Neuroscience-informed classification of prevention interventions in substance use disorders: An RDoC-based approach

Neuroscience has contributed to uncover the mechanisms underpinning substance use disorders (SUD). The next frontier is to leverage these mechanisms as active targets to create more effective interventions for SUD treatment and prevention. Recent large-scale cohort studies from early childhood are generating multiple levels of neuroscience-based information with the potential to inform the development and refinement of future preventive strategies. However, there are still no available well-recognized frameworks to guide the integration of these multi-level datasets into prevention interventions. The Research Domain Criteria (RDoC) provides a neuroscience-based multi-system framework that is well suited to facilitate translation of neurobiological mechanisms into behavioral domains amenable to preventative interventions. We propose a novel RDoC-based framework for prevention science and adapted the framework for the existing preventive interventions. From a systematic review of randomized controlled trials using a person-centered drug/alcohol preventive approach for adolescents, we identified 22 unique preventive interventions. By teasing apart these 22 interventions into the RDoC domains, we proposed distinct neurocognitive trajectories which have been recognized as precursors or risk factors for SUDs, to be targeted, engaged and modified for effective addiction prevention.

Lifetime history of major depressive disorder is associated with decreased reward learning: Evidence from a novel online version of the probabilistic reward task

BACKGROUND

The Probabilistic Reward Task (PRT) is a signal detection task that assesses reward learning. In laboratory versions of the task, individuals with current or past major depressive disorder (MDD) were characterized by reduced response bias towards a more frequently rewarded stimuli, compared to controls. Our main goal was to develop and validate a novel online version of the PRT, and, in exploratory analyses, evaluate whether lifetime history of depression was associated with blunted reward learning.

METHODS

429 participants recruited via CloudResearch completed questionnaires assessing psychiatric history and an online PRT featuring visually appealing stimuli. 108 participants reported either current or past diagnosis of MDD (lifetime MDD group), and were compared to 321 without lifetime MDD.

RESULTS

Participants showed overall increase in response bias, validating the online PRT. Females with lifetime MDD (N = 43), compared to females without prior history of MDD (N = 173), exhibited blunted response bias towards the more frequently rewarded stimulus (i.e., reduced reward learning).

LIMITATIONS

Participants did not undergo a structured clinical interview, thus we cannot confirm whether they met full diagnostic criteria for depression.

CONCLUSIONS

The online PRT yielded similar psychometric properties as laboratory versions of the task. In exploratory analyses, females with lifetime MDD showed a lower propensity to modulate behavior as a function of rewards, which might contribute to heightened vulnerability for developing MDD in females. Future studies should consider social, cultural, and neurobiological factors contributing to sex differences in reward responsiveness and how factors may relate to disease prognosis and treatment outcomes.

Precision psychiatry and Research Domain Criteria: Implications for clinical trials and future practice

Psychiatric disorders are associated with significant social and economic burdens, many of which are related to issues with current diagnosis and treatments. The coronavirus (COVID-19) pandemic is estimated to have increased the prevalence and burden of major depressive and anxiety disorders, indicating an urgent need to strengthen mental health systems globally. To date, current approaches adopted in drug discovery and development for psychiatric disorders have been relatively unsuccessful. Precision psychiatry aims to tailor healthcare more closely to the needs of individual patients and, when informed by neuroscience, can offer the opportunity to improve the accuracy of disease classification, treatment decisions, and prevention efforts. In this review, we highlight the growing global interest in precision psychiatry and the potential for the National Institute of Health-devised Research Domain Criteria (RDoC) to facilitate the implementation of transdiagnostic and improved treatment approaches. The need for current psychiatric nosology to evolve with recent scientific advancements and increase awareness in emerging investigators/clinicians of the value of this approach is essential. Finally, we examine current challenges and future opportunities of adopting the RDoC-associated translational and transdiagnostic approaches in clinical studies, acknowledging that the strength of RDoC is that they form a dynamic framework of guiding principles that is intended to evolve continuously with scientific developments into the future. A collaborative approach that recruits expertise from multiple disciplines, while also considering the patient perspective, is needed to pave the way for precision psychiatry that can improve the prognosis and quality of life of psychiatric patients.

Translational In Vivo Assays in Behavioral Biology

The failure of preclinical research to advance successful candidate medications in psychiatry has created a paradigmatic crisis in psychiatry. The Research Domain Criteria (RDoC) initiative was designed to remedy this situation with a neuroscience-based approach that employs multimodal and cross-species in vivo methodology to increase the probability of translational findings and, consequently, drug discovery. The present review underscores the feasibility of this methodological approach by briefly reviewing, first, the use of multidimensional and cross-species methodologies in traditional behavioral pharmacology and, subsequently, the utility of this approach in contemporary neuroimaging and electrophysiology research-with a focus on the value of functionally homologous studies in nonhuman and human subjects. The final section provides a brief review of the RDoC, with a focus on the potential strengths and weaknesses of its domain-based underpinnings. Optimistically, this mechanistic and multidimensional approach in neuropsychiatric research will lead to novel therapeutics for the management of neuropsychiatric disorders.

Multivariate Associations Among White Matter, Neurocognition, and Social Cognition Across Individuals With Schizophrenia Spectrum Disorders and Healthy Controls

BACKGROUND AND HYPOTHESIS

Neurocognitive and social cognitive abilities are important contributors to functional outcomes in schizophrenia spectrum disorders (SSDs). An unanswered question of considerable interest is whether neurocognitive and social cognitive deficits arise from overlapping or distinct white matter impairment(s).

STUDY DESIGN

We sought to fill this gap, by harnessing a large sample of individuals from the multi-center Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) dataset, unique in its collection of advanced diffusion imaging and an extensive battery of cognitive assessments. We applied canonical correlation analysis to estimates of white matter microstructure, and cognitive performance, across people with and without an SSD.

STUDY RESULTS

Our results established that white matter circuitry is dimensionally and strongly related to both neurocognition and social cognition, and that microstructure of the uncinate fasciculus and the rostral body of the corpus callosum may assume a "privileged role" subserving both. Further, we found that participant-wise estimates of white matter microstructure, weighted by cognitive performance, were largely consistent with participants' categorical diagnosis, and predictive of (cross-sectional) functional outcomes.

CONCLUSIONS

The demonstrated strength of the relationship between white matter circuitry and neurocognition and social cognition underscores the potential for using relationships among these variables to identify biomarkers of functioning, with potential prognostic and therapeutic implications.

Pharmacological characterisation of the effort for reward task as a measure of motivation for reward in male mice

RATIONALE

Motivational deficits are a common symptom shared across multiple psychiatric and neurodegenerative disorders. Effort-based decision-making tasks are a translatable method for assessing motivational state. Much of the preclinical validation of the task derives from acute pharmacological manipulations in rats. However, mice currently offer a greater genetic toolkit to study risk genes and phenotypic models. Despite this, there is limited characterisation of their behaviour in this type of motivation task.

OBJECTIVES

Here, we investigate the effort for reward (EfR) task as a measure of motivational state in mice using drugs previously shown to modulate effort-based decision-making in rats and humans.

METHOD

Using male C57bl/6j mice, we test the effects of drugs which modulate DA transmission. We also test the effects of CP101-606 which does not act directly via DA modulation but has been shown to exert beneficial effects on motivational state. Finally, we test the sensitivity of the task to a chronic corticosterone (CORT) treatment.

RESULTS

Amphetamine, methylphenidate, and CP101606 in mice increased high-effort responses for high-value reward, while administration of haloperidol decreased high-effort responses. Surprisingly, tetrabenazine had no effect at the doses tested. Chronic, low-dose CORT consumption did not alter task performance.

CONCLUSION

These data suggest that the EfR task is sensitive to acute dopaminergic modulation and NR2B selective antagonism in mice. However, it may lack sensitivity to non-acute phenotypic models. Further work is required to demonstrate the utility of the task in this context.

Using the Research Domain Criteria as a framework to integrate psychophysiological findings into stress management and psychotherapy interventions

Research on the psychophysiology of stress is expanding rapidly, but the field lacks a clear integrative framework to help translate research findings into empirically supported stress interventions. The Research Domain Criteria (RDoC) is an excellent candidate to explore as a framework to integrate stress research. The RDoC framework is a dimensional, multi-modal approach to psychopathology proposed as an alternative to categorical approaches used by the International Classification of Diseases (ICD) and the Diagnostic and Statistical Manual (DSM). The goal of this paper is to explore the RDoC as a framework to integrate psychophysiology research into therapeutic interventions for stress. The RDoC consists of six domains: negative valence systems, positive valence systems, cognitive systems, social processes systems, arousal/regulatory systems, and sensorimotor systems, and provides an excellent structure for integrating information from multiple levels of functioning including physiology, behavior, and self-report, as well as genes, molecules, cells, and brain circuits. Integrating psychophysiological research on stress using the RDoC framework can direct and amplify stress management and psychotherapeutic interventions. First, the RDoC provides a clear foundation for conceptualizing the stress response in terms of important concepts such as allostasis and adaptation. In this perspective, the terms "allostatic response" or "adaptation response" are more descriptive terms than "stress response" in understanding bodily responses to life threats and challenges. Second, psychophysiological approaches can be used in the context of modalities such as biofeedback and mindfulness to both collect psychophysiological data and then integrate that data into a broader therapeutic framework. Heart rate variability (HRV) biofeedback is being used more frequently as part of a therapeutic intervention package with stress management and psychotherapy, and HRV data is also used to provide outcome evidence on the efficacy of treatment. Mindfulness practices are commonly used in combination with stress management and psychotherapy, and psychophysiological data (HRV, EEG, blood pressure, etc.) is often collected to explore and understand mind/body relationships. In conclusion, the lack of a clear framework to assess and understand mind/body functioning limits current stress research and interventions. The RDoC provides a strong framework to assess and integrate physiological and psychological data and improve stress interventions.

The associations of Positive and Negative Valence Systems, Cognitive Systems and Social Processes on disease severity in anxiety and depressive disorders

Background

Anxiety and depressive disorders share common features of mood dysfunctions. This has stimulated interest in transdiagnostic dimensional research as proposed by the Research Domain Criteria (RDoC) approach by the National Institute of Mental Health (NIMH) aiming to improve the understanding of underlying disease mechanisms. The purpose of this study was to investigate the processing of RDoC domains in relation to disease severity in order to identify latent disorder-specific as well as transdiagnostic indicators of disease severity in patients with anxiety and depressive disorders.

Methods

Within the German research network for mental disorders, 895 participants (n = 476 female, n = 602 anxiety disorder, n = 257 depressive disorder) were recruited for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) and included in this cross-sectional study. We performed incremental regression models to investigate the association of four RDoC domains on disease severity in patients with affective disorders: Positive (PVS) and Negative Valance System (NVS), Cognitive Systems (CS) and Social Processes (SP).

Results

The results confirmed a transdiagnostic relationship for all four domains, as we found significant main effects on disease severity within domain-specific models (PVS: β = -0.35; NVS: β = 0.39; CS: β = -0.12; SP: β = -0.32). We also found three significant interaction effects with main diagnosis showing a disease-specific association.

Limitations

The cross-sectional study design prevents causal conclusions. Further limitations include possible outliers and heteroskedasticity in all regression models which we appropriately controlled for.

Conclusion

Our key results show that symptom burden in anxiety and depressive disorders is associated with latent RDoC indicators in transdiagnostic and disease-specific ways.

Toward Precision Characterization and Treatment of Psychopathology: A Path Forward and Integrative Framework of the Hierarchical Taxonomy of Psychopathology and the Research Domain Criteria

A critical mission of psychological science is to conduct research that ultimately improves the lives of individuals who experience psychopathology. One important aspect of accomplishing this mission is increasing the likelihood that treatments will work for each person. I contend that treatment prognosis can be improved by moving toward a precision-medicine model. I advance a principle-driven framework for working toward these objectives. First, I synthesize the Hierarchical Taxonomy of Psychopathology and the Research Domain Criteria and demonstrate how integrating these models facilitates precision characterization of psychopathology. Second, I outline and demonstrate a systematic process for approaching treatment selection by leveraging precisely characterized representations of psychopathology. Finally, I advocate the research and clinical applications of this framework. Although clinical and psychological scientists are conducting exciting, multidisciplinary, and methodologically rigorous research in their respective domains, the impact of these pursuits will be maximized in the context of a unifying theoretical framework that supports a clear guiding mission.

Categorical and Dimensional Deficits in Hippocampal Subfields Among Schizophrenia, Obsessive-Compulsive Disorder, Bipolar Disorder, and Major Depressive Disorder

BACKGROUND

The hippocampus is a core region of interest for all major mental disorders, and its subfields implement distinctive functions. It is unclear whether the mental disorders exhibit common patterns of hippocampal impairments, and we lack knowledge on whether and how hippocampal subfields represent deficit spectra across mental disorders.

METHODS

Using brain images of 1123 individuals scanned on a single magnetic resonance imaging scanner, we examined the commonality, specificity, and symptom associations of the volume of hippocampal subfields across patients with schizophrenia, patients with obsessive-compulsive disorder, patients with bipolar disorder, patients with major depressive disorder, and healthy control subjects. We further performed a transdiagnostic analysis of the individual variability of the volume of hippocampal subfields to reflect cross-disease gradients in the hippocampus.

RESULTS

We found common and disease-specific abnormalities in a few hippocampal fields and identified 2 reliable transdiagnostic factors in the hippocampal subfields, each reflecting a spectrum of mental disorders. The plane spanned by the 2 most reliable factors provided a clearer view of hippocampal volume abnormality spectra among the major mental disorders. In addition, functional and genetic enrichment analyses supported the different roles of the 2 hippocampal factors in mental disorders.

CONCLUSIONS

The volume of hippocampal subfields reflected some commonality and specificity among the 3 major mental disorders. We propose a new pathophysiological dimensional view of the hippocampus, reflecting at least 2 spectra of mental disorders, suggesting multivariate links among the diseases. This work highlights the value of the complementary categorical and dimensional views of the hippocampal deficits in mental disorders.

Electrophysiological Studies of Reception of Facial Communication in Autism Spectrum Disorder and Schizophrenia

Autism spectrum disorder (ASD) and schizophrenia spectrum disorders (SZ) are characterized by difficulty with social cognition and atypical reception of facial communication - a key area in the Research Domain Criteria framework. To identify areas of overlap and dissociation between ASD and SZ, we review studies of event-related potentials (ERP) to faces across ASD and SZ populations, focusing on ERPs implicated in social perception: P100, N170, N250, and P300. There were many inconsistent findings across studies; however, replication was strongest for delayed N170 latency in ASD and attenuated N170 amplitude in SZ. These results highlight the challenges of replicating research findings in heterogeneous clinical populations and the need for transdiagnostic research that continuously quantifies behavior and neural activity across neurodevelopmental disorders.

Psychiatric diagnosis and treatment in the 21st century: paradigm shifts versus incremental integration

Psychiatry has always been characterized by a range of different models of and approaches to mental disorder, which have sometimes brought progress in clinical practice, but have often also been accompanied by critique from within and without the field. Psychiatric nosology has been a particular focus of debate in recent decades; successive editions of the DSM and ICD have strongly influenced both psychiatric practice and research, but have also led to assertions that psychiatry is in crisis, and to advocacy for entirely new paradigms for diagnosis and assessment. When thinking about etiology, many researchers currently refer to a biopsychosocial model, but this approach has received significant critique, being considered by some observers overly eclectic and vague. Despite the development of a range of evidence-based pharmacotherapies and psychotherapies, current evidence points to both a treatment gap and a research-practice gap in mental health. In this paper, after considering current clinical practice, we discuss some proposed novel perspectives that have recently achieved particular prominence and may significantly impact psychiatric practice and research in the future: clinical neuroscience and personalized pharmacotherapy; novel statistical approaches to psychiatric nosology, assessment and research; deinstitutionalization and community mental health care; the scale-up of evidence-based psychotherapy; digital phenotyping and digital therapies; and global mental health and task-sharing approaches. We consider the extent to which proposed transitions from current practices to novel approaches reflect hype or hope. Our review indicates that each of the novel perspectives contributes important insights that allow hope for the future, but also that each provides only a partial view, and that any promise of a paradigm shift for the field is not well grounded. We conclude that there have been crucial advances in psychiatric diagnosis and treatment in recent decades; that, despite this important progress, there is considerable need for further improvements in assessment and intervention; and that such improvements will likely not be achieved by any specific paradigm shifts in psychiatric practice and research, but rather by incremental progress and iterative integration.

Mapping Research Domain Criteria using a transdiagnostic mini-RDoC assessment in mental disorders: a confirmatory factor analysis

This study aimed to build on the relationship of well-established self-report and behavioral assessments to the latent constructs positive (PVS) and negative valence systems (NVS), cognitive systems (CS), and social processes (SP) of the Research Domain Criteria (RDoC) framework in a large transnosological population which cuts across DSM/ICD-10 disorder criteria categories. One thousand four hundred and thirty one participants (42.1% suffering from anxiety/fear-related, 18.2% from depressive, 7.9% from schizophrenia spectrum, 7.5% from bipolar, 3.4% from autism spectrum, 2.2% from other disorders, 18.4% healthy controls, and 0.2% with no diagnosis specified) recruited in studies within the German research network for mental disorders for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) were examined with a Mini-RDoC-Assessment including behavioral and self-report measures. The respective data was analyzed with confirmatory factor analysis (CFA) to delineate the underlying latent RDoC-structure. A revised four-factor model reflecting the core domains positive and negative valence systems as well as cognitive systems and social processes showed a good fit across this sample and showed significantly better fit compared to a one factor solution. The connections between the domains PVS, NVS and SP could be substantiated, indicating a universal latent structure spanning across known nosological entities. This study is the first to give an impression on the latent structure and intercorrelations between four core Research Domain Criteria in a transnosological sample. We emphasize the possibility of using already existing and well validated self-report and behavioral measurements to capture aspects of the latent structure informed by the RDoC matrix.

Revisiting the seven pillars of RDoC

BACKGROUND

In 2013, a few years after the launch of the National Institute of Mental Health's Research Domain Criteria (RDoC) initiative, Cuthbert and Insel published a paper titled "Toward the future of psychiatric diagnosis: the seven pillars of RDoC." The RDoC project is a translational research effort to encourage new ways of studying psychopathology through a focus on disruptions in normal functions (such as reward learning or attention) that are defined jointly by observable behavior and neurobiological measures. The paper outlined the principles of the RDoC research framework, including emphases on research that acquires data from multiple measurement classes to foster integrative analyses, adopts dimensional approaches, and employs novel methods for ascertaining participants and identifying valid subgroups.

DISCUSSION

To mark the first decade of the RDoC initiative, we revisit the seven pillars and highlight new research findings and updates to the framework that are related to each. This reappraisal emphasizes the flexible nature of the RDoC framework and its application in diverse areas of research, new findings related to the importance of developmental trajectories within and across neurobehavioral domains, and the value of computational approaches for clarifying complex multivariate relations among behavioral and neurobiological systems.

CONCLUSION

The seven pillars of RDoC have provided a foundation that has helped to guide a surge of new studies that have examined neurobehavioral domains related to mental disorders, in the service of informing future psychiatric nosology. Building on this footing, future areas of emphasis for the RDoC project will include studying central-peripheral interactions, developing novel approaches to phenotyping for genomic studies, and identifying new targets for clinical trial research to facilitate progress in precision psychiatry.

Research Domain Criteria (RDoC): Progress and Potential

The National Institute of Mental Health (NIMH) addressed in its 2008 Strategic Plan an emerging concern that the current diagnostic system was hampering translational research, as accumulating data suggested that disorder categories constituted heterogeneous syndromes rather than specific diseases. However, established practices in peer review placed high priority on extant disorders in evaluating grant applications for mental illness. To provide guidelines for alternative study designs, NIMH included a goal to develop new ways of studying psychopathology based on dimensions of measurable behavior and related neurobiological measures. The Research Domain Criteria (RDoC) project is the result, intended to build a literature that informs new conceptions of mental illness and future revisions to diagnostic manuals. The framework calls for the study of empirically-derived fundamental dimensions as characterized by related behavioral/psychological and neurobiological data (e.g., reward valuation, working memory). RDoC also emphasizes full-range dimensional approaches (from typical to increasingly abnormal), neurodevelopment and environmental effects, and research designs that integrate data across behavioral, biological, and self-report measures. This commentary provides an overview of the project's first decade and its potential future directions. RDoC remains grounded in experimental psychopathology perspectives, and its progress is strongly linked to psychological measurement and integrative approaches to brain-behavior relationships.

Klerman's "credo" reconsidered: neo-Kraepelinianism, Spitzer's views, and what we can learn from the past

In 1978, G. Klerman published an essay in which he named the then-nascent "neo-Kraepelinian" movement and formulated a "credo" of nine propositions expressing the movement's essential claims and aspirations. Klerman's essay appeared on the eve of the triumph of neo-Kraepelinian ideas in the DSM-III. However, this diagnostic system has subsequently come under attack, opening the way for competing proposals for the future of psychiatric nosology. To better understand what is at stake, in this paper I provide a close reading and consideration of Klerman's credo in light of the past forty years of research and reflection. The credo is placed in the context of two equally seminal publications in the same year, one by S. Guze, the leading neo-Kraepelinian theorist, and the other by R. Spitzer and J. Endicott, defining mental disorder. The divergences between Spitzer and standard neo-Kraepelinianism are highlighted and argued to be much more important than is generally realized. The analysis of Klerman's credo is also argued to have implications for how to satisfactorily resolve the current nosological ferment in psychiatry. In addition to issues such as creating descriptive syndromal diagnostic criteria, overthrowing psychoanalytic dominance of psychiatry, and making psychiatry more scientific, neo-Kraepelinians were deeply concerned with the conceptual issue of the nature of mental disorder and the defense of psychiatry's medical legitimacy in response to antipsychiatric criticisms. These issues cannot be ignored, and I argue that proposals currently on offer to replace the neo-Kraepelinian system, especially popular proposals to replace it with dimensional measures, fail to adequately address them.

Augmentation of Psychotherapy with Neurobiological Methods: Current State and Future Directions

BACKGROUND

Psychotherapy and pharmacotherapy are first-line treatments for mental disorders. Despite recent improvements, only approximately 50% of the patients reach sustained remission, indicating a need for novel developments. The main concept put forward in this systematic review and hypothesis article is the targeted co-administration of defined neurobiological interventions and specific psychotherapeutic techniques.

METHODS

We conducted a systematic literature search for randomized controlled trials comparing the efficacy of augmented psychotherapy to psychotherapy alone.

RESULTS

Thirty-five trials fulfilled the inclusion criteria. The majority (29 trials) used augmentation strategies such as D-cycloserine, yohimbine, or sleep to enhance the effects of exposure therapy for anxiety disorders. Fewer studies investigated noninvasive brain stimulation with the aim of improving cognitive control, psychedelic compounds with the aim of enhancing existentially oriented psychotherapy, and oxytocin to improve social communication during psychotherapy. Results demonstrate small augmentation effects for the enhancement of exposure therapy - however, some of the studies found negative results. Other methods are less thoroughly researched, and results are mixed.

CONCLUSIONS

This approach provides an open matrix for further research and has the potential to systematically guide future studies.

Quantifying Distances Between Non-Elliptical Clusters to Enhance the Identification of Meaningful Emotional Reactivity Subtypes

Coordinated emotional responses across psychophysiological and subjective indices is a cornerstone of adaptive emotional functioning. Using clustering to identify cross-diagnostic subgroups with similar emotion response profiles may suggest novel underlying mechanisms and treatments.However, many psychophysiological measures are non-normal even in homogenous samples, and over-reliance on traditional elliptical clustering approaches may inhibit the identification of meaningful subgroups. Finite mixture models that allow for non-elliptical cluster distributions is an emerging methodological field that may overcome this hurdle. Furthermore, succinctly quantifying pairwise cluster separation could enhance the clinical utility of the clustering solutions. However, a comprehensive examination of distance measures in the context of elliptical and non-elliptical model-based clustering is needed to provide practical guidance on the computation, benefits, and disadvantages of existing measures. We summarize several measures that can quantify the multivariate distance between two clusters and suggest practical computational tools. Through a simulation study, we evaluate the measures across three scenarios that allow for clusters to differ in location, scale, skewness, and rotation. We then demonstrate our approaches using psychophysiological and subjective responses to emotional imagery captured through the Transdiagnostic Anxiety Study. Finally, we synthesize findings to provide guidance on how to use distance measures in clustering applications.

Toward personalized medicine in connectomic deep brain stimulation

At the group-level, deep brain stimulation leads to significant therapeutic benefit in a multitude of neurological and neuropsychiatric disorders. At the single-patient level, however, symptoms may sometimes persist despite "optimal" electrode placement at established treatment coordinates. This may be partly explained by limitations of disease-centric strategies that are unable to account for heterogeneous phenotypes and comorbidities observed in clinical practice. Instead, tailoring electrode placement and programming to individual patients' symptom profiles may increase the fraction of top-responding patients. Here, we propose a three-step, circuit-based framework with the aim of developing patient-specific treatment targets that address the unique symptom constellation prevalent in each patient. First, we describe how a symptom network target library could be established by mapping beneficial or undesirable DBS effects to distinct circuits based on (retrospective) group-level data. Second, we suggest ways of matching the resulting symptom networks to circuits defined in the individual patient (template matching). Third, we introduce network blending as a strategy to calculate optimal stimulation targets and parameters by selecting and weighting a set of symptom-specific networks based on the symptom profile and subjective priorities of the individual patient. We integrate the approach with published literature and conclude by discussing limitations and future challenges.

A novel mind-set in primate experimentation: Implications for primate welfare

We emphasize the importance of studying the primate brain in cognitive neuroscience and suggest a new mind-set in primate experimentation within the boundaries of animal welfare regulations. Specifically, we list the advantages of investigating both genes and neural mechanisms and processes in the emergence of behavioral and cognitive functions, and propose the establishment of an open field of primate research. The latter may be conducted by implementing and harmonizing experimental practices with ethical guidelines that regulate (1) management of natural parks with free-moving populations of target nonhuman primates, (2) establishment of indoor-outdoor labs for both system genetics and neuroscience investigations, and (3) hotel space and technologies which remotely collect and dislocate information regarding primates geographically located elsewhere.

Experimental models in psychopathology research: The relation between Research Domain Criteria and Experimental Psychopathology

Experimental Psychopathology (EPP) and the Research Domain Criteria (RDoC) are research approaches that have developed in parallel, providing inter-related yet different scientific frameworks to investigate psychopathology at the intersection of fundamental and applied research. Here we address the overlap and differences between RDoC and EPP, and the challenges that both approaches face. Although overlap between EPP and RDoC can be clearly observed, each approach has its own unique strengths and weaknesses. These aspects will be illustrated by examples with respect to fear conditioning, an experimental procedure that has played a central role in both EPP and RDoC. We see much potential in boosting psychopathology research by combining the strengths of these two approaches.

The role of RDoC in future classification of mental disorders

The Research Domain Criteria (RDoC) project constitutes a translational framework for psychopathology research, initiated by the National Institute of Mental Health in an attempt to provide new avenues for research to circumvent problems emerging from the use of symptom-based diagnostic categories in diagnosing disorders. The RDoC alternative is a focus on psychopathology based on dimensions simultaneously defined by observable behavior (including quantitative measures of cognitive or affective behavior) and neurobiological measures. Key features of the RDoC framework include an emphasis on functional dimensions that range from normal to abnormal, integration of multiple measures in study designs (which can foster computational approaches), and high priority on studies of neurodevelopment and environmental influences (and their interaction) that can contribute to advances in understanding the etiology of disorders throughout the lifespan. The paper highlights key implications for ways in which RDoC can contribute to future ideas about classification, as well as some of the considerations involved in translating basic behavioral and neuroscience data to psychopathology.


A New Characterization of Mental Health Disorders Using Digital Behavioral Data: Evidence from Major Depressive Disorder

Mental health disorders are ambiguously defined and diagnosed. The established diagnosis technique, which is based on structured interviews, questionnaires and data subjectively reported by the patients themselves, leaves the mental health field behind other medical areas. We support these statements with examples from major depressive disorder (MDD). The National Institute of Mental Health (NIMH) launched the Research Domain Criteria (RDoC) project in 2009 as a new framework to investigate psychiatric pathologies from a multidisciplinary point of view. This is a good step in the right direction. Contemporary psychiatry considers mental illnesses as diseases that manifest in the mind and arise from the brain, expressed as a behavioral condition; therefore, we claim that these syndromes should be characterized primarily using behavioral characteristics. We suggest the use of smartphones and wearable devices to passively collect quantified behavioral data from patients by utilizing digital biomarkers of mental disorder symptoms. Various digital biomarkers of MDD symptoms have already been detected, and apps for collecting this longitudinal behavioral data have already been developed. This quantified data can be used to determine a patient’s diagnosis and personalized treatment, and thereby minimize the diagnosis rate of comorbidities. As there is a wide spectrum of human behavior, such a fluidic and personalized approach is essential.

Improving cognitive functioning in major depressive disorder with psychedelics: A dimensional approach

The high symptomatic and biological heterogeneity of major depressive disorder (MDD) makes it very difficult to find broadly efficacious treatments that work against all symptoms. Concentrating on single core symptoms that are biologically well understood might consist of a more viable approach. The Research Domain Criteria (RDoC) framework is a trans-diagnostic dimensional approach that focuses on symptoms and their underlying neurobiology. Evidence is accumulating that psychedelics may possess antidepressant activity, and this can potentially be explained through a multi-level (psychobiological, circuitry, (sub)cellular and molecular) analysis of the cognitive systems RDoC domain. Cognitive deficits, such as negative emotional processing and negativity bias, often lead to depressive rumination. Psychedelics can increase long-term cognitive flexibility, leading to normalization of negativity bias and reduction in rumination. We propose a theoretical model that explains how psychedelics can reduce the negativity bias in depressed patients. At the psychobiological level, we hypothesize that the negativity bias in MDD is due to impaired pattern separation and that psychedelics such as psilocybin help in depression because they enhance pattern separation and hence reduce negativity bias. Pattern separation is a mnemonic process that relies on adult hippocampal neurogenesis, where similar inputs are made more distinct, which is essential for optimal encoding of contextual information. Impairment in this process may underlie the negative cognitive bias in MDD by, for example, increased pattern separation of cues with a negative valence that can lead to excessive deliberation on aversive outcomes. On the (sub) cellular level, psychedelics stimulate hippocampal neurogenesis as well as synaptogenesis, spinogenesis and dendritogenesis in the prefrontal cortex. Together, these effects help restoring resilience to chronic stress and lead to modulation of the major connectivity hubs of the prefrontal cortex, hippocampus, and amygdala. Based on these observations, we propose a new translational framework to guide the development of a novel generation of therapeutics to treat the cognitive symptoms in MDD.

Neural correlates of RDoC-specific cognitive processes in a high-functional autistic patient: a statistically validated case report

The level of functioning of individuals with autism spectrum disorder (ASD) varies widely. To better understand the neurobiological mechanism associated with high-functioning ASD, we studied the rare case of a female patient with an exceptional professional career in the highly competitive academic field of Mathematics. According to the Research Domain Criteria (RDoC) approach, which proposes to describe the basic dimensions of functioning by integrating different levels of information, we conducted four fMRI experiments targeting the (1) social processes domain (Theory of mind (ToM) and face matching), (2) positive valence domain (reward processing), and (3) cognitive domain (N-back). Patient’s data were compared to data of 14 healthy controls (HC). Additionally, we assessed the subjective experience of our case during the experiments. The patient showed increased response times during face matching and achieved a higher total gain in the Reward task, whereas her performance in N-back and ToM was similar to HC. Her brain function differed mainly in the positive valence and cognitive domains. During reward processing, she showed reduced activity in a left-hemispheric frontal network and cortical midline structures but increased connectivity within this network. During the working memory task patients’ brain activity and connectivity in left-hemispheric temporo-frontal regions were elevated. In the ToM task, activity in posterior cingulate cortex and temporo-parietal junction was reduced. We suggest that the high level of functioning in our patient is rather related to the effects in brain connectivity than to local cortical information processing and that subjective report provides a fruitful framework for interpretation.

Irritability through Research Domain Criteria: an opportunity for transdiagnostic conceptualisation

Irritability is a transdiagnostic phenomenon that, despite its ubiquity and significant impact, is poorly conceptualised, defined and measured. As it lacks specificity, efforts to examine irritability in adults by using a diagnostic category perspective have been hamstrung. Therefore, using a Research Domain Criteria (RDoC) approach to examine irritability in adults, which spans many constructs and domains, may have a better chance of yielding underlying mechanisms that can then be mapped onto various diagnostic categories. Recently, a model has been proposed for irritability in children and adolescents that uses the RDoC framework; however, this model, which accounts for chronic, persistent irritability, may not necessarily transpose to adults. Therefore, use of the RDoC framework to examine irritability in adults is urgently needed, as it may shed light on this currently amorphous phenomenon and the many disorders within which it operates.

A Research Domain Criteria Approach to Gambling Disorder and Behavioral Addictions: Decision-Making, Response Inhibition, and the Role of Cannabidiol

Gambling Disorder (GD) has been recently re-classified in the DSM-5 under the "substance-related and addictive disorders," in light of its genetic, endophenotypic, and phenotypic resemblances to substance dependence. Diminished control is a core defining concept of psychoactive substance dependence or addiction and has given rise to the concept of "behavioral" addictions, which are syndromes analogous to substance addiction, but with a behavioral focus other than ingestion of a psychoactive substance. The main symptom clusters are represented by loss of control, craving/withdrawal, and neglect of other areas of life, whereas in a Research Domain Criteria (RDoC) perspective, GD patients exhibit deficits in the domain of "Positive valence systems," particularly in the "Approach motivation" and "Reward learning" constructs, as well as in the "Cognitive systems," primarily in the "Cognitive control" construct. In the Addictions Neuroclinical Assessment (ANA), three relevant domains for addictions emerge: "Incentive salience," "Negative Emotionality," and "Executive Function." The endocannabinoid system (ECS) may largely modulate these circuits, presenting a promising pharmaceutical avenue for treating addictions. Up to now, research on cannabidiol has shown some efficacy in Attention Deficit/Hyperactivity Disorder (ADHD), whereas in behavioral addictions its role has not been fully elucidated, as well as its precise action on RDoC domains. Herein, we review available evidence on RDoC domains affected in GD and behavioral addictions and summarize insights on the use of cannabidiol in those disorders and its potential mechanisms of action on reward, decisional, and sensorimotor processes.

Mapping the Research Domain Criteria Social Processes Constructs to the Social Responsiveness Scale

OBJECTIVE

Research Domain Criteria (RDoC) operationalizes a set of basic social dimensions that can be used to deconstruct sources of variation in social impairments across affected individuals, regardless of their diagnostic status. This is a necessary step toward the development of etiologically based and individualized treatments. The main objective of this investigation was to derive estimations of the RDoC social constructs from the Social Responsiveness Scale (SRS-2).

METHOD

Exploratory structural equation modeling and confirmatory factor analysis were conducted using individual SRS-2 items from six distinct databases ( N = 27,953; mean age = 9.55 years, SD = 3.79; 71.7% male participants) spanning normative (33.8%) and atypical (66.2%) development. The following models were estimated: a one-factor model; a three-factor model with separate attachment and affiliation, social communication, and understanding of mental states factors; and a four-factor model where social communication was further split into production of facial and non-facial communication.

RESULTS

The one-factor solution showed poor fit. The three-factor solution had adequate fit (comparative fit index = 0.952, Tucker Lewis Index = 0.937, root mean square error of approximation = 0.054). However, the four-factor solution had superior fit (comparative fit index = 0.973, Tucker Lewis Index = 0.961, root mean square error of approximation = 0.042) and was robust across age, sex, and clinical status.

CONCLUSION

To our knowledge, this is the first study examining estimations of the RDoC social constructs from an existing measure. Reported findings show promise for capturing important RDoC social constructs using the SRS-2 and highlight crucial areas for the development of novel dimensional social processing measures.

A transdiagnostic perspective of constructs underlying obsessive-compulsive and related disorders: An international Delphi consensus study

BACKGROUND

The Research Domain Criteria seeks to bridge knowledge from neuroscience with clinical practice by promoting research into valid neurocognitive phenotypes and dimensions, irrespective of symptoms and diagnoses as currently conceptualized. While the Research Domain Criteria offers a vision of future research and practice, its 39 functional constructs need refinement to better target new phenotyping efforts. This study aimed to determine which Research Domain Criteria constructs are most relevant to understanding obsessive-compulsive and related disorders, based on a consensus between experts in the field of obsessive-compulsive and related disorders.

METHODS

Based on a modified Delphi method, 46 experts were recruited from Australia, Africa, Asia, Europe and the Americas. Over three rounds, experts had the opportunity to review their opinion in light of feedback from the previous round, which included how their response compared to other experts and a summary of comments given.

RESULTS

Thirty-four experts completed round one, of whom 28 (82%) completed round two and 24 (71%) completed round three. At the final round, four constructs were endorsed by ⩾75% of experts as 'primary constructs' and therefore central to understanding obsessive-compulsive and related disorders. Of these constructs, one came from the Positive Valence System (Habit), two from the Cognitive Control System (Response Selection/Inhibition and Performance Monitoring) and the final construct was an additional item suggested by experts (Compulsivity).

CONCLUSION

This study identified four Research Domain Criteria constructs that, according to experts, cut across different obsessive-compulsive and related disorders. These constructs represent key areas for future investigation, and may have potential implications for clinical practice in terms of diagnostic processes and therapeutic management of obsessive-compulsive and related disorders.

Towards a Pragmatic Approach to a Psychophysiological Unit of Analysis for Mental and Brain Disorders: An EEG-Copeia for Neurofeedback

This article proposes what we call an "EEG-Copeia" for neurofeedback, like the "Pharmacopeia" for psychopharmacology. This paper proposes to define an "EEG-Copeia" as an organized list of scientifically validated EEG markers, characterized by a specific association with an identified cognitive process, that define a psychophysiological unit of analysis useful for mental or brain disorder evaluation and treatment. A characteristic of EEG neurofeedback for mental and brain disorders is that it targets a EEG markers related to a supposed cognitive process, whereas conventional treatments target clinical manifestations. This could explain why EEG neurofeedback studies encounter difficulty in achieving reproducibility and validation. The present paper suggests that a first step to optimize EEG neurofeedback protocols and future research is to target a valid EEG marker. The specificity of the cognitive skills trained and learned during real time feedback of the EEG marker could be enhanced and both the reliability of neurofeedback training and the therapeutic impact optimized. However, several of the most well-known EEG markers have seldom been applied for neurofeedback. Moreover, we lack a reliable and valid EEG targets library for further RCT to evaluate the efficacy of neurofeedback in mental and brain disorders. With the present manuscript, our aim is to foster dialogues between cognitive neuroscience and EEG neurofeedback according to a psychophysiological perspective. The primary objective of this review was to identify the most robust EEG target. EEG markers linked with one or several clearly identified cognitive-related processes will be identified. The secondary objective was to organize these EEG markers and related cognitive process in a psychophysiological unit of analysis matrix inspired by the Research Domain Criteria (RDoC) project.

Biocognitive Classification of Antisocial Individuals Without Explanatory Reductionism

Effective and specifically targeted social and therapeutic responses for antisocial personality disorders and psychopathy are scarce. Some authors maintain that this scarcity should be overcome by revising current syndrome-based classifications of these conditions and devising better biocognitive classifications of antisocial individuals. The inspiration for the latter classifications has been embedded in the Research Domain Criteria (RDoC) approach. RDoC-type approaches to psychiatric research aim at transforming diagnosis, provide valid measures of disorders, aid clinical practice, and improve health outcomes by integrating the data on the genetic, neural, cognitive, and affective systems underlying psychiatric conditions. In the first part of the article, we discuss the benefits of such approaches compared with the dominant syndrome-based approaches and review recent attempts at building biocognitive classifications of antisocial individuals. Other researchers, however, have objected that biocognitive approaches in psychiatry are committed to an untenable form of explanatory reductionism. Explanatory reductionism is the view that psychological disorders can be exclusively categorized and explained in terms of their biological causes. In the second part of the article, we argue that RDoC-like approaches need not be associated with explanatory reductionism. Moreover, we argue how this is the case for a specific biocognitive approach to classifying antisocial individuals.

Grant Report on Anxiety-CBT: Dimensional Brain Behavior Predictors of CBT Outcomes in Pediatric Anxiety

In the following grant report, we describe initial and planned work supported by our National Institute of Mental Health R01-funded, Research Domain Criteria (RDoc) informed project, “Dimensional Brain Behavior Predictors of CBT Outcomes in Pediatric Anxiety”. This project examines response to cognitive behavioral therapy (CBT) in a large sample of anxiety-affected and low-anxious youth ages 7 to 18 years using multiple levels of analysis, including brain imaging, behavioral performance, and clinical measures. The primary goal of the project is to understand how brain-behavioral markers of anxiety-relevant constructs, namely acute threat, cognitive control, and their interaction, associate with CBT response in youth with clinically significant anxiety. A secondary goal is to determine whether child age influences how these markers predict, and/or change, across varying degrees of CBT response. Now in its fourth year, data from this project has informed the examination of (1) baseline (i.e., pre-CBT) anxiety severity as a function of brain-behavioral measures of cognitive control, and (2) clinical characteristics of youth and parents that associate with anxiety severity and/or predict response to CBT. Analysis of brain-behavioral markers before and after CBT will assess mechanisms of CBT effect, and will be conducted once the data collection in the full sample has been completed. This knowledge will help guide the treatment of clinically anxious youth by informing for whom and how does CBT work.

Sluggish cognitive tempo and positive valence systems: Unique relations with greater reward valuation but less willingness to work

BACKGROUND

Research has started conceptualizing sluggish cognitive tempo (SCT) within the Research Domain Criteria (RDoC), but no study has tested SCT symptomatology in relation to the positive valence systems.

METHODS

Participants (N = 4,679; 18-29 years; M = 19.08, SD = 1.36; 69% female; 80.9% White) enrolled in six universities in the United States completed self-reported measures of positive valence systems, SCT, and psychopathology dimensions.

RESULTS

SCT symptoms were uniquely associated with greater reward valuation and expectancy of reward, but less willingness to work for reward. SCT symptoms were not uniquely related to initial and sustained response to reward. Conversely, depressive symptoms remained uniquely associated with greater reward valuation but less expectancy, willingness to work, initial, and sustained response to reward.

LIMITATIONS

The present study included a relatively homogenous sample of college-age students, solely relied on self-report measures of the positive valence systems, and analyses were conducted cross-sectionally.

CONCLUSIONS

Findings demonstrated that SCT has unique relations with various components of the positive valence system while controlling for commonly co-occurring psychopathology dimensions. Future research should continue investigating relations between SCT and positive valence systems to understand whether these domains may be targets for prevention and intervention.

The Positive Valence Systems Scale: Development and Validation

We present the Positive Valence Systems Scale (PVSS), a measure of the National Institute of Mental Health's Research Domain Criteria Positive Valence Systems domain. An initial long form of the scale (45 items) providing a broad assessment of the domain was distilled into a short form (21 items) measuring responses to a wide range of rewards (Food, Physical Touch, Outdoors, Positive Feedback, Social Interactions, Hobbies, and Goals). Across three diverse samples, the PVSS-21 demonstrated strong internal consistency, retest reliability, and factorial validity. It was more strongly related to reward than punishment sensitivity, positive than negative affect, and depression than anxiety. PVSS-21 scores discriminated depressed from nondepressed individuals and predicted anhedonia severity even when controlling for depression status. Hobbies emerged as the strongest predictor of clinical outcomes and the best differentiator of depressed and nondepressed individuals. Results highlight the potential of the PVSS for advancing understanding of reward-related abnormalities in depression and other disorders.

Research Domain Criteria: Strengths, Weaknesses, and Potential Alternatives for Future Psychiatric Research

The Research Domain Criteria (RDoC) paradigm was launched 10 years ago as a superior approach for investigation of mental illness. RDoC conceptualizes normal human behavior, emotion, and cognition as dimensional, with mental illnesses as dimensional extremes. We suggest that RDoC may have value for understanding normal human psychology and some conditions plausibly construed as extremes of normal variation. By contrast, for the most serious of mental illnesses, including dementia, autism, schizophrenia, and bipolar disorder, we argue that RDoC is conceptually flawed. RDoC conflates variation along dimensional axes of normal function with quantitative measurements of disease phenotypes and with the occurrence of diseases in overlapping clusters or spectra. This moves away from the disease model of major mental illness. Further, RDoC imposes a top-down approach to research. We argue that progress in major mental illness research will be more rapid with a bottom-up approach, starting with the discovery of etiological factors, proceeding to investigation of pathogenic pathways, including use of cell and animal models, and leading to a refined nosology and novel, targeted treatments.

Research Domain Criteria scores estimated through natural language processing are associated with risk for suicide and accidental death

BACKGROUND

Identification of individuals at increased risk for suicide is an important public health priority, but the extent to which considering clinical phenomenology improves prediction of longer term outcomes remains understudied. Hospital discharge provides an opportunity to stratify risk using readily available clinical records and details.

METHODS

We applied a validated natural language processing tool to generate estimated Research Domain Criteria (RDoC) scores for a cohort of 444,317 individuals drawn from 815,457 hospital discharges between 2005 and 2013. We used survival analysis to examine the association of this risk with suicide and accidental death, adjusted for sociodemographic features.

RESULTS

In adjusted models, symptoms in each of the five domains contributed to incremental risk (log rank P < 0.001), with greatest increase observed with positive valence. The contribution of each domain to risk was time dependent.

CONCLUSIONS

RDoC symptom scores parsed from clinical documentation are associated with suicide and illustrates that multiple domains contribute to risk in a time-varying fashion.

Dimensional thinking in psychiatry in the era of the Research Domain Criteria (RDoC)

The biological mechanisms underlying psychiatric diagnoses are not well defined. Clinical diagnosis based on categorical systems exhibit high levels of heterogeneity and co-morbidity. The Research Domain Criteria (RDoC) attempts to reconceptualize psychiatric disorders into transdiagnostic functional dimensional constructs based on neurobiological measures and observable behaviour. By understanding the underlying neurobiology and pathophysiology of the relevant processes, the RDoC aims to advance biomarker development for disease prediction and treatment response. This important evolving dimensional framework must also consider environmental factors. Emerging evidence suggests that gut microbes (microbiome) play a physiological role in brain diseases by modulating neuroimmune, neuroendocrine and neural signalling pathways between the gut and the brain. The integration of the gut microbiome signature as an additional dimensional component of the RDoC may enhance precision psychiatry.

Ontological representation-oriented term normalization and standardization of the Research Domain Criteria

The Research Domain Criteria, launched by the National Institute of Mental Health, is a new dimensional and interdisciplinary research framework for mental disorders. The Research Domain Criteria matrix is its core part. Since an ontology has the strengths of supporting semantic inferencing and automatic data processing, we would like to transform the Research Domain Criteria matrix into an ontological structure. In terms of data normalization, which is the essential part of an ontology representation, the Research Domain Criteria elements (mainly in the Units of Analysis) have some limitations. In this article, we propose a series of solutions to improve data normalization of the Research Domain Criteria elements in the Units of Analysis, including leveraging standard terminologies (i.e. the Unified Medical Language System Metathesaurus), context-combining queries, and domain expertise. The evaluation results show the positive (Yes) percentage is more than 80 percent, indicating our work is favorably received by the mental health professionals, and we have formed a good data foundation for the Research Domain Criteria ontological representation in the future work.

Children's sustained attention to emotional facial expressions and their autonomic nervous system reactivity during parent-child interactions

The way individuals process socio-affective information is thought to impact their responses to social interactions, but research testing the relation between these processes is scarce, particularly among children. This study examined if children's attention to socio-affective stimuli was associated with their autonomic nervous system (ANS) reactivity during parent-child interactions. Children's sustained attention to facial expressions of emotion (afraid, happy, sad) was indexed using the late positive potential (LPP) event-related potential (ERP) component during a computer-based task. To measure ANS reactivity, children's respiratory sinus arrhythmia (RSA) was assessed at baseline and during positive and negative parent-child discussions. Enhanced LPP amplitudes in response to all emotional facial expressions, reflecting greater sustained attention to socio-affective stimuli, were associated with increased RSA reactivity during parent-child discussions. These results show correspondence between two psychophysiological substrates of emotion processing in healthy children and highlight how these systems may be synergistic forces contributing to emotion reactivity.

A Novel Bio-Psychosocial-Behavioral Treatment Model of Panic Disorder

To conceptualize a novel bio-psychosocial-behavioral treatment model of panic disorder (PD), it is necessary to completely integrate behavioral, psychophysiological, neurobiological, and genetic data. Molecular genetic research on PD is specifically focused on neurotransmitters, including serotonin, neuropeptides, glucocorticoids, and neurotrophins. Although pharmacological interventions for PD are currently available, the need for more effective, faster-acting, and more tolerable pharmacological interventions is unmet. Thus, glutamatergic receptor modulators, orexin receptor antagonists, corticotrophin-releasing factor 1 receptor antagonists, and other novel mechanism-based anti-panic therapeutics have been proposed. Research on the neural correlates of PD is focused on the dysfunctional "cross-talk" between emotional drive (limbic structure) and cognitive inhibition (prefrontal cortex) and the fear circuit, which includes the amygdala-hippocampus-prefrontal axis. The neural perspective regarding PD supports the idea that cognitive-behavioral therapy normalizes alterations in top-down cognitive processing, including increased threat expectancy and attention to threat. Consistent with the concept of "personalized medicine," it is speculated that Research Domain Criteria can enlighten further treatments targeting dysfunctions underlying PD more precisely and provide us with better definitions of moderators used to identify subgroups according to different responses to treatment. Structuring of the "negative valence systems" domain, which includes fear/anxiety, is required to define PD. Therefore, targeting glutamate- and orexin-related molecular mechanisms associated with the fear circuit, which includes the amygdala-hippocampus-prefrontal cortex axis, is required to define a novel bio-psychosocial-behavioral treatment model of PD.

Deep brain stimulation in the treatment of obsessive-compulsive disorder: current perspectives

Deep brain stimulation (DBS) is a neuro-psychosurgical technique widely accepted in movement disorders, such as Parkinson's disease. Since 1999, DBS has been explored for severe, chronic and treatment-refractory psychiatric diseases. Our review focuses on DBS in obsessive-compulsive disorder (OCD), considered as a last treatment resort by most of learned societies in psychiatry. Two main stimulation areas have been studied: the striatal region and the subthalamic nucleus. But, most of the trials are open-labeled, and the rare controlled ones have failed to highlight the most efficient target. The recent perspectives are otherwise encouraging. Indeed, clinicians are currently considering other promising targets. A case series of 2 patients reported a decrease in OCD symptoms after DBS in the medial forebrain bundle and an open-label study is exploring bilateral habenula stimulation. New response criteria are also investigating such as quality of life, or subjective and lived-experience. Moreover, first papers about cost-effectiveness which is an important criterion in decision making, have been published. The effectiveness of tractography-assisted DBS or micro-assisted DBS is studying with the aim to improve targeting precision. In addition, a trial involving rechargeable pacemakers is undergoing because this mechanism could be efficient and have a positive impact on cost-effectiveness. A recent trial has discussed the possibility of using combined cognitive behavioral therapy (CBT) and DBS as an augmentation strategy. Finally, based on RDoc Research, the latest hypotheses about the understanding of cortico-striato-thalamo-cortical circuits could offer new directions including clinical predictors and biomarkers to perform adaptive closed-loop systems in the next future.

Research Domain Criteria: Cutting Edge Neuroscience or Galen's Humors Revisited?

The Research Domain Criteria (RDoC) scheme has guided the research agenda of the National Institute of Mental Health for the past decade. The essence of RDoC is its dimensional conception of mental illness, with the assumption that psychopathology is a manifestation of extremes along axes of neuropsychological variation. Research, it follows, should emphasize normal neuropsychological function and its associated neurocircuitry. We argue that RDoC, dressed in terms of modern neurobiology, is in fact a return to the humoral theory of Galen, a dimensional approach in which physical and mental health requires a balance of the four basic bodily humors (blood, black bile, yellow bile, and phlegm). The RDoC/Galenic approach may be useful in understanding those conditions best understood as extremes along a continuum, such as personality disorders. However, we contend that for the most severe psychiatric disorders - categorically defined diseases such as schizophrenia, bipolar disorder, and autism - RDoC's Galenic dimensionalism is a retreat from the biomedical approach that seeks to find rational therapeutic targets by identifying etiologic factors and pathogenic pathways. Abandoning this medical model now, in the context of remarkable advances in genetics, neuroimaging, and neuroscience, is a major setback for the advancement of scientific psychiatry.

High Throughput Phenotyping for Dimensional Psychopathology in Electronic Health Records

BACKGROUND

Relying on diagnostic categories of neuropsychiatric illness obscures the complexity of these disorders. Capturing multiple dimensional measures of neuropathology could facilitate the clinical and neurobiological investigation of cognitive and behavioral phenotypes.

METHODS

We developed a natural language processing-based approach to extract five symptom dimensions, based on the National Institute of Mental Health Research Domain Criteria definitions, from narrative clinical notes. Estimates of Research Domain Criteria loading were derived from a cohort of 3619 individuals with 4623 hospital admissions. We applied this tool to a large corpus of psychiatric inpatient admission and discharge notes (2010-2015), and using the same cohort we examined face validity, predictive validity, and convergent validity with gold standard annotations.

RESULTS

In mixed-effect models adjusted for sociodemographic and clinical features, greater negative and positive symptom domains were associated with a shorter length of stay (β = -.88, p = .001 and β = -1.22, p < .001, respectively), while greater social and arousal domain scores were associated with a longer length of stay (β = .93, p < .001 and β = .81, p = .007, respectively). In fully adjusted Cox regression models, a greater positive domain score at discharge was also associated with a significant increase in readmission risk (hazard ratio = 1.22, p < .001). Positive and negative valence domains were correlated with expert annotation (by analysis of variance [df = 3], R² = .13 and .19, respectively). Likewise, in a subset of patients, neurocognitive testing was correlated with cognitive performance scores (p < .008 for three of six measures).

CONCLUSIONS

This shows that natural language processing can be used to efficiently and transparently score clinical notes in terms of cognitive and psychopathologic domains.

Interoception and Mental Health: A Roadmap

Interoception refers to the process by which the nervous system senses, interprets, and integrates signals originating from within the body, providing a moment-by-moment mapping of the body's internal landscape across conscious and unconscious levels. Interoceptive signaling has been considered a component process of reflexes, urges, feelings, drives, adaptive responses, and cognitive and emotional experiences, highlighting its contributions to the maintenance of homeostatic functioning, body regulation, and survival. Dysfunction of interoception is increasingly recognized as an important component of different mental health conditions, including anxiety disorders, mood disorders, eating disorders, addictive disorders, and somatic symptom disorders. However, a number of conceptual and methodological challenges have made it difficult for interoceptive constructs to be broadly applied in mental health research and treatment settings. In November 2016, the Laureate Institute for Brain Research organized the first Interoception Summit, a gathering of interoception experts from around the world, with the goal of accelerating progress in understanding the role of interoception in mental health. The discussions at the meeting were organized around four themes: interoceptive assessment, interoceptive integration, interoceptive psychopathology, and the generation of a roadmap that could serve as a guide for future endeavors. This review article presents an overview of the emerging consensus generated by the meeting.

Variable Selection for Skewed Model-Based Clustering: Application to the Identification of Novel Sleep Phenotypes

In sleep research, applying finite mixture models to sleep characteristics captured 8 through multiple data types, including self-reported sleep diary, a wrist monitor capturing movement (actigraphy), and brain waves (polysomnography), may suggest new phenotypes that reflect underlying disease mechanisms. However, a direct mixture model application is challenging because there are many sleep variables from which to choose, and sleep variables are often highly skewed even in homogenous samples. Moreover, previous sleep research findings indicate that some of the most clinically interesting solutions will be those that incorporate all three data types. Thus, we present two novel skewed variable selection algorithms based on the multivariate skew normal (MSN) distribution: one that selects the best set of variables ignoring data type and another that embraces the exploratory nature of clustering and suggests multiple statistically plausible sets of variables that each incorporate all data types. Through a simulation study we empirically compare our approach with other asymmetric and normal dimension reduction strategies for clustering. Finally, we demonstrate our methods using a sample of older adults with and without insomnia. The proposed MSN-based variable selection algorithm appears to be suitable for both MSN and multivariate normal cluster distributions, especially with moderate to large sample sizes.

Toward a Neuroscience of Adult Cognitive Developmental Theory

Piaget's genetic epistemology has provided the constructivist approach upon which child developmental theories were founded, in that infants are thought to progress through distinct cognitive stages until they reach maturity in their early 20's. However, it is now well established that cognition continues to develop after early adulthood, and several “neo-Piagetian” theories have emerged in an attempt to better characterize adult cognitive development. For example, Kegan's Constructive Developmental Theory (CDT) argues that the thought processes used by adults to construct their reality change over time, and reaching higher stages of cognitive development entails becoming objectively aware of emotions and beliefs that were previously in the realm of the subconscious. In recent years, neuroscience has shown a growing interest in the biological substrates and neural mechanisms encompassing adult cognitive development, because psychological and psychiatric disorders can arise from deficiencies therein. In this article, we will use Kegan's CDT as a framework to discuss adult cognitive development in relation to closely correlated existing constructs underlying social processing, such as the perception of self and others. We will review the functional imaging and electrophysiologic evidence behind two key concepts relating to these posited developmental changes. These include self-related processing, a field that distinguishes between having conscious experiences (“being a self”) and being aware of oneself having conscious experiences (“being aware of being a self”); and theory of mind, which is the objective awareness of possessing mental states such as beliefs and desires (i.e., having a “mind”) and the understanding that others possess mental states that can be different from one's own. We shall see that cortical midline structures, including the medial prefrontal cortex and cingulate gyrus, as well as the temporal lobe, are associated with psychological tasks that test these models. In addition, we will review computational modeling approaches to cognitive development, and show how mathematical modeling can provide insights into how sometimes continuous changes in the neural processing substrate can give rise to relatively discrete developmental stages. Because deficiencies in adult cognitive development can result in disorders such as autism and depression, bridging the gaps between developmental psychology, neuroscience, and modeling has potential implications for clinical practice. As neuromodulation techniques such as deep brain and transcranial stimulation continue to advance, interfacing with these systems may lead to the emergence of novel investigational methods and therapeutic strategies in adults suffering from developmental disorders.

Using Event-Related Potentials and Startle to Evaluate Time Course in Anxiety and Depression

The National Institute of Mental Health's Research Domain Criteria initiative is a research framework designed toward understanding psychopathology as abnormalities of dimensional neurobehavioral constructs rather than in terms of DSM-defined categories. Research Domain Criteria constructs within the negative valence domain are particularly relevant for understanding anxiety and depressive disorders, which are pervasive, debilitating, and characterized by negative processing bias. One important direction for Research Domain Criteria research is investigating processes and parameters related to the time course (or chronometry) of negative valenced constructs. Two reliable methods for assessing chronometry are event-related potentials (ERPs) and startle blink. In this qualitative review, we examine ERP and startle studies of individuals with anxiety or depression or individuals vulnerable to affective disorders. The aim of the review is to highlight how these methods can inform the role of chronometry in the spectrum of anxiety and depression. ERP studies examining different chronometry facets of negative valenced responses have shown that transdiagnostic groups of individuals with internalizing psychopathologies exhibit abnormalities at early stages of processing. Startle reactivity studies have robustly differentiated fear-based disorders (e.g., panic disorder, social phobia) from other anxiety disorders (e.g., generalized anxiety disorder) and have also shown that different internalizing phenotypes exhibit different patterns of habituation. Findings lend support to the value of ERP and startle measures in identifying groups that cut across conventional classification systems. We also highlight methodological issues that can aid in the validity and reproducibility of ERP and startle findings and, ultimately, in the goal of developing more precise models of anxiety and depression.

Brain activity and connectivity in response to negative affective stimuli: Impact of dysphoric mood and sex across diagnoses

Negative affective stimuli elicit behavioral and neural responses which vary on a continuum from adaptive to maladaptive, yet are typically investigated in a dichotomous manner (healthy controls vs. psychiatric diagnoses). This practice may limit our ability to fully capture variance from acute responses to negative affective stimuli to psychopathology at the extreme end. To address this, we conducted a functional magnetic resonance imaging study to examine the neural responses to negative valence/high arousal and neutral valence/low arousal images as a function of dysphoric mood and sex across individuals (n = 99) who represented traditional categories of healthy controls, major depressive disorder, bipolar psychosis, and schizophrenia. Observation of negative (vs. neutral) stimuli elicited blood oxygen-level dependent responses in the following circuitry: periaqueductal gray, hypothalamus (HYPO), amygdala (AMYG), hippocampus (HIPP), orbitofrontal cortex (OFC), medial prefrontal cortex (mPFC), and greater connectivity between AMYG and mPFC. Across all subjects, severity of dysphoric mood was associated with hyperactivity of HYPO, and, among females, right (R) AMYG. Females also demonstrated inverse relationships between severity of dysphoric mood and connectivity between HYPO - R OFC, R AMYG - R OFC, and R AMYG - R HIPP. Overall, our findings demonstrated sex-dependent deficits in response to negative affective stimuli increasing as a function of dysphoric mood state. Females demonstrated greater inability to regulate arousal as mood became more dysphoric. These findings contribute to elucidating biosignatures associated with response to negative stimuli across disorders and suggest the importance of a sex-dependent lens in determining these biosignatures. Hum Brain Mapp 37:3733-3744, 2016. © 2016 Wiley Periodicals, Inc.

Understanding suicide risk within the Research Domain Criteria (RDoC) framework: A meta-analytic review

BACKGROUND

The field is in need of novel and transdiagnostic risk factors for suicide. The National Institute of Mental Health's Research Domain Criteria (RDoC) provides a framework that may help advance research on suicidal behavior.

METHOD

We conducted a meta-analytic review of existing prospective risk and protective factors for suicidal thoughts and behaviors (ideation, attempts, and deaths) that fall within one of the five RDoC domains or relate to a prominent suicide theory. Predictors were selected from a database of 4,082 prospective risk and protective factors for suicide outcomes.

RESULTS

A total of 460 predictors met inclusion criteria for this meta-analytic review and most examined risk (vs. protective) factors for suicidal thoughts and behaviors. The overall effect of risk factors was statistically significant, but relatively small, in predicting suicide ideation (weighted mean odds ratio: wOR = 1.72; 95% CI: 1.59-1.87), suicide attempt (wOR = 1.66 [1.57-1.76), and suicide death (wOR = 1.41 [1.24-1.60]). Across all suicide outcomes, most risk factors related to the Negative Valence Systems domain, although effect sizes were of similar magnitude across RDoC domains.

CONCLUSIONS

This study demonstrated that the RDoC framework provides a novel and promising approach to suicide research; however, relatively few studies of suicidal behavior fit within this framework. Future studies must go beyond the "usual suspects" of suicide risk factors (e.g., mental disorders, sociodemographics) to understand the processes that combine to lead to this deadly outcome.

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.