Social media use has been linked to more depressive symptoms, but how algorithm-generated content influences psychopathology is unclear given the proprietary nature of algorithms on social media platforms. The present study investigated associations among personally recommended content, real-time emotional processing of such content, and depressive symptoms. Data collection was conducted between 2024 January and 2025 February. Sixty young adults (78.30% female; M age = 20.17; 51.67% Asian, 25.00% White, 3.33% Bi-racial, 20.00% Hispanic or Latino) completed a depressive symptoms scale and watched personally recommended videos (PV) extracted from their Instagram or TikTok accounts and generalized videos (GV) from new user accounts, while brain activity was recorded using electroencephalogram (EEG) to derive Frontal Alpha Asymmetry (FAA). To understand what types of content participants viewed, PV were categorized using a content analysis. Results showed that the most common category watched by young adults was social relationship videos (about friends and romantic partners), 20.11%. These videos were further categorized as positive, neutral, or negative and were used in analyses. Partial correlations controlling for sex and screen time showed that adults with more depressive symptoms viewed fewer positive, more negative, and neutral social relationship videos and showed negative emotional processing (reflected in more relative right FAA) toward PV, but not GV. Fewer positive social relationship content was also associated with relative right FAA toward PV. These findings suggest that algorithmically generated recommended content is linked to how users emotionally process that content in real-time, in ways associated with depressive symptoms.

Childhood behavioral problems are associated with significant long-term consequences, yet the underlying cognitive mechanisms remain poorly understood. In this study, we employed computational modeling alongside traditional reaction time (RT) measures to investigate cognitive control during a flanker task. We evaluated the predictive utility of these methods in explaining variance across eight transdiagnostic symptom domains in late childhood (mean age = 10.0 years; n = 10,343) from the Adolescent Brain Cognitive Development study. We compared simultaneous regression models across congruent and incongruent conditions using an RT-only model and a drift–diffusion model (DDM) that incorporated boundary separation, bias, drift rate, and non-decision time parameters. Results from the RT-only models indicated that slower reaction times across both task conditions were associated with higher scores on most symptom subscales, suggesting more behavioral problems. For both task conditions, DDM regressions accounted for more total variance across symptom domains compared to RT models. Additionally, DDM regressions demonstrated that impoverished evidence accumulation emerged as a shared feature of both internalizing and externalizing behaviors, while reductions in non-decision time, indicative of increased impulsiveness, were unique to rule-breaking and aggressive behaviors. These findings suggest that different aspects of cognitive control are associated with specific behavioral problems in children, rather than just overall response speed. Present results provide new insights into cognitive control dynamics and suggest that targeting ineffective cognitive control could be crucial for the prevention and intervention of childhood psychopathology.

This study investigates the neural underpinnings of cognitive control deficits in attention-deficit/hyperactivity disorder (ADHD), focusing on trial-level variability of neural coding. Using fMRI, we apply a computational approach to single-trial neural decoding on a cued stop-signal task, probing proactive and reactive control within the dual control model. Reactive control involves suppressing an automatic response when interference is detected, and proactive control involves implementing preparatory strategies based on prior information. In contrast to typically developing children (TD), children with ADHD show disrupted neural coding during both proactive and reactive control, characterized by increased temporal variability and diminished spatial stability in neural responses in salience and frontal-parietal network regions. This variability correlates with fluctuating task performance and ADHD symptoms. Additionally, children with ADHD exhibit more heterogeneous neural response patterns across individuals compared to TD children. Our findings underscore the significance of modeling trial-wise neural variability in understanding cognitive control deficits in ADHD.

Background: Pathological anxiety is commonly treated as a unitary construct, manifesting as various clinical subtypes. However, there is a growing consensus that anxiety has at least two unique dimensions, anxious arousal and anxious apprehension. Nevertheless, their distinguishable neurobiological mechanisms are unclear. Here, we take a transdiagnostic approach to disentangle network-level functional and structural disturbances at rest, a state when some anxiety symptoms may be most apparent. Methods: 53 adults experiencing a range of anxiety and/or depressive symptoms completed resting-state fMRI. Resting-state networks were identified by independent components analysis. Dual-regression tested anxious arousal and anxious apprehension derived within-network connectivity differences while controlling for depression. FSLNets tested differences in between-network functional connectivity. Results: Anxious apprehension was associated with expansion of the default and somatomotor networks, while anxious arousal was associated with hyperconnectivity in the salience, limbic, frontoparietal, and default networks. Anxious apprehension was also associated with increased connectivity between the default and salience networks as well as decreased connectivity between the dorsal attention and limbic networks. Limitations: Evaluating a larger sample size and longer resting-state scans can better ensure reproducibility of results. The cross-sectional design limits conclusions about the temporal dynamics of anxious apprehension and anxious arousal and functional connectivity alterations observed in the present study. Conclusions: Results suggest that anxious apprehension and anxious arousal have distinguishable neurobiological mechanisms that contribute to maladaptive differences in threat evaluation, stress response, and self-referential thought. These findings enhance our understanding of anxiety's nosology and pathophysiology, informing potential mechanisms for intervention.

OBJECTIVES:Older adults may be particularly vulnerable to the negative effect of distress on cognition, thus explaining cognitive behavioral therapy's (CBT's) diminished efficacy for generalized anxiety disorder (GAD) in later life. Emotion-centered Problem Solving Therapy (EC-PST) may address this and other barriers to skill acquisition. METHOD:This single-arm pilot aimed to determine the feasibility of 6-session EC-PST to achieve clinically significant improvements in anxiety and/or worry symptoms in adults aged 55+ with GAD. Secondary analyses also examined reductions in depressive symptoms and assessed participant satisfaction with treatment components. RESULTS:Sixteen adults aged 58 to 83 years old with current GAD were enrolled. Fourteen participants completed treatment. Twelve participants (85.7%) had a clinically significant pre- to post-treatment reduction in anxiety and/or worry symptoms. Additionally, nine (64.2%) had a clinically significant reduction in depressive symptoms. Qualitative feedback indicated a high level of satisfaction based on themes of reduced avoidance, increased confidence in managing anxiety, and feeling more in control of life problems. CONCLUSION:Findings support feasibility and acceptability of EC-PST for GAD in middle-aged and older adults that is worthy of follow up in a randomized controlled trial given the limited options for evidence-based therapy in later life anxiety.

Creating abbreviated measures from lengthy questionnaires is important for reducing respondent burden while improving response quality. Though factor analytic strategies have been used to guide item retention for abbreviated questionnaires, item retention can be conceptualized as a feature selection task amenable to machine learning approaches. The present study tested a machine learning-guided approach to item retention, specifically item-level importance as measured by Shapley values for the prediction of total score, to create abbreviated versions of the Penn State Worry Questionnaire (PSWQ) in a sample of 3,906 secondary school students. Results showed that Shapley values were a useful measure for determining item retention in creating abbreviated versions of the PSWQ, demonstrating concordance with the full PSWQ. As item-level importance varied based on the proportion of the worry distribution predicted (e.g., high versus low PSWQ scores), item retention is dependent on the intended purpose of the abbreviated measure. Illustrative examples are presented.

Mild traumatic brain injury (mTBI) and posttraumatic stress are prevalent in military service members and share objective and subjective cognitive symptoms, complicating recovery. We investigated the effects of remote mTBI characteristics and current posttraumatic stress symptoms on neuropsychological performance in 152 veterans with a history of remote mTBI and current cognitive concerns. Participants completed clinical neuropsychological evaluations within a Veterans Affairs Level-II TBI/Polytrauma outpatient clinic (i.e. tertiary trauma care center for US military veterans outside of a research or teaching hospital setting). Archival data analysis of mTBI injury characteristics, clinical diagnoses, scores on the Posttraumatic Stress Disorder Checklist-Military Version (PCL-M) and performance on tests of processing speed, attention and executive function was conducted. Hierarchical linear regression demonstrated that elevated PCL-M scores were associated with slower performance on trail making test (TMT) Parts A and B (p < .016). PCL-M symptoms moderated the effect of alteration of consciousness (AOC) on TMT performance, with endorsement of AOC associated with better performance, but only when PCL-M scores were high (p < .005). Follow-up mediation analyses demonstrated that PCL-M score fully mediated the relationship between AOC and TMT-A performance and partially mediated the relationship between AOC and TMT-B performance. Post-hoc analyses meant to separate the impact of processing speed on TMT-B were all non-significant. Remote mTBI characteristics, specifically AOC, were not associated with decrements in cognitive performance. Posttraumatic symptoms were associated with worse processing speed, suggesting that psychological distress and psychopathology are contributing factors in understanding and treating persistent cognitive distress following remote mTBI.

We developed a novel Proactive Reactive and Attentional Dynamics (PRAD) computational model designed to dissect the latent mechanisms of inhibitory control in human cognition. Leveraging data from over 7,500 participants in the NIH Adolescent Brain Cognitive Development study, we demonstrate that PRAD surpasses traditional models by integrating proactive, reactive, and attentional components of inhibitory control. Employing a hierarchical Bayesian framework, PRAD offers a granular view of the dynamics underpinning action execution and inhibition, provides debiased estimates of stop-signal reaction times, and elucidates individual and temporal variability in cognitive control processes. Our findings reveal significant intra-individual variability, challenging conventional assumptions of random variability across trials. By addressing nonergodicity and systematically accounting for the multi-componential nature of cognitive control, PRAD advances our understanding of the cognitive mechanisms driving individual differences in cognitive control and provides a sophisticated computational framework for dissecting dynamic cognitive processes across diverse populations. ### Competing Interest Statement The authors have declared no competing interest.

Repetitive negative thinking, including worry and rumination, is considered a transdiagnostic process that contributes to the development and persistence of psychopathology. Recently, Castro et al. (2022) investigated how both repetitive negative thinking and more adaptive repetitive thinking may be related each other. They found evidence for a bi-factor structure of repetitive thinking with both shared variance in repetitive thinking and unique variance specific to each form of repetitive thinking, specifically worry, rumination, and reflection. The present study replicated this bi-factor structure of repetitive thinking in a younger sample from the Netherlands (N = 3906). Additionally, biological sex did not alter bi-factor structure fit. The present findings provide additional evidence of a bi-factor structure of repetitive thinking, and future work should continue to explore the clinical relevance of repetitive thinking and its distinct forms.

This study explores the neural underpinnings of cognitive control deficits in ADHD, focusing on overlooked aspects of trial-level variability of neural coding. We employed a novel computational approach to neural decoding on a single-trial basis alongside a cued stop-signal task which allowed us to distinctly probe both proactive and reactive cognitive control. Typically developing (TD) children exhibited stable neural response patterns for efficient proactive and reactive dual control mechanisms. However, neural coding was compromised in children with ADHD. Children with ADHD showed increased temporal variability and diminished spatial stability in neural responses in salience and frontal-parietal network regions, indicating disrupted neural coding during both proactive and reactive control. Moreover, this variability correlated with fluctuating task performance and with more severe symptoms of ADHD. These findings underscore the significance of modeling single-trial variability and representational similarity in understanding distinct components of cognitive control in ADHD, highlighting new perspectives on neurocognitive dysfunction in psychiatric disorders.

Cognitive control deficits are a hallmark of attention deficit hyperactivity disorder (ADHD) in children. Theoretical models posit that cognitive control involves reactive and proactive control processes but their distinct roles and inter-relations in ADHD are not known, and the contributions of proactive control remain vastly understudied. Here, we investigate the dynamic dual cognitive control mechanisms associated with both proactive and reactive control in 50 children with ADHD (16F/34M) and 30 typically developing (TD) children (14F/16M) aged 9-12 years across two different cognitive controls tasks using a within-subject design. We found that while TD children were capable of proactively adapting their response strategies, children with ADHD demonstrated significant deficits in implementing proactive control strategies associated with error monitoring and trial history. Children with ADHD also showed weaker reactive control than TD children, and this finding was replicated across tasks. Furthermore, while proactive and reactive control functions were correlated in TD children, such coordination between the cognitive control mechanisms was not present in children with ADHD. Finally, both reactive and proactive control functions were associated with behavioral problems in ADHD, and multi-dimensional features derived from the dynamic dual cognitive control framework predicted inattention and hyperactivity/impulsivity clinical symptoms. Our findings demonstrate that ADHD in children is characterized by deficits in both proactive and reactive control, and suggest that multi-componential cognitive control measures can serve as robust predictors of clinical symptoms.

Psychopathology in youth is highly prevalent and associated with psychopathology in adulthood. However, the developmental trajectories of psychopathology symptoms, including potential gender differences, are markedly underspecified. The present study employed a directed network approach to investigate longitudinal relationships and gender differences among eight transdiagnostic symptom domains across three years, in a homogenous age sample of youth participants ( n = 6,414; mean baseline age = 10.0 years; 78.6% White; Adolescent Brain Cognitive Development study). Anxious/depressed problems and aggressive behaviors were central symptoms and most predictive of increases in other symptom clusters at later timepoints. Rule-breaking behaviors, aggressive behaviors, and withdrawn/depressed problems emerged as bridge symptoms between externalizing and internalizing problems. Results supported cascade models in which externalizing problems predicted future internalizing problems, but internalizing problems also significantly predicted future externalizing problems, which is contrary to cascade models. Network structure, symptom centrality, and patterns of bridge symptoms differed between female and male participants, suggesting gender differences in the developmental trajectories of youth psychopathology. Results provide new insights into symptom trajectories and associated gender differences that may provide promising pathways for understanding disorder (dis)continuity and co-occurrence. The central and bridge symptoms identified here may have important implications for screening and early intervention for youth psychopathology.

OBJECTIVEThere is a growing recognition that the use of conventional norms (e.g., age, sex, years of education, race) as proxies to capture a broad range of sociocultural variability on cognitive performance is suboptimal, limiting sample representativeness. The present study evaluated the incremental utility of family income, family conflict, and acculturation beyond the established associations of age, gender,maternal years of education, and race on cognitive performance.METHODHierarchical linear regressions evaluated the incremental utility of sociocultural factors on National Institutes of Health Toolbox in a nationally representative sample of pre-adolescent children (n = 11,878; Mage = 10.0 years; Adolescent Brain Cognitive Development Study). A regression-based norming procedure was implemented for significant models. Paired sample t-tests were used to compare original and newly created demographically corrected T-scores.RESULTSNearly all regression models predicted performance on the NIH-TB subtests and composite scores (p < .005). Greater family income and lower family conflict predicted better performance, although the effect sizes were small by traditional standards. Acculturation scores did not explain additional variance in cognitive performance. Lastly, there were no significant differences between the original and newly created demographically corrected T-scores (Mdiff < 0.50).CONCLUSIONSThe present study highlights that, although family income, family conflict, and acculturation have been shown to routinely influence cognitive performance in preadolescent children, the NIH-TB appears to be highly robust to individual differences in sociocultural factors in children between ages 9 and 10. Contextual and temporal implications of the present results are discussed.

Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are highly prevalent, co-occurring disorders with significant symptom overlap, posing challenges in accurately distinguishing and diagnosing these disorders. The tripartite model proposes that anxious arousal is specific to anxiety and anhedonia is specific to depression, though anxious apprehension may play a greater role in GAD than anxious arousal. The present study tested the efficacy of the Mood and Anxiety Symptom Questionnaire anhedonic depression (MASQ-AD) and anxious arousal (MASQ-AA) scales and the Penn State Worry Questionnaire (PSWQ) in identifying lifetime or current MDD, current major depressive episode (MDE), and GAD using binary support vector machine learning algorithms in an adult sample (n = 150). The PSWQ and MASQ-AD demonstrated predictive utility in screening for and identification of GAD and current MDE respectively, with the MASQ-AD eight-item subscale outperforming the MASQ-AD 14-item subscale. The MASQ-AA did not predict MDD, current MDE, or GAD, and the MASQ-AD did not predict current or lifetime MDD. The PSWQ and MASQ-AD are efficient and accurate screening tools for GAD and current MDE. Results support the tripartite model in that anhedonia is unique to depression, but inclusion of anxious apprehension as a separate dimension of anxiety is warranted.

The Penn State Worry Questionnaire (PSWQ) is a widely used assessment of excessive worry. American undergraduate samples have predominately been used to evaluate its factor structure, which may not generalize to other developmental, cultural, and psychopathology populations. The present study tested the PSWQ's factor structure across three diverse samples: American undergraduate students (n = 3,243), Dutch high school students (n = 3,906), and American adults with psychopathology (n = 384). Exploratory, confirmatory, and multigroup confirmatory factor analyses were conducted. Measurement invariance and concurrent validity were also tested. Method-factor and two-factor models were largely equivalent and superior to a one-factor model. Invariance tests supported configural and metric invariance but only partial scalar invariance. Positively worded items but not negatively worded items demonstrated concurrent validity with anxiety and depression symptom measures and diagnoses. Overall, the PSWQ appears to measure a unitary construct. Present results warrant further testing of the PSWQ across diverse samples.

OBJECTIVE:To investigate whether the BDNF Val66Met polymorphism influences the associations of hypertension, executive functioning and processing speed in older adults diagnosed with amnestic Mild Cognitive Impairment (aMCI).DESIGN:Secondary data analysis using moderation modeling.SETTING:Veterans Affairs Hospital, Palo Alto, CA.PARTICIPANTS:Sample included 108 community-dwelling volunteers (mean age 71.3 ± 9.2 years) diagnosed with aMCI.MEASUREMENTS:Cognitive performance was evaluated from multiple baseline assessments (Trail Making Test; Stroop Color-Word Test; Symbol Digit Modality Test) and grouped into standardized composite scores representing executive function and processing speed domains. BDNF genotypes were determined from whole blood samples. Hypertension was assessed from resting blood pressures or by self-report.RESULTS:Controlling for age, BDNF Val66Met moderated the effects of hypertension on executive functioning, but added no significant variance to processing speed scores. Specifically, hypertensive carriers of the BDNF Met allele performed significantly below the sample mean on tasks of executive functioning, and evidenced significantly lower scores when compared to Val-Val homozygotes and normotensive participants.CONCLUSIONS:Results posit that the executive functioning of non-demented older adults may be susceptible to interactions between BDNF genotype and hypertension, and Val-Val homozygotes and normotensive older adults may be more resilient to these effects of cognitive change. Further research is needed to understand the underlying processes and to implement strategies that target modifiable risk factors and promote cognitive resilience.

Anhedonia is a prominent characteristic of depression and related pathology that is associated with a prolonged course of mood disturbance and treatment resistance. However, the neurobiological mechanisms of anhedonia are poorly understood as few studies have disentangled the specific effects of anhedonia from other co-occurring symptoms. Here, we take a transdiagnostic, dimensional approach to distinguish anhedonia alterations from other internalizing symptoms on intrinsic functional brain circuits. 53 adults with varying degrees of anxiety and/or depression completed resting-state fMRI. Neural networks were identified through independent components analysis. Dual regression was used to characterize within-network functional connectivity alterations associated with individual differences in anhedonia. Modulation of between-network functional connectivity by anhedonia was tested using region-of-interest to region-of-interest correlational analyses. Anhedonia was associated with visual network hyperconnectivity and expansion of the visual, dorsal attention, and default networks. Additionally, anhedonia was associated with decreased between-network connectivity among default, salience, dorsal attention, somatomotor, and visual networks. Findings suggest that anhedonia is associated with aberrant connectivity and structural alterations in resting-state networks that contribute to impairments in reward learning, low motivation, and negativity bias characteristic of depression. Results reveal dissociable effects of anhedonia on resting-state network dynamics, characterizing possible neurocircuit mechanisms for intervention.

Children with Attention Deficit Hyperactivity Disorder (ADHD) have prominent deficits in sustained attention that manifest as elevated intra-individual response variability and poor decision-making. Influential neurocognitive models have linked attentional fluctuations to aberrant brain dynamics, but these models have not been tested with computationally rigorous procedures. Here we use a Research Domain Criteria approach, drift-diffusion modeling of behavior, and a novel Bayesian Switching Dynamic System unsupervised learning algorithm, with ultrafast temporal resolution (490 ms) whole-brain task-fMRI data, to investigate latent brain state dynamics of salience, frontoparietal, and default mode networks and their relation to response variability, latent decision-making processes, and inattention. Our analyses revealed that occurrence of a task-optimal latent brain state predicted decreased intra-individual response variability and increased evidence accumulation related to decision-making. In contrast, occurrence and dwell time of a non-optimal latent brain state predicted inattention symptoms and furthermore, in a categorical analysis, distinguished children with ADHD from controls. Importantly, functional connectivity between salience and frontoparietal networks predicted rate of evidence accumulation to a decision threshold, whereas functional connectivity between salience and default mode networks predicted inattention. Taken together, our computational modeling reveals dissociable latent brain state features underlying response variability, impaired decision-making, and inattentional symptoms common to ADHD. Our findings provide novel insights into the neurobiology of attention deficits in children.

Objective: To test embedded symptom validity scales of the Neurobehavioral Symptom Inventory (NSI) as predictors of performance validity. Setting: A Veterans Affairs Level II TBI/Polytrauma outpatient care unit in the Midwestern United States. Participants: Veterans with a history of mild traumatic brain injury undergoing neuropsychological assessment as part of their routine care within the TBI/Polytrauma clinic. Design: Retrospective analysis of the existing clinical data. Main Measures: The NSI, the b Test, Test of Memory Malingering, Reliable Digit Span, California Verbal Learning Test-II Forced Choice. Results: Embedded NSI validity scales were positively correlated with number of performance validity test failures. Participants identified as invalid responders scored higher on embedded NSI validity scales than participants identified as valid responders. Using receiver operating characteristic analysis, the embedded NSI validity scales showed poor sensitivity and specificity for invalid responding using previously published cutoff scores. Only 1 scale differentiated valid from invalid responders better than chance. Conclusion: The embedded NSI validity scales' usefulness in predicting invalid neuropsychological performance validity was limited in this sample. Continued measurement of both symptom and performance validity in clinical settings involving traumatic brain injury treatment is recommended, as the present results support the existing research suggesting symptom validity tests and performance validity tests tap into related but ultimately distinct constructs.

BACKGROUND:Anxiety and stress reactivity are risk factors for the development of affective disorders. However, the behavioral and neurocircuit mechanisms that potentiate maladaptive emotion regulation are poorly understood. Neuroimaging studies have implicated the amygdala and dorsolateral prefrontal cortex (DLPFC) in emotion regulation, but how anxiety and stress alter their context-specific causal circuit interactions is not known. Here, we use computational modeling to inform affective pathophysiology, etiology, and neurocircuit targets for early intervention.METHODS:Forty-five children (10-11 years of age; 25 boys) reappraised aversive stimuli during functional magnetic resonance imaging scanning. Clinical measures of anxiety and stress were acquired for each child. Drift-diffusion modeling of behavioral data and causal circuit analysis of functional magnetic resonance imaging data, with a National Institute of Mental Health Research Domain Criteria approach, were used to characterize latent behavioral and neurocircuit decision-making dynamics driving emotion regulation.RESULTS:Children successfully reappraised negative responses to aversive stimuli. Drift-diffusion modeling revealed that emotion regulation was characterized by increased initial bias toward positive reactivity during viewing of aversive stimuli and increased drift rate, which captured evidence accumulation during emotion evaluation. Crucially, anxiety and stress reactivity impaired latent behavioral dynamics associated with reappraisal and decision making. Anxiety and stress increased dynamic casual influences from the right amygdala to DLPFC. In contrast, DLPFC, but not amygdala, reactivity was correlated with evidence accumulation and decision making during emotion reappraisal.CONCLUSIONS:Our findings provide new insights into how anxiety and stress in children impact decision making and amygdala-DLPFC signaling during emotion regulation, and uncover latent behavioral and neurocircuit mechanisms of early risk for psychopathology.