (e.g., Luking et al., 2016) suggesting that future studies could benefit from a broader examination of motivational and regulatory systems beyond the ERN. It is essential to consider participants’ age and developmental stage when interpreting the findings of this study. Adolescence is critical period for the maturation of cognitive and emotional systems, including neural mechanisms underlying error detection and response control (Luna et al., 2015). The age range of the current sample (14-17 years) may have influenced the results, as evidence suggests that associations between ACEs, ERN, and externalising behaviours are more pronounced during earlier developmental stages, particularly late childhood to early adolescence (approximately 10-13 years; Meyer et al., 2012; Torpey et al., 2012). During this period, the ACC and associated error monitoring networks undergo rapid development, potentially heightening sensitivity to the effects of early life-stress. By mid- to late adolescence, these systems begin to stabilise, which may attenuate the observable impact of ACEs on error processing and behavioural regulation. Consequently, the developmental stage of the present sample may not have represented the most sensitive window for ACE-ERN-externalising associations. Additionally, the limited variability in externalising symptoms in the current sample could have influenced the lack of significant findings. As the participants did not exhibit a wide range of externalising behaviours, there was reduced opportunity to detect relationships with error processing. 4.3 Study Limitations While this study offers valuable insights, several limitations should be acknowledged. First, although an a priori power analysis determined that n = 65 would be sufficient to detect small effect sizes (f 2 = 0.02), the final sample included only 50 participants due to recruitment and data quality constraints. This reduced sample size may have limited the ability to detect small or indirect effects, particularly in the mediation models, which are known to require larger samples for adequate statistical power (Fritz & MacKinnon, 2007). Second, the cross-sectional design precludes any conclusion about temporal ordering between ACEs, inhibitory control and internalising and externalising symptoms. Without longitudinal assessments, it remains uncertain whether the ERN amplitude observed in adolescents exposed to ACEs represents a consequence of early adversity or reflects pre-existing neurocognitive vulnerabilities. Third, this current study did not examine potential moderators or mediators that could influence the pathways from ACEs to psychological outcomes. For instance, unmeasured processes such as emotion regulation strategies, cognitive biases (e.g., rumination or negative self-evaluation), and stress physiology (e.g., cortisol levels, autonomic reactivity) may offer additional explanatory power regarding how ACEs influence psychological symptoms (Gruzman et al., 2024; Peters et al., 2019; Sokołowski et al., 2022). Future research should prioritise larger, more diverse samples, incorporate longitudinal designs, and examine the influence of adversity subtypes and severity, and additional cognitive and emotional mechanisms. These steps will help to clarify the complex pathways linking ACEs and adolescent mental health. 5. Conclusion This study provides novel evidence that adolescents with a history of ACEs show heightened ERN amplitudes alongside elevated internalising symptoms, suggesting that early adversity may shape neural systems involved in error monitoring. Although ERN amplitude was independently associated with internalising symptoms, it did not account for the relation between ACEs and these outcomes, and behavioural indices of inhibitory control showed no significant associations. Together, these findings highlight the multifaceted pathways linking early adversity to adolescent mental health and emphasise the potential value of neural markers, such as the ERN, in capturing aspects of risk that may not be observable through behavioural performance alone. 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Authors Affiliations Satwika Rahapsari Universitas Gadjah Mada View all articles by this author Kubra Ulusoy 0009-0006-0649-0321 Hacettepe Universitesi Biyoloji Bolumu View all articles by this author Richard Rowe The University of Sheffield View all articles by this author Myles Jones The University of Sheffield View all articles by this author Liat Levita 0000-0001-6002-6817 [email protected] University of Sussex View all articles by this author Metrics & Citations Metrics Article Usage 191 views 66 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Satwika Rahapsari, Kubra Ulusoy, Richard Rowe, et al. Neural correlates of error processing: Linking adverse childhood experience to adolescent inhibitory control and internalising and externalising symptoms. Authorea . 27 January 2026. 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