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. Author manuscript; available in PMC: 2026 Jan 17.
Published in final edited form as: Child Neuropsychol. 2025 Jan 17;31(6):850–870. doi: 10.1080/09297049.2025.2451799

Adverse Childhood Experiences and Post-Traumatic Stress Impacts on Brain Connectivity and Alcohol Use in Adolescence

Mary Milo O Woodley 1, Qingyu Zhao 2, David B Goldston 3, Andrew M Michael 4, Duncan B Clark 5, Sandra A Brown 6,7, Kate B Nooner 1,3
PMCID: PMC12272169  NIHMSID: NIHMS2047628  PMID: 39819312

Abstract

The current study investigated the relationship between adverse childhood experiences (ACEs), post-traumatic stress disorder (PTSD) symptoms, within-network resting-state functional connectivity (rs-FC), and alcohol use during adolescence using functional magnetic resonance imaging (fMRI) data from the National Consortium on Alcohol and Neurodevelopment in Adolescence study (NCANDA; N = 687). Significant rs-FC differences emerged that linked participant ACEs, PTSD symptoms, and alcohol use problems. Participants with ACEs compared to those without had diminished rs-FC within the default mode, salience, and medial frontoparietal networks (p ≤ 0.005). Further reduction in rs-FC within the default mode and medial frontoparietal networks (p ≤ 0.005) was found when PTSD symptoms were present in addition to ACEs. Findings suggest that PTSD symptoms are associated with lower within-network rs-FC beyond exposure to ACEs, and some of these rs-FC changes were associated with worsened alcohol use problems (i.e., withdrawal symptoms). These findings highlight the importance of addressing PTSD symptoms in adolescents with a history of ACEs as it may mitigate problematic changes in brain connectivity and reduce the risk of developing alcohol use problems.

Keywords: Adverse childhood experiences, Post-traumatic stress disorder, Alcohol use, fMRI, Adolescence

Adverse childhood experiences (ACEs) are negative experiences that occur before age 18 and are typically characterized by abuse, neglect, and household challenges, but also include experiences like bullying and community violence (Centers for Disease Control and Prevention, 2022; Felitti et al., 1998). ACEs are common, with U.S. surveys indicating that, between 2011 and 2019, approximately 2/3 of adults reported at least one ACE, and 1/6 of adults reported four or more ACEs in their lifetime (Swedo et al., 2023). These rates likely underrepresent the actual prevalence of ACEs in the U.S. due to underreporting and measurement limitations (Swedo et al., 2023). ACEs are an important area of study, as they are linked to a greater likelihood of physical and mental health problems, increased health risk behaviors, and limited life opportunities (Merrick et al., 2019, Metzler et al., 2017).

Post-traumatic stress disorder (PTSD) is a mental disorder that can develop following traumatic events including actual and perceived threat exposures (National Institute of Mental Health, 2019). Given that traumatic events may contribute to distressing symptoms, it is not surprising that adolescents with a history of ACEs have a higher prevalence rate of PTSD diagnosis (McLaughlin et al., 2013) as well as PTSD symptoms (Clark et al., 2010; Tabb et al., 2022). In addition, adults with greater cumulative ACE history are also more likely to endorse PTSD symptoms following trauma (Tabb et al., 2022), even after accounting for adult trauma history (Frewen et al., 2019). Since PTSD symptoms following ACEs can persist into adulthood, it is plausible that there may be brain changes at the intersection of ACEs and PTSD symptoms during adolescence that may confer lifelong vulnerability.

ACEs and PTSD symptoms have been independently linked to alcohol use outcomes including initiating use, and higher consumption quantities (Dube et al., 2006; Loudermilk et al., 2018). Furthermore, PTSD diagnosis significantly increases the likelihood of developing risky alcohol use behaviors following ACEs, including high levels of binge drinking (Jung et al., 2020). The current study leverages data from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA), a longitudinal, multi-site study that follows adolescents into adulthood (Brown et al., 2015). A primary aim of NCANDA is to identify brain functional and affective markers that may predict substance use and related psychopathology (Brown et al., 2015). Among the NCANDA sample, PTSD symptoms following ACEs (compared to a lack thereof) have been linked to increased drinking in follow-up years (De Bellis et al., 2020). While the mechanisms underlying these relationships are unclear, ACEs and PTSD symptoms have both been linked with cognitive and functional brain changes that could contribute to increased vulnerability to alcohol-related behaviors and problems (Silveira et al., 2020). In the present study, we explore the influence of ACEs and PTSD symptoms on the adolescent brain and explore potential brain changes that may increase the risk for alcohol-related outcomes (i.e., alcohol use onset, consumption, and related problems).

ACEs, PTSD Symptoms, and Functional Networks

The default mode network (DMN), central executive network (CEN), and salience network (SN) are functional brain networks that make up the triple network model. The triple network model suggests that these three networks are interconnected and thus contribute to a wide range of functional consequences when impacted (Menon, 2019). The default mode network (DMN) is involved in functions related to internally oriented processes, future-oriented thought, and memory (Raichle, 2015, Menon, 2019). The central executive network (CEN), sometimes referred to interchangeably with the frontoparietal network (FPN), is involved in externally oriented processes such as cognitive control, working memory, attention, and decision-making (Menon, 2019; Zhao et al., 2021a). The salience network (SN) is involved in facilitating “network switching” (e.g., DMN to CEN) to allocate appropriate cognitive resources in response to the external environment. The SN supports goal-directed behaviors, focusing on emotion and reward functions (Goulden et al., 2014, Menon, 2019). Alternations in the functioning of the triple network model have been linked to the development of mental health symptoms, including the endorsement of ACEs (Rakesh et al., 2021), PTSD symptoms (Weng et al., 2019), and alcohol use (Jacobson et al., 2023).

ACEs have been linked to reductions in resting-state functional connectivity (rs-FC) within the DMN (Akiki et al., 2018; Bluhm et al., 2009; Philip et al., 2013), SN (Zhao et al., 2021a, Mishra et al., 2020), and CEN (Zhao et al., 2021a). Diminished DMN rs-FC related to ACEs has been found among adult samples (Lu et al., 2017) as well as among samples of young children (Park et al., 2018), suggesting that brain changes may begin at the onset of ACE exposure, including in the medial prefrontal cortex and superior temporal gyrus. While reductions in the SN have been related to ACEs, some findings suggest that this relationship may depend on the presence of abuse or neglect, with neglect being associated with reductions in connectivity (Fadel et al., 2021). Nonetheless, these changes in rs-FC are expected to contribute to SN functioning related to the detection, processing, and response to negative or other salient stimuli (Zhao et al., 2021a). Within the CEN, there have been mixed findings regarding the influence of ACEs on rs-FC. Researchers in a sample of older children found that reported lifetime ACE count was associated with higher frontoparietal connectivity at baseline (Albertina et al., 2022). Notably, this study did not track changes in functional connectivity over time and may not reflect the developmental impacts of ACEs between follow-up years. Although there is some evidence of regions showing increased rs-FC within these networks as it relates to ACEs (e.g., Lu et al., 2017), consideration of whole network function suggests that ACEs relate broadly to reductions in rs-FC within the DMN, SN, and CEN (Rakesh et al., 2021).

PTSD diagnosis and severity are also related to alterations in the triple network model. Individuals with PTSD have shown diminished DMN rs-FC, specifically in regions including the medial prefrontal cortex, posterior cingulate cortex/precuneus, temporal gyrus, hippocampus, amygdala, etc. (Akiki et al., 2018; Bluhm et al., 2009, Zhou et al., 2012). Moreover, work assessing the relationship between PTSD and SN rs-FC has found that severity of PTSD symptoms has been associated with decreased connectivity within SN regions, such as the insula and temporal gyrus (Sheynin et al., 2020; Tursich et al., 2015). Although research investigating the relationship between PTSD symptoms to CEN function is limited, findings generally point to a decrease in CEN functioning associated with PTSD symptom presence and severity at rest and during tasks, which may be reflective of a more generalized impairment in functioning (Akiki et al., 2017; Cisler et al., 2013; Holmes et al., 2018; Koch et al., 2016). Some of the prior findings suggest that PTSD symptom influences on within-network rs-FC may differ based on PTSD symptom presentations (e.g., hyperarousal versus depersonalization/derealization symptoms (Lanius et al., 2010; Nicholson et al., 2020; Tursich et al., 2015). Nonetheless, several studies have found a pattern of diminished of connectivity within the three networks, including when assessed in combination with ACE history (Bluhm et al., 2009). The aberrant connectivity found within these three networks (i.e., DMN, SN, CEN) may offer some explanation to commonly observed behavioral changes associated with PTSD including worsened emotion dysregulation, memory, inhibitory control, and cognitive functioning.

Alcohol Use & Functional Networks

Changes in rs-FC in networks involved in the triple network model (DMN, SN, and CEN) are also related to the presence and severity of alcohol use. Prior work using the NCANDA sample found that less functional activity within regions of the DMN, including the precuneus, posterior cingulate, caudal anterior cingulate, and middle and superior temporal regions predicted initiation of heavy alcohol use from early adolescence to age 18 (Squeglia et al. 2017). Furthermore, diminished DMN rs-FC has been associated with increased severity of alcohol use disorder among adults (Gerhardt et al., 2022). Recent meta-analytic findings indicated that the presence of a substance use disorder was associated with decreased resting-state functional connectivity within key regions of the salience network (i.e., the bilateral anterior cingulate cortex and medial prefrontal cortex; Yan et al., 2023). Greater ACE severity in the NCANDA sample was also related to poorer executive functioning and changes in rs-FC of the SN, which in turn predicted higher-risk drinking among adolescents (Silveira et al., 2020). Among other samples decreased rs-FC within the CEN has also been found to relate to increased binge drinking behaviors among emerging adults (Lesnewich et al., 2022). Thus, problematic alcohol use during adolescence may be, in part, explained by brain changes associated with early adverse experiences.

Current Study

The current study investigated ACEs and PTSD symptom influence on the adolescent brain using data from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA). We assessed how ACEs, including when coupled with PTSD symptoms, contribute to differences in rs-FC within networks and associated brain regions. Our study expanded on prior research using a large, nationally representative sample of adolescents followed into adulthood. Further, we investigated whether differences in rs-FC relate to the severity of ACEs (overall and by abuse and neglect type), PTSD symptoms, and alcohol use onset, consumption, and related problems. We predicted that participants with ACEs and PTSD symptoms would show significantly diminished within-network rs-FC of the DMN, SN, and CEN compared to those without, with a graded effect, such that those with both ACEs and PTSD symptoms would show the largest rs-FC differences followed by those with ACES and no PTSD symptoms. To explore this hypothesis, in the first model, we assessed the impact of ACEs. In our next model, we assessed the impact of ACEs and PTSD symptoms in combination. We also tested whether within network rs-FC differences that emerged related to ACE and PTSD symptom severity. Last, to examine the impacts of these experiences on behavioral outcomes, we hypothesized that significant rs-FC differences would relate to alcohol use outcomes.

Method

Participants

The NCANDA study is a longitudinal multi-site study that is sponsored by the National Institute on Alcohol Abuse and Alcoholism, the National Institute of Mental Health, the National Institute on Drug Abuse, and the National Institute on Child Health and Human Development (Brown et al., 2015). NCANDA includes 831 individuals (age range: 12.0–21.9 years) followed annually.

Data collection occurs across five research sites: Duke University, University of Pittsburgh, Oregon Health & Science University (OHSU), University of California, San Diego (UCSD), and SRI International (SRI; Brown et al., 2015). Each site received site-specific Institutional Review Board approval for the study and collected convenience samples representative of their respective counties (Brown et al., 2015). Exclusion criteria included potential factors that could impede upon NCANDA study aims, acquiring complete testing protocols, and maintaining participant retention (e.g., MRI contraindications, residence, English fluency, current or persistent Axis I psychiatric disorders such as psychosis or substance dependence, etc.). The full NCANDA sample baseline demographics are reported in previous studies (Brown et al., 2015). Parental consent and youth assent were collected, and participants received compensation for participation (Brown et al., 2015).

Inclusion criteria for this analysis included complete demographic data, ACEs and PTSD symptom measures, and at least one functional magnetic resonance imaging (fMRI) scan. We analyzed multiple annual visits for 687 NCANDA participants (357 females, 330 males, μage = 16.21 years at baseline, SDage = 2.39, age range: 12.0–21.9 years at baseline, 1–7 annual visits). Of the 687 participants, 65 reported neither ACEs nor PTSD symptoms, and 622 (91%) endorsed at least one ACE. Of those who endorsed an ACE, 130 (20.9%) endorsed at least one PTSD symptom while the remaining 492 (79.1%) denied PTSD symptoms. Due to significantly older age among those with ACEs and PTSD symptoms (p < 0.05), we removed the oldest participants who met the criteria for both (n = 22) to match ACE and PTSD categories by age and sex. Table 1 includes demographic data for age, sex, and racial identity by ACE and PTSD symptom endorsement. The data were part of the public data release NCANDA_PUBLIC_7Y_COVID_REDCAP_V03 (Pohl et al., 2023a, 2023b), distributed according to the NCANDA Data Distribution agreement (https://www.niaaa.nih.gov/ncanda-data-distribution-agreement). This work is supported by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) funding AA021697, AA021695, AA021692, AA021696, AA021681, AA021690, and AA021691, AA028840.

Table 1.

Demographic & Measure Characteristics by ACE & PTSD presence (N = 687)

Characteristic No ACE/No PTSD Sx
N = 65, 9.46%		 ACEs/No PTSD Sx
N = 492, 71.62%		 ACEs/PTSD Sx
N = 130, 18.92%
Mean (SD) Mean (SD) Mean (SD)
Age (years) 16.14 (2.27) 16.14 (2.52) 16.52 (1.89)
Sex (male/female) 31/34 243/249 56/74
Race (n)
  White 52 360 85
  Black 2 55 23
  Asian 4 40 6
  Other 7 36 16
CTQ Scores
  Emotional Abuse 5.46 (0.70) 7.75 (3.49) 9.53 (4.45)
  Physical Abuse 5.17 (0.45) 6.70 (2.46) 7.77 (3.34)
  Sexual Abuse 5.00 (0.00) 5.54 (2.05) 6.58 (3.99)
  Emotional Neglect 5.89 (1.21) 10.60 (4.59) 12.14 (5.18)
  Physical Neglect 5.34 (0.68) 7.77 (2.84) 8.42 (3.10)
  Total 26.77 (2.03) 36.78 (10/16) 40.62 (15.45)
ACE-IQ Total 0.00 (0.00) 3.28 (2.20) 4.36 (2.64)
PTSD Total 0.00 (0.00) 0.00 (0.00) 6.89 (4.98)
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Note. CTQ = Childhood Trauma Questionnaire, ACE-IQ = Adverse Childhood Experiences (ACE) International Questionnaire, PTSD Sx = post-traumatic stress disorder symptoms (maximum).

Procedure

The full NCANDA battery includes a comprehensive clinical interview, self-report measures, MRI scans, neuropsychological testing, etc. (Brown et al., 2015). The current study used measures collected during annual visits including fMRI scans clinical interviews, and self-report measures. Clinical interview and self-report data were available up to year 7 (age range: 19.1–29.0); fMRI scans were processed up to year 6 (i.e., 1–7 scans; age range: 17.9–28.2) at the time of data analysis.

Functional MRI Acquisition and Processing

Resting-state functional MRI consisted of a 10-minute scan during which participants were instructed to keep their eyes open and minimize head movement. Sites used the 3T GE Discovery MR750 or 3T Siemens TIM TRIO scanners and followed the same acquisition protocol (Brown et al., 2015; Müller-Oehring et al. 2018, Zhao et al., 2019). Each scan was processed by the public NCANDA pipeline (Müller-Oehring et al. 2018), including motion correction, outlier frame detection, physiological noise removal, and spatial and temporal filtering. Then, a dual-regression group-level independent component analysis identified twenty-three intrinsic functional networks from each scan (Zhao et al., 2019, Zhao et al., 2021b), with each network represented by a voxel-wise spatial map encoding within-network rs-FC. We investigated the DMN, SN, and CEN due to their cross-network interaction and related functions (Figure 1). We computed the average rs-FC at each voxel for each network based on all available scans for each participant up from baseline to follow-up year 6. Group-level functional network averages for the networks of interest (DMN, SN, and CEN) were compared based on ACE and PTSD symptom presence (See Supplementary Figures 1, 2, and 3). For the 646 participants who had at least two scans across the 7 years, we also computed the slope of rs-FC at each voxel to quantify the direction of change over time for rs-FC. This approach created a robust estimate of average and slope rs-FC for each network which was optimal to compare with ACE and PTSD measures given limited timing data.

Figure 1.

Figure 1

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Functional Networks

Note. The group-level functional networks overlaid with SRI24 atlas (Rohlfing et al., 2010). Regions with high connectivity (Z-scores ≥ 3) are visualized in yellow.

Measures

Demographics

Participant demographics included baseline age, sex, race, and socioeconomic status (SES) characterized by parent-reported years of education and drinking threshold. The drinking threshold was determined using alcohol and drug use guidelines from the NIAAA and the National Survey on Drug Use and Mental Health (Brown et al., 2015; NIAAA, 2011; Substance Abuse and Mental Health Services Administration, 2012). Recommended cutoffs varied by age for lifetime drinking days, maximum drinks on one occasion, and lifetime drug use days (i.e., cigarettes, marijuana, and “other”). For example, 12-year-old participants could not exceed five lifetime days of drinking, more than three drinks on one occasion, or exceed other substance use cutoffs (Brown et al., 2015).

ACEs & PTSD Symptoms

ACEs were assessed using the Adverse Childhood Experiences International Questionnaire (ACE-IQ) and Childhood Trauma Questionnaire- Short Form (CTQ-SF). Binomial scores from the ACE-IQ and cut-off scores from the CTQ-SF were used to determine the presence of ACEs for the primary analyses.

The ACE-IQ measures child abuse and neglect, household challenges, and peer and community violence (Felitti et al., 1998; World Health Organization [WHO], 2019). This questionnaire has established psychometric soundness, including convergent and predictive validity (Ford et al., 2014; Kidman et al., 2019). We applied WHO recommendations for ACE-IQ (2019) binomial scoring using the highest score ever reported. Higher scores indicated more ACE types endorsed, and ACE count was used in exploratory analyses. Participants completed the ACE-IQ once during follow-up years 4–7.

The CTQ-SF is a 28-item self-administered questionnaire that measures exposure to childhood abuse and neglect (Bernstein et al., 2003). The CTQ-SF has established test-retest reliability, internal consistency, and convergent validity (Bernstein et al., 2003; Hagborg et al., 2022). Participants responded to items using a 5-point scale (1 = Never True, 2 = Rarely True, 3 = Sometimes True, 4 = Often True, 5 = Very Often True); eight items were reverse scored. We summed responses to create a total score (range: 25–125) and subscale scores for abuse and neglect (ranging from 5–25); higher scores indicated greater ACE severity. Using the highest CTQ score ever reported, we categorized composite scores into four categories of maltreatment exposure (i.e., none/minimal, low-to-moderate, moderate-severe, and severe-extreme) based on recommended cut-off scores (Bernstein et al.; 1998). Total and subscale scores for abuse and neglect were used in exploratory analyses. Participants completed the CTQ-SF annually from baseline to year 3, and once during follow-up years 4–7.

The Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) is a semi-structured interview that assesses for mental disorders, including lifetime PTSD, and has previously established reliability and validity (American Psychiatric Association, 1994, 2013; Bucholz et al., 1994; Hesselbrock et al., 1999). Participants who endorsed PTSD Criterion A (0 = no, 5 = yes), either on the adolescent version of the SSAGA or by reporting a trauma that occurred before age 18 on the adult version, were categorized as experiencing an ACE. Endorsement of at least one PTSD criteria B-E (0 = no, 5 = yes) before age 18 was used to determine the presence of PTSD symptoms for the primary analyses. Furthermore, participants’ maximum number of symptoms ever reported before age 18 was used in exploratory analyses to assess whether the greatest symptom severity during adolescence related to rs-FC outcomes. The SSAGA was collected annually from baseline to year 3, and ages 24- and 27 years old.

Alcohol Use

The Customary Drinking and Drug Use Record (CDDR) is a structured interview that assesses lifetime and recent (i.e., past year, past month) substance use and related outcomes including psychological and behavioral dependence (e.g., withdrawal), and other negative consequences (Brown et al., 1998). The CDDR has exhibited psychometric soundness for self-reported substance use and utility in identifying problematic use patterns that could suggest substance abuse (Brown et al., 1998). We used items about the age of alcohol use onset (first report) and recent involvement including frequency (days of use in the past year), consumption (average number of drinks per occasion in the past year), and related problems (number of withdrawal symptoms and blackouts in the past year). We used participants’ most recent reports for items related to alcohol frequency, consumption, and problems. The CDDR was administered annually.

Data Analysis

To assess the association between ACEs, PTSD symptoms, and within-network rs-FC, we conducted a voxel-wise GLM analysis on the average rs-FC for each network of interest using MATLAB (The MathWorks Inc., 2022a) and the FSL Permutation of Linear Models (PALM) package (Winkler et al., 2014). We applied 5000 permutations for each GLM, which regressed the average rs-FC from the ACE coefficient and the ACE and PTSD coefficients. Covariates included age, sex, race, SES, site, drinking threshold at baseline, and motion (mean relative displacement). T-tests were used to examine whether ACEs related to average rs-FC and whether PTSD symptoms were related to rs-FC over and beyond the influence of ACEs alone. Voxel-wise two-tailed p-values were adjusted by the FSL threshold-free cluster enhancement (TFCE), family-wise error correction at the 5% level, and Bonferroni correction for the five networks of interest (p < 0.01) level. For each cluster of significant voxels, we identified overlapping brain regions using the SRI24 atlas (Rohlfing, 2010) and assessed the link between the average rs-FC over the cluster with CTQ total and subscale severity, ACE count, PTSD symptom severity, and alcohol use outcomes among participants who reported ACEs. Due to normality concerns and zero-inflated data, we applied Spearman correlations in R and R Studio software (R Core Team, 2022) using the psych package corr.test() function. Lastly, we repeated the average rs-FC analysis on the slope of rs-FC.

Results

Default Mode Network

The voxel-wise GLM analysis of average rs-FC in the DMN revealed that ACE presence related to lower average rs-FC in two clusters in the right pre-and postcentral gyrus and the left hippocampus (p ≤ 0.005, Figure 2a, 2c). Moreover, within the significant cluster of the pre-and postcentral gyrus, ACEs and PTSD symptoms combined related to less connectivity in regions of the DMN compared to those with neither and ACE alone (p ≤ 0.005, Figure 2a). Endorsing ACEs and PTSD symptoms are also related to lower connectivity in the left temporal superior region (p ≤ 0.005, Figure 2b).

Figure 2.

Figure 2

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Default Mode Network

Note. This figure illustrates the influence of adverse childhood experiences (ACEs) and post-traumatic stress disorder (PTSD) symptoms on average and slope functional connectivity within the Default Mode Network (DMN; p ≤ 0.005 level). The presence of ACEs was significantly associated with less DMN average (red) and slope (green) connectivity. Average connectivity clusters that emerged included the pre and postcentral gyrus (a), temporal gyrus (b), and hippocampus (c). The slope connectivity cluster included the calcarine sulcus, lingual gyrus, precuneus, cerebellum, vermis, and pons (d). The presence of both ACEs and PTSD symptoms (blue; see arrows) was significantly associated with further diminished average connectivity in the pre and postcentral gyrus and temporal gyrus clusters.

The average rs-FC in the hippocampus cluster (see Figure 2c) for the ACE comparison showed a negative correlation with emotional abuse (r = −0.09, p = 0.02) and sexual abuse scores (r = −0.08, p = 0.05). The hippocampus cluster also showed a negative correlation with alcohol use age of onset (r = −0.09, p = 0.04) and withdrawal symptoms (r = −0.29, p < 0.001), and a positive correlation with an average number of drinks per occasion (r = 0.14, p < 0.001). In contrast, the average rs-FC in the pre-and postcentral gyrus negatively correlated with the average number of drinks per occasion (r = −0.12, p = 0.01). For average rs-FC in the left superior temporal gyrus, ACEs and PTSD symptoms related to a negative correlation with PTSD symptom total (r = −0.09, p = 0.03), and a positive correlation with withdrawal symptoms (r = 0.11, p = 0.01).

For voxel-wise slope analysis, the ACE endorsement was associated with a significantly lower slope within a cluster of regions including the calcarine sulcus, lingual gyrus, precuneus, cerebellum, vermis, and pons (p ≤ 0.005, Figure 2d). However, no other significant differences were found.

Salience Network

The voxel-wise analysis of average and slope SN rs-FC indicated ACEs were associated with significantly lower average rs-FC in a cluster of regions including the right olfactory bulb, right rectus gyrus, right caudate, and right putamen, and diminished slope connectivity in a cluster, including regions of the right lingual gyrus and right fusiform gyrus (p’s ≤ 0.005, Figure 3a, 3b). The SN average analysis cluster was negatively correlated with age onset of alcohol use (r = −0.14, p < 0.001) and withdrawal symptoms (r’s = −0.17, p < 0.001; see Table 2). The SN slope analysis cluster for the ACE combined comparison showed a negative correlation with physical abuse (r = −0.11, p = 0.01; Table 2). No other differences were found.

Figure 3.

Figure 3

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Salience Network

Note. This figure illustrates the influence of adverse childhood experiences (ACEs) and post-traumatic stress disorder (PTSD) symptoms on average and slope functional connectivity within the Salience Network (SN; p ≤ 0.005 level). The presence of ACEs was significantly associated with less average (red) and slope (green) connectivity. The average connectivity cluster included the right olfactory bulb, right rectus gyrus, right caudate, and right putamen (a). The slope connectivity cluster included the right lingual gyrus and right fusiform gyrus (b).

Table 2.

Correlations with Functional Networks for Participants with an ACE History

Region N Mean (SD) 1. 2. 3. 4. 5. 6. 7. 8.
DMN
1.Temporal Superior L (C2) 622 −0.45 (0.86) --- 0.11* −0.21** 0.04 −0.22** 0.11* 0.08 0.09*
2.Pre & Postcentral (C2) 622 −0.43 (0.90) -- -- −0.31** 0.15** −0.26** 0.03 −0.03 0.00
3.Hippocampus (C1) 622 1.06 (0.79) -- -- -- −0.13** 0.53** −0.11* 0.01 −0.05
4.Slope (C1) 591 −0.10 (0.50) -- -- -- -- −0.09* 0.02 0.02 0.01
SN
5.Average (C1) 622 0.72 (0.69) -- -- -- -- -- −0.06 −0.06 −0.11*
6.Slope (C1) 591 −0.02 (0.38) -- -- -- -- -- -- 0.06 0.05
Medial FPN
7.Slope (C1) 591 −0.04 (0.48) -- -- -- -- -- -- -- 0.84**
8.Slope (C2) 591 −0.07 (0.63) -- -- -- -- -- -- -- --
ACE-IQ 475 3.51 (2.34) −0.05 −0.05 −0.03 −0.01 0.04 0.01 −0.03 −0.01
CTQ total 588 37.94 (11.14) −0.03 −0.02 −0.07 0.05 −0.07 −0.04 −0.06 −0.03
EA 588 8.13 (3.78) 0.01 −0.01 −0.09* 0.01 −0.05 −0.05 −0.01 0.01
PA 588 6.92 (2.70) −0.05 −0.04 −0.01 0.00 −0.04 −0.11* 0.00 0.01
SA 588 5.76 (2.62) 0.00 0.03 −0.08* 0.02 −0.05 −0.02 0.01 0.08
EN 588 10.93 (4.76) −0.05 0.00 −0.06 0.06 −0.06 0.00 −0.05 0.00
PN 588 7.91 (2.91) −0.01 −0.01 −0.01 0.03 −0.06 −0.04 −0.06 −0.05
PTSD total 588 1.44 (3.61) −0.09* −0.05 −0.05 0.02 0.03 0.01 0.00 0.00
EtOH Onset 555 16.22 (2.40) 0.04 0.02 −0.09* 0.00 −0.14** 0.00 0.01 0.00
EtOH Days (past year) 622 53.76 (66.43) 0.05 0.04 0.01 0.04 0.07 −0.02 −0.03 0.01
EtOH Average 515 2.61 (1.83) −0.06 −0.12* 0.14** −0.03 0.08 0.01 0.00 0.03
WD Symptoms 513 0.32 (0.87) 0.11* 0.05 −0.29** −0.01 −0.17** 0.06 −0.01 0.00
Blackout 486 0.70 (3.04) −0.06 −0.03 0.05 −0.03 0.04 0.06 −0.07 −0.03
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Note. Spearman correlations for clinical measures and functional connectivity averages & slopes among participants with an ACE history (n = 622). DMN = Default Mode Network, SN = Salience Network, FPN = Frontoparietal Network, C1 = Contrast 1 (the ACE coefficient GLM), C2 = Contrast 2 (ACE and PTSD coefficient GLM), ACE-IQ= maximum Adverse Childhood Experiences International Questionnaire, CTQ = Childhood Trauma Questionnaire, EA = Emotional Abuse, PA = Physical Abuse, SA = Sexual Abuse, PN = Physical Neglect, EN = Emotional Neglect, PTSD total = post-traumatic stress disorder symptom total (Maximum), EtOH Onset = Alcohol Use Age of Onset, EtOH Days = Number of Days of Alcohol Use (past year), EtOH Average = Number of Drinks on Average Per Occasion; WD = Withdrawal.

*

p ≤ 0.05

**

p < 0.001

Central Executive Network

Three networks represented the CEN (i.e., the medial, left and right superior FPNs). ACEs related to significantly lower slope rs-FC in the medial FPN (MFN) regions, including the right middle and superior temporal gyri (p ≤ 0.005, Figure 4). Further, ACEs and PTSD symptoms related to significantly lower slope connectivity within the right superior temporal gyrus (p ≤ 0.005; Figure 4). No other differences were detected for rs-FC within the medial, left, or right FPN.

Figure 4.

Figure 4

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Medial Frontoparietal Network

Note. This figure illustrates the influence of adverse childhood experiences (ACEs) and post-traumatic stress disorder (PTSD) symptoms on slope functional connectivity within the medial superior frontoparietal network (mFPN; p ≤ 0.005 level). The presence of ACEs (green) was significantly associated with less slope functional connectivity (green) in a cluster that included the right middle and superior temporal gyri. The presence of both ACEs and PTSD symptoms (blue; see arrows) was associated with further diminished slope connectivity in a cluster that included the right superior temporal gyrus.

Exploratory Analyses

Tables 2 and 3 show Spearman correlations between ACE severity, PTSD symptom severity, alcohol use outcomes, and the average and slope values for significant network clusters for participants who reported ACEs. Table 4 shows the same Spearman correlations among participants without an ACE history.

Table 3.

Correlations for Clinical & Self-Report Measures for Participants with ACE History

Measure 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13.
1.ACE-IQ 0.43** 0.50** 0.36** 0.27** 0.31** 0.15** 0.18** −0.09 0.01 −0.01 −0.08 −0.06
2.CTQ -- 0.68** 0.55** 0.40** 0.87** 0.66** 0.20** −0.05 −0.13** −0.04 −0.06 −0.12*
3. EA -- -- 0.48** 0.36** 0.47** 0.27** 0.19** −0.04 −0.11* −0.06 −0.04 −0.09*
4. PA -- -- -- 0.31** 0.35** 0.24** 0.15** 0.02 −0.07 −0.05 −0.07 −0.10*
5. SA -- -- -- -- 0.26** 0.21** 0.17** −0.06 −0.06 −0.07 −0.05 0.02
6.EN -- -- -- -- -- 0.56** 0.14** 0.00 −0.12** −0.05 −0.06 −0.11*
7.PN -- -- -- -- -- -- 0.10* −0.06 −0.04 −0.03 −0.03 −0.06
8.PTSD total -- -- -- -- -- -- -- −0.11* 0.05 0.04 0.13** 0.06
9.EtOH Age -- -- -- -- -- -- -- -- -.23** -.30** −0.10* −0.20**
10.EtOH Days -- -- -- -- -- -- -- -- -- 0.31** 0.21** 0.30**
11. EtOH Average -- -- -- -- -- -- -- -- -- -- 0.13** 0.40**
12.WD Sx -- -- -- -- -- -- -- -- -- -- -- 0.13**
13.Blackout -- -- -- -- -- -- -- -- -- -- -- --
Open in a new tab

Note: Spearman correlations for clinical and alcohol use measures for participants with a history of ACEs (n = 622). ACE-IQ= maximum Adverse Childhood Experiences International Questionnaire, CTQ = Childhood Trauma Questionnaire, EA = Emotional Abuse, PA = Physical Abuse, SA = Sexual Abuse, PN = Physical Neglect, EN = Emotional Neglect, PTSD = post-traumatic stress disorder symptom total (Maximum), EtOH Onset = Alcohol Use Age of Onset, EtOH Days = Number of Days of Alcohol Use (past year), EtOH Average = Number of Drinks on Average Per Occasion; WD = Withdrawal.

*

p ≤ 0.05

**

p < 0.001

Table 4.

Correlations with Functional Networks for Participants without an ACE History

Region N Mean (SD) 1. 2. 3. 4. 5. 6. 7. 8.
DMN
1.Temporal Superior L (C2) 65 −0.25 (0.88) --- 0.11 −0.13 0.13 −0.03 −0.15 −0.01 −0.06
2.Pre & Postcentral (C2) 65 −0.03 (1.04) -- -- −0.17 0.03 0.14 −0.11 0.03 0.06
3.Hippocampus (C1) 65 1.78 (1.22) -- -- -- 0.15 0.38** 0.12 0.14 0.09
4.Slope (C1) 55 0.45 (1.01) -- -- -- -- 0.15 0.26 0.20 0.10
SN
5.Average (C1) 65 1.25 (0.94) -- -- -- -- -- 0.25 0.07 0.03
6.Slope (C1) 55 0.33 (0.93) -- -- -- -- -- -- 0.32* 0.33*
Medial FPN
7.Slope (C1) 55 0.43 (1.18) -- -- -- -- -- -- -- 0.89**
8.Slope (C2) 55 0.55 (1.30) -- -- -- -- -- -- -- --
ACE-IQ 13 0.00 (0.00) -- -- -- -- -- -- -- --
CTQ total 35 26.77 (2.03) 0.68** 0.05 −0.21 0.35 −0.19 −0.06 −0.09 −0.17
EA 35 5.46 (0.70) 0.35* −0.16 −0.29 0.24 −0.49** −0.11 0.02 −0.13
PA 35 5.17 (0.45) 0.09 −0.24 0.01 0.19 −0.35* −0.01 −0.13 −0.28
SA 35 5.00 (0.00) -- -- -- -- -- -- -- --
EN 35 5.89 (1.21) 0.67** 0.23 −0.19 0.14 0.04 −0.08 −0.08 −0.06
PN 35 5.34 (0.68) 0.38* 0.06 −0.21 0.56** −0.11 0.10 0.00 −0.09
PTSD total 65 0.00 (0.00) -- -- -- -- -- -- -- --
EtOH Onset 51 16.62 (1.87) −0.03 0.01 −0.17 −0.19 −0.21 −0.12 −0.07 −0.05
EtOH Days (past year) 65 43.42 (52.17) −0.07 −0.08 0.25* −0.10 0.00 −0.36* −0.16 −0.14
EtOH Average 46 2.90 (1.77) −0.17 0.25 0.00 −0.02 0.42** 0.00 −0.13 −0.23
WD Symptoms 46 0.11 (0.38) 0.07 0.00 −0.14 0.12 −0.08 −0.11 0.04 −0.18
Blackout 41 0.63 (1.04) 0.15 0.31* −0.10 0.23 0.17 −0.03 0.04 0.02
Open in a new tab

Note. Spearman correlations for clinical measures and functional connectivity averages & slopes among participants without an ACE history (n = 65). DMN = Default Mode Network, SN = Salience Network, FPN = Frontoparietal Network, C1 = Contrast 1 (the ACE coefficient GLM), C2 = Contrast 2 (ACE and PTSD coefficient GLM), ACE-IQ= maximum Adverse Childhood Experiences International Questionnaire, CTQ = Childhood Trauma Questionnaire, EA = Emotional Abuse, PA = Physical Abuse, SA = Sexual Abuse, PN = Physical Neglect, EN = Emotional Neglect, PTSD total = post-traumatic stress disorder symptom total (Maximum), EtOH Onset = Alcohol Use Age of Onset, EtOH Days = Number of Days of Alcohol Use (past year), EtOH Average = Number of Drinks on Average Per Occasion; WD = Withdrawal. No correlations are reported for ACE-IQ, SA, and PTSS total due to absence of symptoms reported and zero variability.

*

p ≤ 0.05

**

p < 0.001

Discussion

The current study assessed adolescent brain function differences related to the presence of ACEs, PTSD symptoms, and alcohol-related problems. Our findings supported predictions that adolescents with ACEs have diminished within-network rs-FC (average and slope) in emotional and cognitive processing regions within the three networks of interest (i.e., DMN, SN, MFN). Within the DMN, adolescents with ACEs showed less rs-FC within the hippocampus. For the DMN and MFN, ACEs were associated with less connectivity in sensory and motor processing regions (e.g., pre-, and post-central gyri, superior and middle temporal gyri). Moreover, ACEs were related to diminished SN rs-FC within reward processing regions (e.g., caudate and putamen). We also found that PTSD symptoms contributed to further diminished rs-FC within the DMN and MFN, particularly for social cognition, sensory, and motor processing regions (e.g., superior temporal gyrus; precentral and postcentral gyri). Last, we found that lower rs-FC was generally linked with more alcohol withdrawal symptoms. These findings shed light on potential social, emotional, and cognitive functioning impairments and alcohol-related implications among adolescents with ACEs and PTSD symptoms.

In line with prior research, ACE presence and severity (i.e., greater abuse and neglect) were related to diminished hippocampal rs-FC which has been associated with poorer memory (Fadel et al., 2021; Silveira et al., 2020; Zhou et al., 2012). We found the same pattern of results for regions involved in sensory and reward processing (e.g., right caudate, right putamen, etc.), suggesting that ACEs may contribute to changes in attention and responding that could lead to more impulsivity (Lloyd et al., 2022). While this change may be adaptive in unpredictable environments, it likely contributes to problems in the long term.

The greater influence of PTSD symptoms on diminished rs-FC found in this study aligns with prior research (e.g., Bluhm et al., 2009; Sheynin et al., 2020; Zhou et al., 2012). Our findings linking the presence of PTSD symptoms and FC changes in the hippocampus complement prior research indicating that patients with PTSD symptoms showed FC changes in the amygdala, which works closely with the hippocampus for emotion-related processing and forming memories (Xiao et al., 2022). Hippocampal rs-FC changes may reflect a dissociative subtype of PTSD characterized by memory suppression and dampened effect that is common among those with early and longstanding exposure to stressors (Lanius et al., 2010). Furthermore, PTSD is associated with deficits in social cognition, though the direction of this relationship is unclear, and may have more widespread influences on brain function (Stevens & Jovanoic, 2019). We did not find weaker rs-FC associated with PTSD symptoms within the SN, which may be due to assessing a variety of ACEs and PTSD presentations together rather than exploring if a specific symptom, such as hyperarousal, was driving changes in the SN (Sheynin et al., 2020). Further work examining the nature and extent of PTSD symptoms is warranted, including related to alcohol.

The present study supports research linking less rs-FC in these networks to alcohol-related problems (e.g., withdrawal; Gerhardt et al., 2022). Withdrawal is suggested to be a useful marker of drinking severity and is associated with reductions in hippocampal volume among adolescents (Squeglia et al., 2014). The finding of decreased rs-FC may reflect changes in alcohol cue reactivity associated with withdrawal. Given that withdrawal is a serious alcohol disorder symptom, our findings indicate a need for further exploration to determine how rs-FC changes may relate to profiles of risk. Our results did not support that lower rs-FC associated with ACEs and/or PTSD symptoms was related to earlier alcohol use onset or heavier average alcohol consumption in keeping with other studies of alcohol onset on brain function in the areas under investigation (Nguyen-Louie et al., 2019).

Limitations

Using fMRI NCANDA data, we created a robust estimate of average and slope rs-FC for each network that allowed us to explore brain function in adolescents. This approach has limitations, as aggregating fMRI data may contribute to overlooking important brain differences at the intersection of ACEs and PTSD symptoms. Furthermore, applying a longitudinal analysis to assess changes in brain function over time would provide insight into specific within-participant developmental trajectories. The absence of data for specific ages of ACEs and PTSD symptoms limited our ability to determine the temporal precedence of measures. While the use of retrospective measures is evidence-based and widely used, no conclusions can be made for causality.

Given the high prevalence of ACEs, the use of low cut-off values to categorize participants for ACE and PTSD symptoms may have prevented us from detecting differences in rs-FC. The low threshold for PTSD symptom categorization (one symptom) may partially explain why an additive influence of PTSD symptoms was not found for all clusters. Future studies should consider continuous measurements or higher cut-off values to address these concerns.

While typical, the non-normality and zero inflation in adolescent alcohol use and clinical symptom measures may have limited our ability to identify relationships between variables. We applied Spearman correlations to address these concerns. This decision may partially explain the overall low magnitude of associations that emerged from exploratory analyses. Additionally, we did not include interaction effects in our models. Alternative approaches for working with longitudinal data and non-normal distributions could be explored in future investigations.

Clinical Implications

Our study included adolescents who experienced ACEs of varying types and severity and those with at least one reported PTSD symptom. We found brain changes at the intersection of ACEs and PTSD symptoms which also related to higher self-reported alcohol problems (i.e., withdrawal symptoms). Thus, our findings suggest that interventions may be warranted among adolescents with less severe forms of adversity and below the full diagnostic criteria for PTSD. Screening early for ACEs and PTSD symptoms more broadly could help to identify children and adolescents at risk for socioemotional challenges and mental health problems. Our findings suggest a need to tailor interventions toward reducing neural vulnerability and promoting health in adolescence and early adulthood. In addition, prevention efforts focused on decreasing adolescent alcohol use behaviors (e.g., binge drinking) that may contribute to reducing the risk for problematic alcohol use outcomes, like withdrawal. These efforts can help to mitigate the risk of problematic developmental consequences that are associated with exposure to ACEs and mental health sequelae.

Conclusion

In NCANDA, a nationally representative sample of adolescents, ACEs and PTSD symptoms were related to reduced rs-FC within brain networks involved in emotional and cognitive processing. We found an additional influence of PTSD symptoms on brain function, which warrants future research aimed at investigating the role of specific PTSD symptoms. The role of ACE type, severity, and chronicity on brain function was not considered in this study, making this another important aim for future studies. Our findings indicated that alcohol withdrawal symptoms at a later follow-up were related to reductions in resting-state functioning in some of the impacted brain networks. Future research is needed to better understand the role of rs-FC changes on subsequent alcohol use outcomes, and directionality of this relationship. Furthermore, consideration of the influences of ACEs and PTSD symptoms on between-network rs-FC may help to clarify functional changes related to specific neural pathways and behavioral/cognitive outcomes. Overall, the present study offers new and supporting information on the relationship between ACEs, PTSD symptoms, and alcohol use on adolescent brain function that can be used to inform prevention and treatment efforts for both PTSD and alcohol-related problems.

Supplementary Material

Supplementary Figure 1

Supplementary Figure 1 Functional Networks for Participants without ACEs and PTSD Symptoms

Note. The group-level functional networks overlaid with SRI24 atlas (Rohlfing et al., 2010) for participants who denied adverse childhood experiences (ACEs) and post-traumatic stress disorder (PTSD) symptoms (n = 65). Regions with high connectivity (Z-scores ≥ 3) are visualized in yellow.

Supplementary Figure 2

Supplementary Figure 2 Functional Networks for Participants with ACEs and No PTSD Symptoms

Note. The group-level functional networks overlaid with SRI24 atlas (Rohlfing et al., 2010) for participants who endorsed adverse childhood experiences (ACEs) and denied post-traumatic stress disorder (PTSD) symptoms (n = 492). Regions with high connectivity (Z-scores ≥ 3) are visualized in yellow.

Supplementary Figure 3

Supplementary Figure 3 Functional Networks for Participants with ACEs and PTSD Symptoms

Note. The group-level functional networks overlaid with SRI24 atlas (Rohlfing et al., 2010) for participants who endorsed adverse childhood experiences (ACEs) and post-traumatic stress disorder (PTSD) symptoms (n = 130). Regions with high connectivity (Z-scores ≥ 3) are visualized in yellow.

Footnotes

Declaration of Interest Statement: The authors report there are no competing interests to declare.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Figure 1

Supplementary Figure 1 Functional Networks for Participants without ACEs and PTSD Symptoms

Note. The group-level functional networks overlaid with SRI24 atlas (Rohlfing et al., 2010) for participants who denied adverse childhood experiences (ACEs) and post-traumatic stress disorder (PTSD) symptoms (n = 65). Regions with high connectivity (Z-scores ≥ 3) are visualized in yellow.

NIHMS2047628-supplement-Supplementary_Figure_1.jpg (901.7KB, jpg)
Supplementary Figure 2

Supplementary Figure 2 Functional Networks for Participants with ACEs and No PTSD Symptoms

Note. The group-level functional networks overlaid with SRI24 atlas (Rohlfing et al., 2010) for participants who endorsed adverse childhood experiences (ACEs) and denied post-traumatic stress disorder (PTSD) symptoms (n = 492). Regions with high connectivity (Z-scores ≥ 3) are visualized in yellow.

NIHMS2047628-supplement-Supplementary_Figure_2.jpg (882.6KB, jpg)
Supplementary Figure 3

Supplementary Figure 3 Functional Networks for Participants with ACEs and PTSD Symptoms

Note. The group-level functional networks overlaid with SRI24 atlas (Rohlfing et al., 2010) for participants who endorsed adverse childhood experiences (ACEs) and post-traumatic stress disorder (PTSD) symptoms (n = 130). Regions with high connectivity (Z-scores ≥ 3) are visualized in yellow.

NIHMS2047628-supplement-Supplementary_Figure_3.jpg (899.8KB, jpg)

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