Combining neural and behavioral indicators in the assessment of internalizing psychopathology in children and adolescents

The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health

Childhood mental health problems are common, impairing, and can become chronic if left untreated. Children are not reliable reporters of their emotional and behavioral health, and caregivers often unintentionally under- or over-report child symptoms, making assessment challenging. Objective physiological and behavioral measures of emotional and behavioral health are emerging. However, these methods typically require specialized equipment and expertise in data and sensor engineering to administer and analyze. To address this challenge, we have developed the ChAMP (Childhood Assessment and Management of digital Phenotypes) System, which includes a mobile application for collecting movement and audio data during a battery of mood induction tasks and an open-source platform for extracting digital biomarkers. As proof of principle, we present ChAMP System data from 101 children 4-8 years old, with and without diagnosed mental health disorders. Machine learning models trained on these data detect the presence of specific disorders with 70-73% balanced accuracy, with similar results to clinical thresholds on established parent-report measures (63-82% balanced accuracy). Features favored in model architectures are described using Shapley Additive Explanations (SHAP). Canonical Correlation Analysis reveals moderate to strong associations between predictors of each disorder and associated symptom severity (r = .51-.83). The open-source ChAMP System provides clinically-relevant digital biomarkers that may later complement parent-report measures of emotional and behavioral health for detecting kids with underlying mental health conditions and lowers the barrier to entry for researchers interested in exploring digital phenotyping of childhood mental health.

The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health

Childhood mental health problems are common, impairing, and can become chronic if left untreated. Children are not reliable reporters of their emotional and behavioral health, and caregivers often unintentionally under- or over-report child symptoms, making assessment challenging. Objective physiological and behavioral measures of emotional and behavioral health are emerging. However, these methods typically require specialized equipment and expertise in data and sensor engineering to administer and analyze. To address this challenge, we have developed the ChAMP (Childhood Assessment and Management of digital Phenotypes) System, which includes a mobile application for collecting movement and audio data during a battery of mood induction tasks and an open-source platform for extracting digital biomarkers. As proof of principle, we present ChAMP System data from 101 children 4-8 years old, with and without diagnosed mental health disorders. Machine learning models trained on these data detect the presence of specific disorders with 70-73% balanced accuracy, with similar results to clinical thresholds on established parent-report measures (63-82% balanced accuracy). Features favored in model architectures are described using Shapley Additive Explanations (SHAP). Canonical Correlation Analysis reveals moderate to strong associations between predictors of each disorder and associated symptom severity (r = .51-.83). The open-source ChAMP System provides clinically-relevant digital biomarkers that may later complement parent-report measures of emotional and behavioral health for detecting kids with underlying mental health conditions and lowers the barrier to entry for researchers interested in exploring digital phenotyping of childhood mental health.

Stability, change, and reliable individual differences in electroencephalography measures: a lifespan perspective on progress and opportunities

Electroencephalographic (EEG) methods have great potential to serve both basic and clinical science approaches to understand individual differences in human neural function. Importantly, the psychometric properties of EEG data, such as internal consistency and test-retest reliability, constrain their ability to differentiate individuals successfully. Rapid and recent technological and computational advancements in EEG research make it timely to revisit the topic of psychometric reliability in the context of individual difference analyses. Moreover, pediatric and clinical samples provide some of the most salient and urgent opportunities to apply individual difference approaches, but the changes these populations experience over time also provide unique challenges from a psychometric perspective. Here we take a developmental neuroscience perspective to consider progress and new opportunities for parsing the reliability and stability of individual differences in EEG measurements across the lifespan. We first conceptually map the different profiles of measurement reliability expected for different types of individual difference analyses over the lifespan. Next, we summarize and evaluate the state of the field's empirical knowledge and need for testing measurement reliability, both internal consistency and test-retest reliability, across EEG measures of power, event-related potentials, nonlinearity, and functional connectivity across ages. Finally, we highlight how standardized pre-processing software for EEG denoising and empirical metrics of individual data quality may be used to further improve EEG-based individual differences research moving forward. We also include recommendations and resources throughout that individual researchers can implement to improve the utility and reproducibility of individual differences analyses with EEG across the lifespan.

UVM KID Study: Identifying Multimodal Features and Optimizing Wearable Instrumentation to Detect Child Anxiety

Anxiety and depression, collectively known as internalizing disorders, begin as early as the preschool years and impact nearly 1 out of every 5 children. Left undiagnosed and untreated, childhood internalizing disorders predict later health problems including substance abuse, development of comorbid psychopathology, increased risk for suicide, and substantial functional impairment. Current diagnostic procedures require access to clinical experts, take considerable time to complete, and inherently assume that child symptoms are observable by caregivers. Multi-modal wearable sensors may enable development of rapid point-of-care diagnostics that address these challenges. Building on our prior work, here we present an assessment battery for the development of a digital phenotype for internalizing disorders in young children and an early feasibility case study of multi-modal wearable sensor data from two participants, one of whom has been clinically diagnosed with an internalizing disorder. Results lend support that sacral movement responses and R-R interval during a short stress-induction task may facilitate child diagnosis. Multi-modal sensors measuring movement and surface biopotentials of the chest and trapezius are also shown to have significant redundancy, introducing the potential for sensor optimization moving forward. Future work aims to further optimize sensor placement, signals, features, and assessments to enable deployment in clinical practice. Clinical Relevance- This work considers the development and optimization of technologies for improving the identification of children with internalizing disorders.

Network Diffusion Embedding Reveals Transdiagnostic Subnetwork Disruption and Potential Treatment Targets in Internalizing Psychopathologies

Network diffusion models are a common and powerful way to study the propagation of information through a complex system and they offer straightforward approaches for studying multimodal brain network data. We developed an analytic framework to identify brain subnetworks with perturbed information diffusion capacity using the structural basis that best maps to resting state functional connectivity and applied it towards a heterogeneous dataset of internalizing psychopathologies (IPs), a set of psychiatric conditions in which similar brain network deficits are found across the swath of the disorders, but a unifying neuropathological substrate for transdiagnostic symptom expression is currently unknown. This research provides preliminary evidence of a transdiagnostic brain subnetwork deficit characterized by information diffusion impairment of the right area 8BM, a key brain region involved in organizing a broad spectrum of cognitive tasks, which may underlie previously reported dysfunction of multiple brain circuits in the IPs. We also demonstrate that models of neuromodulation involving targeting this brain region normalize IP diffusion dynamics towards those of healthy controls. These analyses provide a framework for multimodal methods that identify both brain subnetworks with disrupted information diffusion and potential targets of these subnetworks for therapeutic neuromodulatory intervention based on previously well-characterized methodology.

On the relationship between the error-related negativity and anxiety in children and adolescents: From a neural marker to a novel target for intervention

The current review focuses on our work on the relationship between the error-related negativity (i.e., ERN) and anxiety in children and adolescents. The ERN is an event-related potential (ERP) that appears as a negative deflection in the ERP waveform when individuals make errors and has been found to be increased in anxious individuals. We, and others, have extended this work into developmental populations, finding that the ERN can be measured reliably in children and that the ERN is increased among clinically anxious youth. Furthermore, we have found that the ERN predicts risk for increases in anxiety across development, among healthy and clinically anxious children. We have done work to elucidate what psychological phenomena the increased ERN among anxious children may reflect by creating a self-report measure of error sensitivity (i.e., the Child Error Sensitivity Index) that relates to the ERN. Moreover, we review our work on parenting and the ERN, which suggests that harsh or critical parenting styles may potentiate the ERN in offspring. And, building on these findings, we discuss our recent work to develop novel, computerized intervention strategies to reduce the ERN and thereby risk for anxiety.

Digital Phenotype for Childhood Internalizing Disorders: Less Positive Play and Promise for a Brief Assessment Battery

Childhood internalizing disorders, like anxiety and depression, are common, impairing, and difficult to detect. Universal childhood mental health screening has been recommended, but new technologies are needed to provide objective detection. Instrumented mood induction tasks, designed to press children for specific behavioral responses, have emerged as means for detecting childhood internalizing psychopathology. In our previous work, we leveraged machine learning to identify digital phenotypes of childhood internalizing psychopathology from movement and voice data collected during negative valence tasks (pressing for anxiety and fear). In this work, we develop a digital phenotype for childhood internalizing disorders based on wearable inertial sensor data recorded from a Positive Valence task during which a child plays with bubbles. We find that a phenotype derived from features that capture reward responsiveness is able to accurately detect children with underlying internalizing psychopathology (AUC = 0.81). In so doing, we explore the impact of a variety of feature sets computed from wearable sensors deployed to two body locations on phenotype performance across two phases of the task. We further consider this novel digital phenotype in the context of our previous Negative Valence digital phenotypes and find that each task brings unique information to the problem of detecting childhood internalizing psychopathology, capturing different problems and disorder subtypes. Collectively, these results provide preliminary evidence for a mood induction task battery to develop a novel diagnostic for childhood internalizing disorders.

The error-related negativity as a neuromarker of risk or resilience in young children

INTRODUCTION

The error-related negativity (ERN) is a neural response that reflects error monitoring. Contradictorily, an enlarged (more negative) ERN has been cited as both a risk factor and a protective factor, which hinders its utility as a predictive indicator. The aim of the current study was to examine the associations between ERN measured in early childhood with the development of cognitive control (CC), emotion regulation, and internalizing/externalizing symptoms over 1-2 years.

METHODS

When children were ages 5-7, EEG was collected during a Go/No-Go task. A subset of the original participants (n = 30) were selected based on their baseline ERN in an extreme-case design: half with high-amplitude ERN, matched by age and sex with another group with low-amplitude ERN.

RESULTS

At follow-up, children in the High-Amplitude group showed better executive function, less self-reported anxiety and depression, less affect dysregulation, more parent-rated CC, less lability/negativity, and fewer parent-reported externalizing problems. Many results held even when accounting for baseline levels. Further, emotion dysregulation mediated the relationship between the ERN and both anxiety and externalizing problems, while CC mediated the ERN's relationship with externalizing problems only.

CONCLUSIONS

These results can inform identification and intervention efforts for children at risk for psychopathology.

Incorporating neurophysiological measures into clinical assessments: Fundamental challenges and a strategy for addressing them

Recent scientific initiatives have called for increased use of neurobiological variables in clinical and other applied assessments. However, the task of incorporating neural measures into psychological assessments entails significant methodological challenges that have not been effectively addressed to date. As a result, neurophysiological measures remain underutilized in clinical and applied assessments, and formal procedures for integrating such measures with report-based measures are lacking. In this article, we discuss major methodological issues that have impeded progress in this direction, and propose a systematic research strategy for integrating neurophysiological measures into psychological assessment protocols. The strategy we propose is an iterative psychoneurometric approach that provides a means to establish multimethod (MM) measurement models for core biobehavioral traits that influence functioning across diverse areas of life. We provide a detailed illustration of a MM model for one such trait, inhibitory control (inhibition-disinhibition), and highlight work being done to develop counterpart models for other biobehavioral traits (i.e., threat sensitivity, reward sensitivity, affiliative capacity). We discuss how these measurement models can be refined and extended through use of already existing data sets, and outline steps that can be taken to establish norms for MM assessments and optimize the feasibility of their use in everyday practice. We believe this model-oriented strategy can provide a viable pathway toward effective use of neurophysiological measures in routine clinical assessments. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Feedback-related neurophysiology in children and their parents: Developmental differences, familial transmission, and relationship to error-monitoring

The feedback negativity (FN) and reward positivity (RewP) are event-related brain potentials (ERPs) that follow the presentation of negative and positive feedback information, respectively, and have become the focus of recent research on psychopathology because of their associations with symptom severity of and risk for depression. We advanced our understanding of these feedback-related ERPs by examining developmental differences, familial transmission, and associations with error-monitoring ERPs. Parents and their children completed parallel, developmentally-tailored guessing and go/no-go tasks while feedback- and error-related ERPs were measured. We found that the Δ FN and RewP amplitudes increased with age and were larger in males than females among the child participants. The RewP also demonstrated familial transmission between fathers and their children. Finally, the FN and RewP were associated with error-related ERPs in children and adults, albeit in different ways. The current findings demonstrate that the FN and RewP have promise as developmentally-sensitive neural markers of reward and action monitoring processes associated with risk for psychopathology.

Wearable sensors detect childhood internalizing disorders during mood induction task

There is a significant need to develop objective measures for identifying children under the age of 8 who have anxiety and depression. If left untreated, early internalizing symptoms can lead to adolescent and adult internalizing disorders as well as comorbidity which can yield significant health problems later in life including increased risk for suicide. To this end, we propose the use of an instrumented fear induction task for identifying children with internalizing disorders, and demonstrate its efficacy in a sample of 63 children between the ages of 3 and 7. In so doing, we extract objective measures that capture the full six degree-of-freedom movement of a child using data from a belt-worn inertial measurement unit (IMU) and relate them to behavioral fear codes, parent-reported child symptoms and clinician-rated child internalizing diagnoses. We find that IMU motion data, but not behavioral codes, are associated with parent-reported child symptoms and clinician-reported child internalizing diagnosis in this sample. These results demonstrate that IMU motion data are sensitive to behaviors indicative of child psychopathology. Moreover, the proposed IMU-based approach has increased feasibility of collection and processing compared to behavioral codes, and therefore should be explored further in future studies.

Brain-behavior relationships in externalizing: P3 amplitude reduction reflects deficient inhibitory control

The use of endophenotypes to classify individuals at risk for or suffering from psychopathology has been criticized for lacking specificity and predictive utility. This issue is apparent in research on externalizing, a heritable predisposition to disinhibitory psychopathology and personality traits. Numerous studies have shown that P3 amplitude reduction (P3AR) reliably reflects externalizing, implicating P3AR as a candidate endophenotype for externalizing psychopathology. However, this endophenotype has not been connected directly to a key deficit in executive function (e.g., inhibitory control) commonly related to externalizing. Using a modified oddball task in a sample (N=74) of at-risk adolescents and young adults, we examined the associations among externalizing, P3AR, and inhibitory control. We also examined the associations of P3AR and inhibitory control with frequency of real-world disinhibited behavior. Results indicated that externalizing related to P3AR, which in turn related to deficient inhibitory control. Additionally, there were both unique and interactive associations of P3 amplitude and inhibitory control with indicators of real-world behavior. These findings provide the first direct evidence that P3AR reflects deficits in inhibitory control, thus linking this externalizing-related endophenotype to a specific cognitive process. Moreover, the results highlight the value of considering psychobiological measures alongside behavioral measures for indexing risk for externalizing behavior and psychopathology.

Movements Indicate Threat Response Phases in Children at Risk for Anxiety

Temporal phases of threat response, including potential threat (anxiety), acute threat (startle, fear), and post-threat response modulation, have been identified as the underlying markers of anxiety disorders. Objective measures of response during these phases may help identify children at risk for anxiety; however, the complexity of current assessment techniques prevent their adoption in many research and clinical contexts. We propose an alternative technology, an inertial measurement unit (IMU), that enables noninvasive measurement of the movements associated with threat response, and test its ability to detect threat response phases in young children at a heightened risk for developing anxiety. We quantified the motion of 18 children (3-7 years old) during an anxiety-/fear-provoking behavioral task using an IMU. Specifically, measurements from a single IMU secured to the child's waist were used to extract root-mean-square acceleration and angular velocity in the horizontal and vertical directions, and tilt and yaw range of motion during each threat response phase. IMU measurements detected expected differences in child motion by threat phase. Additionally, potential threat motion was positively correlated to familial anxiety risk, startle range of motion was positively correlated with child internalizing symptoms, and response modulation motion was negatively correlated to familial anxiety risk. Results suggest differential theory-driven threat response phases and support previous literature connecting maternal child risk to anxiety with behavioral measures using more feasible objective methods. This is the first study demonstrating the utility of an IMU for characterizing the motion of young children to mark the phases of threat response modulation. The technique provides a novel and objective measure of threat response for mental health researchers.

A biomarker of anxiety in children and adolescents: A review focusing on the error-related negativity (ERN) and anxiety across development

Background

Anxiety disorders are the most common form of psychopathology and often begin early in development. Therefore, there is interest in identifying neural biomarkers that characterize pathways leading to anxiety disorders early in the course of development. A substantial amount of work focuses on the error-related negativity (ERN) as a biomarker of anxiety. While two previous reviews have focused on the relationship of the ERN and anxiety in adults, no previous review has focused on this issue in children and adolescents.

Results and conclusions

Overall, 22 studies were included in the current review. A number of patterns emerged, including: 1.) The ERN is enhanced in clinically anxious children at all ages (6–18 years old), regardless of the task used to measure the ERN. 2.) Studies focusing on anxiety symptoms and temperamental fear suggest that the relationship between the ERN and normative anxiety may change across development. 3.) The ERN can predict the onset of anxiety disorders across different developmental periods. 4.) The ERN relates to other markers of risk for anxiety (e.g., aversive startle potentiation) in children and adolescents.

Trait liabilities and specific promotive processes in psychopathology: The example of suicidal behavior

BACKGROUND

The RDoC matrix framework calls for investigation of mental health problems through analysis of core biobehavioral processes quantified and studied across multiple domains of measurement. Critics have raised concerns about RDoC, including overemphasis on biological concepts/measures and disregard for the principle of multifinality, which holds that identical biological predispositions can give rise to differing behavioral outcomes. The current work illustrates an ontogenetic process approach to addressing these concerns, focusing on biobehavioral traits corresponding to RDoC constructs as predictors, and suicidal behavior as the outcome variable.

METHOD

Data were collected from a young adult sample (N=105), preselected to enhance rates of suicidality. Participants completed self-report measures of traits (threat sensitivity, response inhibition) and suicide-specific processes.

RESULTS

We show that previously reported associations for traits of threat sensitivity and weak inhibitory control with suicidal behavior are mediated by more specific suicide-promoting processes-namely, thwarted belongingness, perceived burdensomeness, and capability for suicide.

LIMITATIONS

The sample was relatively small and the data were cross-sectional, limiting conclusions that can be drawn from the mediation analyses.

CONCLUSIONS

Given prior research documenting neurophysiological as well as psychological bases to these trait dispositions, the current work sets the stage for an intensive RDoC-oriented investigation of suicidal tendencies in which both traits and suicide-promoting processes are quantified using indicators from different domains of measurement. More broadly, this work illustrates how an RDoC research approach can contribute to a nuanced understanding of specific clinical problems, through consideration of how general biobehavioral liabilities interface with distinct problem-promoting processes.

Six Years of Research on the National Institute of Mental Health's Research Domain Criteria (RDoC) Initiative: A Systematic Review

Six years have passed since the National Institute of Mental Health (NIMH) in the United States launched the Research Domain Criteria (RDoC) initiative. The RDoC introduces a framework for research on the biology of mental illness that integrates research findings across multiple levels of information. The framework outlines constructs that represent specific quantifiable dimensions of behavior (e.g., responses to acute threat, cognitive control) and corresponding units of analysis that can be used to study the constructs, beginning at the levels of genes, molecules, cells, circuits and physiology, and moving up to behaviors and self-reports. In this systematic review, a literature search was conducted to synthesize empirical research published since the proposal of the framework that incorporated the RDoC. Forty-eight peer-reviewed scholarly articles met eligibility criteria for the review. Studies differed according to whether they analyzed RDoC constructs and units of analysis within vs. between clinically-diagnosed and non-psychiatric samples. The most commonly studied constructs were subsumed within the domains of Negative Valence Systems, Positive Valence Systems and Cognitive Systems, providing initial results which primarily connected genetics, brain circuits and physiology research findings with behavior and self-reports. Prospects for future research adopting the RDoC matrix and utilizing a dimensional approach to studying the biology of mental illness are discussed.

Future Research Directions in the Positive Valence Systems: Measurement, Development, and Implications for Youth Unipolar Depression

The Positive Valence Systems (PVS) have been introduced by the National Institute of Mental Health as a domain to help organize multiple constructs focusing on reward-seeking behaviors. However, the initial working model for this domain is strongly influenced by adult constructs and measures. Thus, the present review focuses on extending the PVS into a developmental context. Specifically, the review provides some hypotheses about the structure of the PVS, how PVS components may change throughout development, how family history of depression may influence PVS development, and potential means of intervening on PVS function to reduce onsets of depression. Future research needs in each of these areas are highlighted.

Error-related negativity (ERN) and sustained threat: Conceptual framework and empirical evaluation in an adolescent sample

The error-related negativity (ERN) currently appears as a physiological measure in relation to three Research Domain Criteria (RDoC) constructs: Cognitive Control, Sustained Threat, and Reward Learning. We propose a conceptual model in which variance in the ERN reflects individual differences in the degree to which errors are evaluated as threatening. We also discuss evidence for the placement of the ERN in the "Sustained Threat" construct, as well as evidence that the ERN may more specifically reflect sensitivity to endogenous threat. Following this, we present data from a sample of 515 adolescent females demonstrating a larger ERN in relation to self-reported checking behaviors, but only in older adolescents, suggesting that sensitivity to internal threat and the ERN-checking relationship may follow a developmental course as adolescents develop behavioral control. In contrast, depressive symptoms were linked to a smaller ERN, and this association was invariant with respect to age. Collectively, these data suggest that the magnitude of the ERN is sensitive both to specific anxiety-related processes and depression, in opposing directions that may reflect variation in internal threat sensitivity. We discuss directions for future research, as well as ways in which findings for the ERN complement and challenge aspects of the current RDoC matrix.

Psychobiological operationalization of RDoC constructs: Methodological and conceptual opportunities and challenges

NIMH's Research Domain Criteria (RDoC) project seeks to advance the diagnosis, prevention, and treatment of mental disorders by promoting psychobiological research on dimensional constructs that might cut across traditional diagnostic boundaries (Kozak & Cuthbert, ). At the core of this approach is the notion that these dimensional constructs can be assessed across different units of analysis (e.g., genes, physiology, behavior), enriching the constructs and providing more complete explanations of clinical problems. While the conceptual aspects of RDoC have been discussed in several prior papers, its methodological aspects have received comparatively less attention. For example, how to integrate data from different units of analysis has been relatively unclear. Here, we discuss one means of psychobiologically operationalizing RDoC constructs across different units of analysis (the psychoneurometric approach; Yancey et al., ), highlighting ways in which this approach might be refined in future iterations. We conclude that there is much to be learned from this technique; however, greater attention to scale-development methods and to psychometrics will likely benefit this and other methodological approaches to combining measurements across multiple units of analysis.

Neurophysiological evidence of an association between cognitive control and defensive reactivity processes in young children

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ERN, Pe, startle reflex, and parietal asymmetry were measured in young children.

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Reduced ERN was related to a larger startle and greater right parietal activity.

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Age predicted smaller startle, larger ERN, and better behavioral performance.

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Age did not moderate the association between ERN and startle.

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Age did not moderate the association between ERN and parietal asymmetry.

Interactions between cognitive control and affective processes, such as defensive reactivity, are intimately involved in healthy and unhealthy human development. However, cognitive control and defensive reactivity processes are often studied in isolation and rarely examined in early childhood. To address these gaps, we examined the relationships between multiple neurophysiological measures of cognitive control and defensive reactivity in young children. Specifically, we assessed two event-related potentials thought to index cognitive control processes – the error-related negativity (ERN) and error positivity (Pe) – measured across two tasks, and two markers of defensive reactivity processes – startle reflex and resting parietal asymmetry – in a sample of 3- to 7-year old children. Results revealed that measures of cognitive control and defensive reactivity were related such that evidence of poor cognitive control (smaller ERN) was associated with high defensive reactivity (larger startle and greater right relative to left parietal activity). The strength of associations between the ERN and measures of defensive reactivity did not vary by age, providing evidence that poor cognitive control relates to greater defensive reactivity across early childhood years.

Introduction to the special issue: toward implementing physiological measures in clinical child and adolescent assessments

The National Institute of Mental Health recently launched the Research Domain Criteria (RDoC). The RDoC is an initiative to improve classification of mental health concerns by promoting research on the brain mechanisms underlying these concerns, with the ultimate goal of developing interventions that target these brain mechanisms. A key focus of RDoC involves opening new lines of research examining patients' responses on biological measures. The RDoC presents unique challenges to mental health professionals who work with children and adolescents. Indeed, mental health professionals rarely integrate biological measures into clinical assessments. Thus, RDoC's ability to improve patient care rests, in part, on the development of strategies for implementing biological measures within mental health assessments. Further, mental health professionals already carry out comprehensive assessments that frequently yield inconsistent findings. These inconsistencies have historically posed challenges to interpreting research findings as well as assessment outcomes in practice settings. In this introductory article, we review key issues that informed the development of a special issue of articles demonstrating methods for implementing low-cost measures of physiological functioning in clinical child and adolescent assessments. We also outline a conceptual framework, informed by theoretical work on using and interpreting multiple informants' clinical reports (De Los Reyes, Thomas, Goodman, & Kundey, 2013 ), to guide hypothesis testing when using physiological measures within clinical child and adolescent assessments. This special issue and the conceptual model described in this article may open up new lines of research testing paradigms for implementing clinically feasible physiological measures in clinical child and adolescent assessments.

Neurobehavioral Traits as Transdiagnostic Predictors of Clinical Problems

The National Institute of Mental Health Research Domain Criteria initiative (Insel et al., 2010) calls for a focus on biologically meaningful dimensional constructs in the study of clinical problems. Examples are needed of how Research Domain Criteria constructs can be linked to clinical problems. We examined how two such constructs, threat sensitivity (THT+) and weak inhibitory control (INH-), operationalized using scale measures of fear/fearlessness and inhibition/disinhibition dimensions from established structural models, predicted symptoms of multiple Diagnostic and Statistical Manual of Mental Disorders (4th edition) clinical disorders in 471 community adults. Robust relationships with internalizing disorder symptoms were evident for both trait variables, with THT+ more predictive of fear disorder symptoms and INH- more predictive of distress disorder symptoms. For substance-related problems, prediction was evident only for INH-. Additionally, interactive effects of THT+ and INH- were found for distress disorders, and to a lesser extent, fear disorders. Given their well-established physiological correlates, these dispositional variables represent prime targets for combined psychometric-neurophysiological assessment of broad liabilities to multiple forms of psychopathology.

Voluntary modulation of anterior cingulate response to negative feedback

Anterior cingulate and medial frontal cortex (dACC/mFC) response to negative feedback represents the actions of a generalized error-monitoring system critical for the management of goal-directed behavior. Magnitude of dACC/mFC response to negative feedback correlates with levels of post-feedback behavioral change, and with proficiency of operant learning processes. With this in mind, it follows that an ability to alter dACC/mFC response to negative feedback may lead to representative changes in operant learning proficiency. To this end, the present study investigated the extent to which healthy individuals would show modulation of their dACC/mFC response when instructed to try to either maximize or minimize their neural response to the presentation of contingent negative feedback. Participants performed multiple runs of a standard time-estimation task, during which they received feedback regarding their ability to accurately estimate a one-second duration. On Watch runs, participants were simply instructed to try to estimate as closely as possible the one second duration. On Increase and Decrease runs, participants performed the same task, but were instructed to “try to increase [decrease] their brain's response every time they received negative feedback”. Results indicated that participants showed changes in dACC/mFC response under these differing instructional conditions: dACC/mFC activity following negative feedback was higher in the Increase condition, and dACC activity trended lower in the Decrease condition, compared to the Watch condition. Moreover, dACC activity correlated with post-feedback performance adjustments, and these adjustments were highest in the Increase condition. Potential implications for neuromodulation and facilitated learning are discussed.