The RDoC framework: facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology

The unique face of comorbid anxiety and depression: Increased frontal, insula and cingulate cortex response during Pavlovian fear-conditioning

BACKGROUND

Dysregulation of fear processing through altered sensitivity to threat is thought to contribute to the development of anxiety disorders and major depressive disorder (MDD). However, fewer studies have examined fear processing in MDD than in anxiety disorders. The current study used propensity matching to examine the hypothesis that comorbid MDD and anxiety (AnxMDD) shows greater neural correlates of fear processing than MDD, suggesting that the co-occurrence of AnxMDD is exemplified by exaggerated defense related processes.

METHODS

195 individuals with MDD (N = 65) or AnxMDD (N = 130) were recruited from the community and completed multi-level assessments, including a Pavlovian fear learning task during functional imaging. Visual images paired with threat (conditioned stimuli: CS+) were compared to stimuli not paired with threat (CS-).

RESULTS

MDD and AnxMDD showed significantly different patterns of activation for CS+ vs CS- in the dorsal anterior insula/inferior frontal gyrus (partial eta squared; ηp2 = 0.02), dorsolateral prefrontal cortex (ηp2 = 0.01) and dorsal anterior/mid cingulate cortex (ηp2 = 0.01). These differences were driven by greater activation to the CS+ in AnxMDD versus MDD.

LIMITATIONS

Limitations include the cross-sectional design, a scream US rather than shock and half the number of MDD as AnxMDD participants.

CONCLUSIONS

AnxMDD showed a pattern of increased activation in regions identified with fear processing. Effects were consistently driven by threat, further suggesting fear signaling as the emergent target process. Differences emerged in regions associated with salience processing, attentional orienting/conflict, self-relevant processing and executive functioning in comorbid anxiety and depression, thereby highlighting potential treatment targets for this prevalent and treatment resistant group.

THE ROLE OF GENE-ENVIRONMENT INTERACTIONS IN SOCIAL DYSFUNCTION: FOCUS ON PRECLINICAL EVIDENCE FROM MOUSE STUDIES

Human and animal research has demonstrated that genetic and environmental factors can strongly modulate behavioral function, including the expression of social behaviors and their dysfunctionalities. Several genes have been linked to pathologies characterized by alterations in social behaviors, e.g., aggressive/antisocial personality disorder (ASPD), or autism spectrum disorder (ASD). Environmental stimulation (e.g., physical exercise, environmental enrichment) or adversity (e.g., chronic stress, social isolation) may respectively improve or impair social interactions. While the independent contribution of genetic and environmental factors to social behaviors has been assessed in a variety of human and animal studies, the impact of their interactive effects on social functions has been less extensively investigated. Genetic mutations and environmental changes can indeed influence each other through complex mutual effects, e.g., inducing synergistic, antagonistic or interactive behavioral outcomes. This complexity is difficult to be disentangled in human populations, thus encouraging studies in animal models, especially in the mouse species which is the most suitable for genetic manipulations. Here we review the available preclinical evidence on the impact of gene-environment interactions on social behaviors and their dysfunction, focusing on studies in laboratory mice. We included findings combining naturally occurring mutations, selectively bred or transgenic mice with multiple environmental manipulations, including positive (environmental enrichment, physical exercise) and aversive (social isolation, maternal separation, and stress) experiences. The impact of the results is critically discussed in terms of their generalizability across mouse models and social tests, as well as their implications for human studies on social dysfunction.

Anhedonia as a Potential Transdiagnostic Phenotype With Immune-Related Changes in Recent-Onset Mental Health Disorders

BACKGROUND

Chronic low-grade inflammation is observed across mental disorders and is associated with difficult-to-treat-symptoms of anhedonia and functional brain changes, reflecting a potential transdiagnostic dimension. Previous investigations have focused on distinct illness categories in people with enduring illness, but few have explored inflammatory changes. We sought to identify an inflammatory signal and the associated brain function underlying anhedonia among young people with recent-onset psychosis and recent-onset depression.

METHODS

Resting-state functional magnetic resonance imaging, inflammatory markers, and anhedonia symptoms were collected from 108 (mean [SD] age = 26.2 [6.2] years; female = 50) participants with recent-onset psychosis (n = 53) and recent-onset depression (n = 55) from the European Union/Seventh Framework Programme-funded PRONIA (Personalised Prognostic Tools for Early Psychosis Management) study. Time series were extracted using the Schaefer atlas, defining 100 cortical regions of interest. Using advanced multimodal machine learning, an inflammatory marker model and a functional connectivity model were developed to classify participants into an anhedonic group or a normal hedonic group.

RESULTS

A repeated nested cross-validation model using inflammatory markers classified normal hedonic and anhedonic recent-onset psychosis/recent-onset depression groups with a balanced accuracy of 63.9% and an area under the curve of 0.61. The functional connectivity model produced a balanced accuracy of 55.2% and an area under the curve of 0.57. Anhedonic group assignment was driven by higher levels of interleukin 6, S100B, and interleukin 1 receptor antagonist and lower levels of interferon gamma, in addition to connectivity within the precuneus and posterior cingulate.

CONCLUSIONS

We identified a potential transdiagnostic anhedonic subtype that was accounted for by an inflammatory profile and functional connectivity. Results have implications for anhedonia as an emerging transdiagnostic target across emerging mental disorders.

Large-scale meta-analyses and network analyses of neural substrates underlying human escalated aggression

Escalated aggression represents a frequent and severe form of violence, sometimes manifesting as antisocial behavior. Driven by the pressures of modern life, escalated aggression is of particular concern due to its rising prevalence and its destructive impact on both individual well-being and socioeconomic stability. However, a consistent neural circuitry underpinning it remains to be definitively identified. Here, we addressed this issue by comparing brain alterations between individuals with escalated aggression and those without such behavioral manifestations. We first conducted a meta-analysis to synthesize previous neuroimaging studies on functional and structural alterations of escalated aggression (325 experiments, 2997 foci, 16,529 subjects). Following-up network and functional decoding analyses were conducted to provide quantitative characterizations of the identified brain regions. Our results revealed that brain regions constantly involved in escalated aggression were localized in the subcortical network (amygdala and lateral orbitofrontal cortex) associated with emotion processing, the default mode network (dorsal medial prefrontal cortex and middle temporal gyrus) associated with mentalizing, and the salience network (anterior cingulate cortex and anterior insula) associated with cognitive control. These findings were further supported by additional meta-analyses on emotion processing, mentalizing, and cognitive control, all of which showed conjunction with the brain regions identified in the escalated aggression. Together, these findings advance the understanding of the risk biomarkers of escalated aggressive populations and refine theoretical models of human aggression.

Where do neurodevelopmental conditions fit in transdiagnostic psychiatric frameworks? Incorporating a new neurodevelopmental spectrum

Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.

Towards a consensus roadmap for a new diagnostic framework for mental disorders

Current nosology claims to separate mental disorders into distinct categories that do not overlap with each other. This nosological separation is not based on underlying pathophysiology but on convention-based clustering of qualitative symptoms of disorders which are typically measured subjectively. Yet, clinical heterogeneity and diagnostic overlap in disease symptoms and dimensions within and across different diagnostic categories of mental disorders is huge. While diagnostic categories provide the basis for general clinical management, they do not describe the underlying neurobiology that gives rise to individual symptomatic presentations. The ability to incorporate neurobiology into the diagnostic framework and to stratify patients accordingly will be a critical step forward for the development of new treatments for mental disorders. Furthermore, it will also allow physicians to provide patients with a better understanding of their illness's complexities and management. To realize this ambition, a paradigm shift is needed to build an understanding of how neuropsychiatric conditions can be defined more precisely using quantitative (multimodal) biological processes and markers and thus to significantly improve treatment success. The ECNP New Frontiers Meeting 2024 set out to develop a consensus roadmap for building a new diagnostic framework for mental disorders by discussing its rationale, outlook, and consequences with all stakeholders involved. This framework would instantiate a set of principles and procedures by which research could continuously improve precision diagnostics while moving away from traditional nosology. In this meeting report, the speakers' summaries from their presentations are combined to address three key elements for generating such a roadmap, namely, the application of innovative technologies, understanding the biology of mental illness, and translating biological understanding into new approaches. In general, the meeting indicated a crucial need for a biology-informed framework to establish more precise diagnosis and treatment for mental disorders to facilitate bringing the right treatment to the right patient at the right time.

Atrophy in the supramarginal gyrus associated with impaired cognitive inhibition in grieving Chinese Shidu parents

Background: The loss of an only child, known as Shidu in China, is a profoundly distressing experience, often leading to Prolonged Grief Disorder (PGD). Despite its impact, the structural brain alterations associated with PGD, potentially influencing cognitive impairments in Shidu parents, remain understudied.Objective: This study aims to identify brain structural abnormalities related to prolonged grief and their relation with cognitive inhibition in Shidu parents.Methods: The study included 40 Shidu parents and 42 non-bereaved participants. Prolonged grief was evaluated using the Prolonged Grief Questionnaire (PG-13). We employed voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) to assess brain structural alterations and their correlation with cognitive inhibition, as measured by Stroop interference scores.Results: Findings suggest that greater prolonged grief intensity correlates with reduced grey matter volume in the right amygdala and the left supramarginal gyrus (SMG). Additionally, enhanced amygdala-to-whole-brain structural connectivity showed a marginal association with prolonged grief, particularly with emotional-related symptoms. Furthermore, a decrease in SMG volume was found to mediate the relation between prolonged grief and Stroop Time Inference (TI) score, indicating an indirect effect of prolonged grief on cognitive inhibition.Conclusions: The study provides insight into the neural correlates of prolonged grief in Shidu parents, highlighting the SMG's role in cognitive inhibition. These findings emphasise the need for comprehensive grief interventions to address the complex cognitive and emotional challenges faced by this unique bereaved population.

Conspiratorial thinking in a 50-state survey of American adults

Background

While the NIMH Research Domain Criteria framework stresses understanding how neuropsychiatric phenotypes vary across populations, little is known outside of small clinical cohorts about conspiratorial thoughts as an aspect of cognition.

Methods

We conducted a 50-state non-probability internet survey conducted in 6 waves between October 6, 2022 and January 29, 2024, with respondents age 18 and older. Respondents completed the American Conspiratorial Thinking Scale (ACTS) and the 9-item Patient Health Questionnaire (PHQ-9). Survey-weighted regression models were used to examine sociodemographic and clinical associations with ACTS score, and associations with vaccination status.

Results

Across the 6 survey waves, there were 123,781 unique individuals. After reweighting, a total of 78.6% of respondents somewhat or strongly agreed with at least one conspiratorial idea; 19.0% agreed with all four of them. More conspiratorial thoughts were reported among those age 25 - 54, males, individuals who finished high school but did not start or complete college, those with household income between $25,000 and $50,000 per year, and those who reside in rural areas, as well as those with greater levels of depressive symptoms. Endorsing more conspiratorial thoughts was associated with a significantly lower likelihood of being vaccinated against COVID-19.

Discussion

A substantial proportion of US adults endorsed at least some conspiratorial thinking, which varied widely across population subgroups. The extent of correlation with non-vaccination suggests the importance of considering such thinking in designing public health strategies.

Neural Basis of Pain Empathy Dysregulations in Mental Disorders - A Pre-registered Neuroimaging Meta-Analysis

BACKGROUND

Pain empathy represents a fundamental building block of several social functions, which have been demonstrated to be impaired across various mental disorders by accumulating evidence from case-control functional magnetic resonance imaging (fMRI) studies. However, it remains unclear whether the dysregulations are underpinned by robust neural alterations across mental disorders.

METHODS

This study utilized coordinate-based meta-analyses to quantitatively determine robust markers of altered pain empathy across mental disorders. To support the interpretation of the findings exploratory network-level and behavioral meta-analyses were conducted.

RESULTS

Quantitative analysis of eleven case-control fMRI studies with data from 296 patients and 229 controls revealed patients with mental disorders exhibited increased pain empathic reactivity in the left anterior cingulate gyrus, adjacent medial prefrontal cortex, and right middle temporal gyrus, yet decreased activity in the left cerebellum IV/V and left middle occipital gyrus compared to controls. The hyperactive regions showed network-level interactions with the core default mode network (DMN) and were associated with affective and social cognitive domains.

CONCLUSIONS

The findings suggest that pain-empathic alterations across mental disorders are underpinned by excessive empathic reactivity in brain systems involved in empathic distress and social processes, highlighting a shared therapeutic target to normalize basal social dysfunctions in mental disorders.

Transdiagnostic depression severity and its relationship to global and prefrontal-amygdala structural properties in people with major depression and post-traumatic stress disorder

While some studies have used a transdiagnostic approach to relate depression to metabolic or functional brain alterations, the structural substrate of depression across clinical diagnostic categories is underexplored. In a cross-sectional study of 52 patients with major depressive disorder and 51 with post-traumatic stress disorder, drug-naïve, and spanning mild to severe depression severity, we examined transdiagnostic depressive correlates with regional gray matter volume and the topological properties of gray matter-based networks. Locally, transdiagnostic depression severity correlated positively with gray matter volume in the right middle frontal gyrus and negatively with nodal topological properties of gray matter-based networks in the right amygdala. Globally, transdiagnostic depression severity correlated positively with normalized characteristic path length, a measure implying brain integration ability. Compared with 62 healthy control participants, both major depressive disorder and post-traumatic stress disorder patients showed altered nodal properties in regions of the fronto-limbic-striatal circuit, and global topological organization in major depressive disorder in particular was characterized by decreased integration and segregation. These findings provide evidence for a gray matter-based structural substrate underpinning depression, with the prefrontal-amygdala circuit a potential predictive marker for depressive symptoms across clinical diagnostic categories.

Early Auditory Temporal Processing Deficit in Children with Autism Spectrum Disorder: The Research Domain Criteria Framework

Altered sensory processing especially in the auditory system is considered a typical observation in children with autism spectrum disorder (ASD). Auditory temporal processing is known to be impaired in ASD children. Although research suggests that auditory temporal processing abnormalities could be responsible for the core aspects of ASD, few studies have examined early time processing and their results have been conflicting. The present event-related potential (ERP) study investigated the early neural responses to duration and inter-stimulus interval (ISI) deviants in nonspeech contexts in children with ASD and a control group of typically developing (TD) children matched in terms of age and IQ. A passive auditory oddball paradigm was employed to elicit the mismatch negativity (MMN) for change detection considering both the duration and ISI-based stimulus. The MMN results showed that the ASD group had a relatively diminished amplitude and significant delayed latency in response to duration deviants. The findings are finally discussed in terms of hyper-hyposensitivity of auditory processing and the fact that the observed patterns may potentially act as risk factors for ASD development within the research domain criteria (RDoC) framework.

An exploration of blood-based biomarkers of negative symptoms of psychosis in men

Negative symptoms in the context of psychosis are still poorly understood and diagnosed, which impairs the treatment efficacy of current therapies and patient's integration in society. In this study, we aimed to test hypothesis-based and exploratory associations of negative symptom domains, as defined by the Brief Negative Symptom Scale (BNSS), with hormonal and hematological variables, and, complementarily, with standard psychological/cognitive and psychopathological measures. Fifty-one male patients diagnosed with a psychotic disorder underwent a structured interview and blood collection. Standard Spearmen bivariate correlations were used for data analysis. We obtained evidence of hypothesis-based associations between specific negative symptoms and oxytocin, thyroid stimulating hormone levels and neutrophil-to-lymphocyte ratio; as well as novel and hypothesis-free associations with erythrocyte and lymphocyte count, mean corpuscular volume and red cell distribution width. Complementarily, we also obtained some validation of previous associations of negative symptoms with illness resolution, cognitive symptom severity and social performance, and a novel association with anger contagion. We hope our results can generate new hypotheses in psychosis research. Our work suggests further avenues in research on erythrocytic, inflammatory, thyroid and oxytocin-related markers and abnormalities in psychosis, especially in regards to specific negative symptoms, towards more precise and comprehensive etiological, diagnostic and therapeutic models.

Examination of the mild, moderate, and severe alcohol use disorder severity indicators using a nationally representative sample

OBJECTIVE

The Diagnostic and Statistical Manual of Mental Disorders, fifth edition conceptualizes alcohol use disorder (AUD) as a single continuum with indicators to denote the level of severity along this spectrum with the presence of 2-3, 4-5, or 6 + symptoms indicating mild, moderate, and severe AUD, respectively. However, despite the labels of these indicators, it remains unclear how individuals compare across these indicators, both in terms of AUD severity, but also risk for other related problems (e.g., depression).

METHOD

Confirmatory factor analysis was conducted on past year AUD symptoms to obtain estimates of latent AUD severity using data from the 2020 National Survey on Drug Use and Health (unweighted n = 31,941). The range and distribution of latent trait estimates were then compared across AUD diagnostic statuses (i.e., no AUD, mild, moderate, and severe). Multinomial regressions were then used to compare diagnostic groups based on alcohol use, problems with other substances, treatment utilization, and mental/physical health.

RESULTS

Results indicated very limited overlap in latent severity estimates between individuals with different severity indicators. Multinomial regression results demonstrated that some measures increased in a roughly stepwise fashion across AUD indicators (e.g., alcohol use and drinking behavior), while many did not.

CONCLUSIONS

Results partially support the current AUD indicators as AUD severity and co-occurring problems did broadly increase across the indicators. However, the present study also explores several ways to improve these indicators in future AUD formulations. For example, having indicators that account not only for the quantitative but also the qualitative differences in AUD presentation at different severity levels. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Interplay of Worry and Relationship Satisfaction to Understand Sexual Distress: An APIM Study with Heterosexual Couples Using Cross-Sectional Data

The current study takes an integrative approach, considering individual transdiagnostic processes and relationship outcomes. It assumes an interdependence approach and aims to test a dyadic model to analyze the impact of worry and relationship satisfaction on heterosexual couples' sexual -distress, an essential factor for diagnosing sexual dysfunction. The current study recruited 103 couples from the community to complete an online survey containing the Female Sexual Distress Scale-Revised, the Penn State Worry Questionnaire - Abbreviated, and the Global Measure of Relationship Satisfaction. The results show that women's and men's worries are associated with their own sexual distress, and men's relationship satisfaction has an effect on their own and their partner's sexual distress. These results highlight the critical role of cognitive processes in shaping the experience of sexual distress and reinforce the importance of taking an integrative perspective that considers relationship (satisfaction), individual (worry) and social factors (gender) in interventions to treat sexual distress.

MULTIMODAL NEURAL CORRELATES OF CHILDHOOD PSYCHOPATHOLOGY

Complex structural and functional changes occurring in typical and atypical development necessitate multidimensional approaches to better understand the risk of developing psychopathology. Here, we simultaneously examined structural and functional brain network patterns in relation to dimensions of psychopathology in the Adolescent Brain Cognitive Development dataset. Several components were identified, recapitulating the psychopathology hierarchy, with the general psychopathology (p) factor explaining most covariance with multimodal imaging features, while the internalizing, externalizing, and neurodevelopmental dimensions were each associated with distinct morphological and functional connectivity signatures. Connectivity signatures associated with the p factor and neurodevelopmental dimensions followed the sensory-to-transmodal axis of cortical organization, which is related to the emergence of complex cognition and risk for psychopathology. Results were consistent in two separate data subsamples, supporting generalizability, and robust to variations in analytical parameters. Our findings help in better understanding biological mechanisms underpinning dimensions of psychopathology, and could provide brain-based vulnerability markers.

Pupil contagion variation with gaze, arousal, and autistic traits

Pupillary contagion occurs when one's pupil size unconsciously adapts to the pupil size of an observed individual and is presumed to reflect the transfer of arousal. Importantly, when estimating pupil contagion, low level stimuli properties need to be controlled for, to ensure that observations of pupillary changes are due to internal change in arousal rather than the external differences between stimuli. Here, naturalistic images of children's faces depicting either small or large pupils were presented to a group of children and adolescents with a wide range of autistic traits, a third of whom had been diagnosed with autism. We examined the extent to which pupillary contagion reflects autonomic nervous system reaction through pupil size change, heart rate and skin conductance response. Our second aim was to determine the association between arousal reaction to stimuli and degree of autistic traits. Results show that pupil contagion and concomitant heart rate change, but not skin conductance change, was evident when gaze was restricted to the eye region of face stimuli. A positive association was also observed between pupillary contagion and autistic traits when participants' gaze was constrained to the eye region. Findings add to a broader understanding of the mechanisms underlying pupillary contagion and its association with autism.

Mapping the neurodevelopmental predictors of psychopathology

Neuroimaging research has uncovered a multitude of neural abnormalities associated with psychopathology, but few prediction-based studies have been conducted during adolescence, and even fewer used neurobiological features that were extracted across multiple neuroimaging modalities. This gap in the literature is critical, as deriving accurate brain-based models of psychopathology is an essential step towards understanding key neural mechanisms and identifying high-risk individuals. As such, we trained adaptive tree-boosting algorithms on multimodal neuroimaging features from the Lifespan Human Connectome Developmental (HCP-D) sample that contained 956 participants between the ages of 8 to 22 years old. Our feature space consisted of 1037 anatomical, 1090 functional, and 192 diffusion MRI features, which were used to derive models that separately predicted internalizing symptoms, externalizing symptoms, and the general psychopathology factor. We found that multimodal models were the most accurate, but all brain-based models of psychopathology yielded out-of-sample predictions that were weakly correlated with actual symptoms (r2 < 0.15). White matter microstructural properties, including orientation dispersion indices and intracellular volume fractions, were the most predictive of general psychopathology, followed by cortical thickness and functional connectivity. Spatially, the most predictive features of general psychopathology were primarily localized within the default mode and dorsal attention networks. These results were mostly consistent across all dimensions of psychopathology, except orientation dispersion indices and the default mode network were not as heavily weighted in the prediction of internalizing and externalizing symptoms. Taken with prior literature, it appears that neurobiological features are an important part of the equation for predicting psychopathology but relying exclusively on neural markers is clearly not sufficient, especially among adolescent samples with subclinical symptoms. Consequently, risk factor models of psychopathology may benefit from incorporating additional sources of information that have also been shown to explain individual differences, such as psychosocial factors, environmental stressors, and genetic vulnerabilities.

The Cerebellum and Cognitive Function: Anatomical Evidence from a Transdiagnostic Sample

Multiple lines of evidence across human functional, lesion, and animal data point to a cerebellar role, in particular of crus I, crus II, and lobule VIIB, in cognitive function. However, a mapping of distinct facets of cognitive function to cerebellar structure is missing. We analyzed structural neuroimaging data from the Healthy Brain Network (HBN). Cerebellar parcellation was performed with a validated automated segmentation pipeline (CERES) and stringent visual quality check (n = 662 subjects retained from initial n = 1452). Canonical correlation analyses (CCA) examined regional gray matter volumetric (GMV) differences in association to cognitive function (quantified with NIH Toolbox Cognition domain, NIH-TB), accounting for psychopathology severity, age, sex, scan location, and intracranial volume. Multivariate CCA uncovered a significant correlation between two components entailing a latent cognitive canonical (NIH-TB subscales) and a brain canonical variate (cerebellar GMV and intracranial volume, ICV), surviving bootstrapping and permutation procedures. The components correspond to partly shared cerebellar-cognitive function relationship with a first map encompassing cognitive flexibility (r = 0.89), speed of processing (r = 0.65), and working memory (r = 0.52) associated with regional GMV in crus II (r = 0.57) and lobule X (r = 0.59) and a second map including the crus I (r = 0.49) and lobule VI (r = 0.49) associated with working memory (r = 0.51). We show evidence for a structural subspecialization of the cerebellum topography for cognitive function in a transdiagnostic sample.

Discriminative capacity of the Spanish version of the Inventory of Depression and Anxiety Symptoms-II (IDAS-II) for detecting DMS-5 specific disorders and poor quality of life in a clinical sample

BACKGROUND

Emotional problems can be evaluated using categorical approaches to guide treatment choices focused on targeting specific disorders, or dimensional approaches to reduce symptom severity. Moreover, recent evidence points out the need to intervene in patients' quality of life (QoL), which often remains low even after the remission of emotional problems. Thus, assessment instruments are needed to provide information on diagnosis, symptom severity, and QoL. The present study aimed to provide diagnostic and QoL cutoffs for the Inventory of Depression and Anxiety Symptoms-II (IDAS-II).

METHODS

273 patients recruited from mental health services in Huelva (Spain) completed the IDAS-II, Mini International Neuropsychiatric Interview, and Short Form-36 Health Survey. Receiver operating characteristic curve analyses were used to establish cutoff values. Diagnostic, balanced, and screening cutoffs were provided for each IDAS-II scale to detect corresponding diagnoses and poor QoL.

RESULTS

The specific IDAS-II scales Suicidality, Panic, Social Anxiety, Claustrophobia, and Traumatic Intrusions showed adequate discrimination values for their corresponding diagnoses (suicidal behavior disorder, panic disorder, social anxiety disorder, agoraphobia, and post-traumatic stress disorder, respectively). Both the General Depression and Dysphoria scales showed adequate ability to detect major depressive disorder. The IDAS-II scales showed a higher discrimination ability for Mental Health-related QoL, than for General Health-related QoL.

CONCLUSIONS

The diagnostic and QoL cutoffs expand the clinical utility of the IDAS-II in clinical practice and research, making it a comprehensive, detailed, and versatile self-report tool. The IDAS-II allows for the assessment of emotional problems consistent with the dimensional, categorical, transdiagnostic, and QoL approaches.

Improved Scoring of the Center for Epidemiologic Studies Depression Scale - Revised: An Item Response Theory Analysis

The Center for Epidemiologic Studies Depression Scale - Revised (CESD-R) is a popular self-report screening measure for depression. A 20-item questionnaire with scores ranging from 0 to 4 for each item, the CESD-R can produce total scores ranging from 0 to 80. However, the typical scoring protocol for the CESD-R restricts the range of possible scores to between 0 and 60 to retain the same range and clinical cutoff scores as the original CES-D. Despite the widespread adoption of this scoring approach, the psychometric impact has never been systematically examined. In an undergraduate and community adult sample (n = 869), item response theory analyses indicated that scoring the CESD-R with all 5 response options (CESD-R5opt) provided nearly twice as much information about a person's latent depression for individuals with high levels of depression than did scoring the CESD-R with 4 response options per item (CESD-R4opt). The CESD-R5opt retained the strong reliability and factor structure of the CESD-R4opt and was more sensitive to individual differences for participants at high levels of depression compared to the CESD-R4opt. Results provide preliminary evidence that researchers and clinicians should score the CESD-R using the full 0-to-80 scale and a clinical cutoff score of 29.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10862-024-10155-y.

Neuropsychology and Neurobiology of Negative Schizotypy: A Selective Review

Schizotypy refers to a latent personality organization that reflects liability to schizophrenia. Because schizotypy is a multidimensional construct, people with schizotypy vary in behavioral and neurobiological features. In this article, we selectively review the neuropsychological and neurobiological profiles of people with schizotypy, with a focus on negative schizotypy. Empirical evidence is presented for alterations of neuropsychological performance in negative schizotypy. We also cover the Research Domain Criteria domains of positive valence, social process, and sensorimotor systems. Moreover, we systematically summarize the neurobiological correlates of negative schizotypy at the structural, resting-state, and task-based neural levels, as well as the neurochemical level. The convergence and inconsistency of the evidence are critically reviewed. Regarding theoretical and clinical implications, we argue that negative schizotypy represents a useful organizational framework for studying neuropsychology and neurobiology across different psychiatric disorders.

Threat sensitivity in emotion dynamics: Negativity effects and sex differences

Evolutionary theorizing has given rise to the idea that responding to any particular threat may be more mandatory than responding to any particular reward. The present three experiments (total N = 375) sought to provide support for this perspective in an emotion dynamics task in which participants continuously rated their affective state in response to appetitive (reward-related) versus aversive (threat-related) images. Even when equating images for arousal and extremity, several negativity effects (e.g., steeper reactivity slopes in response to aversive images) were found. These negativity effects can serve as an experimental model of threat sensitivity, which should predispose some individuals, more than others, to symptoms related to fear and anxiety. This point was made with respect to sex differences, given that women (relative to men) are diagnosed with anxiety disorders at higher rates. Sex differences were pronounced and extensions of this work, both basic and applied, are proposed.

Sociodemographic and clinical correlates of hallucinations in patients entering an early intervention program for first episode psychosis

Hallucinations are a core feature of psychosis, and their severity during the acute phase of illness is associated with a range of poor outcomes. Various clinical and sociodemographic factors may predict hallucinations and other positive psychotic symptoms in first episode psychosis (FEP). Despite this, the precise factors associated with hallucinations at first presentation to an early intervention service have not been extensively researched. Through detailed interviews and chart reviews, we investigated sociodemographic and clinical predictors in 636 minimally-medicated patients who entered PEPP-Montréal, an early intervention service for FEP, between 2003 and 2018. Hallucinations were measured using the Scale for the Assessment of Positive Symptoms (SAPS), while negative symptoms were assessed using the Scale for the Assessment of Negative symptoms (SANS). Depressive symptoms were evaluated through the Calgary Depression Scale for Schizophrenia (CDSS), and anxiety symptoms via the Hamilton Rating Scale for Anxiety (HAS). A majority (n = 381, 59.9 %) of the sample presented with clinically significant hallucinations (SAPS global hallucinations score ≥ 3) at program entry. These patients had an earlier age at onset, fewer years of education, and a higher severity of delusions, depression and negative symptoms than those without clinical-level hallucinations. These results suggest that individuals with clinically significant hallucinations at admission tend to be younger and have a greater overall symptom burden. This makes it especially important to monitor hallucinations alongside delusions, depression and negative symptoms in order to identify who might benefit from targeted interventions. The implications of these findings for early intervention and person-centered care are discussed.

Quality over quantity: powering neuroimaging samples in psychiatry

Neuroimaging has been widely adopted in psychiatric research, with hopes that these non-invasive methods will provide important clues to the underpinnings and prediction of various mental health symptoms and outcomes. However, the translational impact of neuroimaging has not yet reached its promise, despite the plethora of computational methods, tools, and datasets at our disposal. Some have lamented that too many psychiatric neuroimaging studies have been underpowered with respect to sample size. In this review, we encourage this discourse to shift from a focus on sheer increases in sample size to more thoughtful choices surrounding experimental study designs. We propose considerations at multiple decision points throughout the study design, data modeling and analysis process that may help researchers working in psychiatric neuroimaging boost power for their research questions of interest without necessarily increasing sample size. We also provide suggestions for leveraging multiple datasets to inform each other and strengthen our confidence in the generalization of findings to both population-level and clinical samples. Through a greater emphasis on improving the quality of brain-based and clinical measures rather than merely quantity, meaningful and potentially translational clinical associations with neuroimaging measures can be achieved with more modest sample sizes in psychiatry.

Normative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients

Advanced methods such as REACT have allowed the integration of fMRI with the brain's receptor landscape, providing novel insights transcending the multiscale organisation of the brain. Similarly, normative modelling has allowed translational neuroscience to move beyond group-average differences and characterise deviations from health at an individual level. Here, we bring these methods together for the first time. We used REACT to create functional networks enriched with the main modulatory, inhibitory, and excitatory neurotransmitter systems and generated normative models of these networks to capture functional connectivity deviations in patients with schizophrenia, bipolar disorder (BPD), and ADHD. Substantial overlap was seen in symptomatology and deviations from normality across groups, but these could be mapped into a common space linking constellations of symptoms through to underlying neurobiology transdiagnostically. This work provides impetus for developing novel biomarkers that characterise molecular- and systems-level dysfunction at the individual level, facilitating the transition towards mechanistically targeted treatments.

Large Individual Differences in Functional Connectivity in the Context of Major Depression and Antidepressant Pharmacotherapy

Clinical studies of major depression (MD) generally focus on group effects, yet interindividual differences in brain function are increasingly recognized as important and may even impact effect sizes related to group effects. Here, we examine the magnitude of individual differences in relation to group differences that are commonly investigated (e.g., related to MD diagnosis and treatment response). Functional MRI data from 107 participants (63 female, 44 male) were collected at baseline, 2, and 8 weeks during which patients received pharmacotherapy (escitalopram, N = 68) and controls (N = 39) received no intervention. The unique contributions of different sources of variation were examined by calculating how much variance in functional connectivity was shared across all participants and sessions, within/across groups (patients vs controls, responders vs nonresponders, female vs male participants), recording sessions, and individuals. Individual differences and common connectivity across groups, sessions, and participants contributed most to the explained variance (>95% across analyses). Group differences related to MD diagnosis, treatment response, and biological sex made significant but small contributions (0.3-1.2%). High individual variation was present in cognitive control and attention areas, while low individual variation characterized primary sensorimotor regions. Group differences were much smaller than individual differences in the context of MD and its treatment. These results could be linked to the variable findings and difficulty translating research on MD to clinical practice. Future research should examine brain features with low and high individual variation in relation to psychiatric symptoms and treatment trajectories to explore the clinical relevance of the individual differences identified here.

The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

Anterior pituitary gland volume mediates associations between pubertal hormones and changes in transdiagnostic symptoms in youth

The pituitary gland (PG) plays a central role in the production and secretion of pubertal hormones, with documented links to the emergence and increase in mental health symptoms known to occur during adolescence. Although much of the literature has focused on examining whole PG volume, recent findings suggest that there are associations among pubertal hormone levels, including dehydroepiandrosterone (DHEA), subregions of the PG, and elevated mental health symptoms (e.g., internalizing symptoms) during adolescence. Surprisingly, studies have not yet examined associations among these factors and increasing transdiagnostic symptomology, despite DHEA being a primary output of the anterior PG. Therefore, the current study sought to fill this gap by examining whether anterior PG volume specifically mediates associations between DHEA levels and changes in dysregulation symptoms in an adolescent sample ( N = 114, 9 - 17 years, M age = 12.87, SD = 1.88). Following manual tracing of the anterior and posterior PG, structural equation modeling revealed that greater anterior, not posterior, PG volume mediated the association between greater DHEA levels and increasing dysregulation symptoms across time, controlling for baseline dysregulation symptom levels. These results suggest specificity in the role of the anterior PG in adrenarcheal processes that may confer risk for psychopathology during adolescence. This work not only highlights the importance of separately tracing the anterior and posterior PG, but also suggests that transdiagnostic factors like dysregulation are useful in parsing hormone-related increases in mental health symptoms in youth.

Structural deviations of the posterior fossa and the cerebellum and their cognitive links in a neurodevelopmental deletion syndrome

High-impact genetic variants associated with neurodevelopmental disorders provide biologically-defined entry points for mechanistic investigation. The 3q29 deletion (3q29Del) is one such variant, conferring a 40-100-fold increased risk for schizophrenia, as well as high risk for autism and intellectual disability. However, the mechanisms leading to neurodevelopmental disability remain largely unknown. Here, we report the first in vivo quantitative neuroimaging study in individuals with 3q29Del (N = 24) and neurotypical controls (N = 1608) using structural MRI. Given prior radiology reports of posterior fossa abnormalities in 3q29Del, we focused our investigation on the cerebellum and its tissue-types and lobules. Additionally, we compared the prevalence of cystic/cyst-like malformations of the posterior fossa between 3q29Del and controls and examined the association between neuroanatomical findings and quantitative traits to probe gene-brain-behavior relationships. 3q29Del participants had smaller cerebellar cortex volumes than controls, before and after correction for intracranial volume (ICV). An anterior-posterior gradient emerged in finer grained lobule-based and voxel-wise analyses. 3q29Del participants also had larger cerebellar white matter volumes than controls following ICV-correction and displayed elevated rates of posterior fossa arachnoid cysts and mega cisterna magna findings independent of cerebellar volume. Cerebellar white matter and subregional gray matter volumes were associated with visual-perception and visual-motor integration skills as well as IQ, while cystic/cyst-like malformations yielded no behavioral link. In summary, we find that abnormal development of cerebellar structures may represent neuroimaging-based biomarkers of cognitive and sensorimotor function in 3q29Del, adding to the growing evidence identifying cerebellar pathology as an intersection point between syndromic and idiopathic forms of neurodevelopmental disabilities.

Therapeutic doses of ketamine acutely attenuate the aversive effect of losses during decision-making

The discovery of rapid-acting antidepressant, ketamine has opened a pathway to a new generation of treatments for depression, and inspired neuroscientific investigation based on a new perspective that non-adaptive changes in the intrinsic excitatory and inhibitory circuitry might underlie the pathophysiology of depression. Nevertheless, it still remains largely unknown how the hypothesized molecular and synaptic levels of changes in the circuitry might mediate behavioral and neuropsychological changes underlying depression, and how ketamine might restore adaptive behavior. Here, we used computational models to analyze behavioral changes induced by therapeutic doses of ketamine, while rhesus macaques were iteratively making decisions based on gains and losses of tokens. When administered intramuscularly or intranasally, ketamine reduced the aversiveness of undesirable outcomes such as losses of tokens without significantly affecting the evaluation of gains, behavioral perseveration, motivation, and other cognitive aspects of learning such as temporal credit assignment and time scales of choice and outcome memory. Ketamine's potentially antidepressant effect was separable from other side effects such as fixation errors, which unlike outcome evaluation, was readily countered with strong motivation to avoid errors. We discuss how the acute effect of ketamine to reduce the initial impact of negative events could potentially mediate longer-term antidepressant effects through mitigating the cumulative effect of those events produced by slowly decaying memory, and how the disruption-resistant affective memory might pose challenges in treating depression. Our study also invites future investigations on ketamine's antidepressant action over diverse mood states and with affective events exerting their impacts at diverse time scales.

A critical review of hot executive functioning in youth attention-deficit/hyperactivity disorder: Methodological limitations, conceptual considerations, and future directions

Hot executive functioning (EF) - EF under emotionally or motivationally salient conditions - is a putative etiology of attention-deficit/hyperactivity disorder (ADHD), disruptive behavior problems (DBPs), and their related impairments. Despite two decades of research, the present study is the first review of the construct in youth ADHD, with a particular focus on the role of task design, age, and DBPs, as well as relevant conceptual and methodological considerations. While certain hot EF tasks have been investigated extensively (e.g., choice impulsivity), substantial inconsistency in measurement of the broader construct remains, severely limiting conclusions. Future research should a) consider the extent to which various hot EF tasks relate to one another, a higher order factor, and other related constructs; b) further investigate task design, particularly the elicitation of emotion or motivation and its anticipated effect on EF; and c) incorporate multiple levels of analysis to validate similarities and differences among tasks with regard to the affective experiences and cognitive demands they elicit. With improved measurement and conceptual clarity, hot EF has potential to advance the literature on etiological pathways to ADHD, DBPs and associated impairments and, more broadly, may represent a useful tool for understanding the influence of emotion and motivation on cognition.

Depressive symptomatology in older adults treated with behavioral activation: A network perspective

BACKGROUND

Late-life depression is a serious mental health problem. Behavioral Activation (BA) is an effective, accessible psychotherapeutic treatment for older adults. However, little is known about which symptoms decrease and how associations between depressive symptoms change during BA treatment.

METHODS

Using data from a cluster-randomized trial for older adults with late-life depression, we estimated a partial correlation network and a relative importance network of depressive symptoms before and after 8 weeks of BA treatment in primary care (n = 96). Networks were examined with measures of network structure, connectivity, centrality as well as stability.

RESULTS

The most central symptoms at baseline and post-treatment were anhedonia, fatigue, and feeling depressed. In contrast, sleeping problems had the lowest centrality. The post-treatment network was significantly more interconnected than at baseline. Moreover, all symptoms were significantly more central at post-treatment.

CONCLUSION

Our findings highlight the utility of the network approach to better understand symptom networks of depressed older adults before and after BA treatment. Results show that network connectivity and centrality of all symptoms increased after treatment. Future studies should investigate longitudinal idiographic networks to explore symptom dynamics within individuals over time.

Psychosis superspectrum II: neurobiology, treatment, and implications

Alternatives to traditional categorical diagnoses have been proposed to improve the validity and utility of psychiatric nosology. This paper continues the companion review of an alternative model, the psychosis superspectrum of the Hierarchical Taxonomy of Psychopathology (HiTOP). The superspectrum model aims to describe psychosis-related psychopathology according to data on distributions and associations among signs and symptoms. The superspectrum includes psychoticism and detachment spectra as well as narrow subdimensions within them. Auxiliary domains of cognitive deficit and functional impairment complete the psychopathology profile. The current paper reviews evidence on this model from neurobiology, treatment response, clinical utility, and measure development. Neurobiology research suggests that psychopathology included in the superspectrum shows similar patterns of neural alterations. Treatment response often mirrors the hierarchy of the superspectrum with some treatments being efficacious for psychoticism, others for detachment, and others for a specific subdimension. Compared to traditional diagnostic systems, the quantitative nosology shows an approximately 2-fold increase in reliability, explanatory power, and prognostic accuracy. Clinicians consistently report that the quantitative nosology has more utility than traditional diagnoses, but studies of patients with frank psychosis are currently lacking. Validated measures are available to implement the superspectrum model in practice. The dimensional conceptualization of psychosis-related psychopathology has implications for research, clinical practice, and public health programs. For example, it encourages use of the cohort study design (rather than case-control), transdiagnostic treatment strategies, and selective prevention based on subclinical symptoms. These approaches are already used in the field, and the superspectrum provides further impetus and guidance for their implementation. Existing knowledge on this model is substantial, but significant gaps remain. We identify outstanding questions and propose testable hypotheses to guide further research. Overall, we predict that the more informative, reliable, and valid characterization of psychopathology offered by the superspectrum model will facilitate progress in research and clinical care.

Does the procedural deficit hypothesis of dyslexia account for the lack of automatization and the comorbidity among developmental disorders?

We critically examine the procedural deficit hypothesis (PDH) that proposes that a deficit in procedural (as opposed to declarative) learning underlies dyslexia and other developmental disorders. We first note that the existence of dissociated learning disorders (and multiple forms for each disorder) appears incompatible with a general deficit account. Moreover, the PDH formulation appears generally underspecified in terms of predictions to be tested. A particular focus is on the conceptualization of automatization. However, there are alternative views of automaticity, and comparing these different views helps frame the body of findings on the PDH. The insufficient PDH specification led to tasks touching on different skills and selecting target groups based on general diagnostic categories. Accordingly, several recent reviews and meta-analyses reported mixed patterns of findings and reached contradictory conclusions on the PDH. We propose avenues for future research to effectively examine the role of PDH in learning and other developmental disorders.

Reward anticipation-related neural activation following cued reinforcement in adults with psychotic psychopathology and biological relatives

BACKGROUND

Schizophrenia is associated with hypoactivation of reward sensitive brain areas during reward anticipation. However, it is unclear whether these neural functions are similarly impaired in other disorders with psychotic symptomatology or individuals with genetic liability for psychosis. If abnormalities in reward sensitive brain areas are shared across individuals with psychotic psychopathology and people with heightened genetic liability for psychosis, there may be a common neural basis for symptoms of diminished pleasure and motivation.

METHODS

We compared performance and neural activity in 123 people with a history of psychosis (PwP), 81 of their first-degree biological relatives, and 49 controls during a modified Monetary Incentive Delay task during fMRI.

RESULTS

PwP exhibited hypoactivation of the striatum and anterior insula (AI) during cueing of potential future rewards with each diagnostic group showing hypoactivations during reward anticipation compared to controls. Despite normative task performance, relatives demonstrated caudate activation intermediate between controls and PwP, nucleus accumbens activation more similar to PwP than controls, but putamen activation on par with controls. Across diagnostic groups of PwP there was less functional connectivity between bilateral caudate and several regions of the salience network (medial frontal gyrus, anterior cingulate, AI) during reward anticipation.

CONCLUSIONS

Findings implicate less activation and connectivity in reward processing brain regions across a spectrum of disorders involving psychotic psychopathology. Specifically, aberrations in striatal and insular activity during reward anticipation seen in schizophrenia are partially shared with other forms of psychotic psychopathology and associated with genetic liability for psychosis.

Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: A systematic review and meta-analysis

Predicting treatment outcome in internalizing mental disorders prior to treatment initiation is pivotal for precision mental healthcare. In this regard, resting-state functional connectivity (rs-FC) and machine learning have often shown promising prediction accuracies. This systematic review and meta-analysis evaluates these studies, considering their risk of bias through the Prediction Model Study Risk of Bias Assessment Tool (PROBAST). We examined the predictive performance of features derived from rs-FC, identified features with the highest predictive value, and assessed the employed machine learning pipelines. We searched the electronic databases Scopus, PubMed and PsycINFO on the 12th of December 2022, which resulted in 13 included studies. The mean balanced accuracy for predicting treatment outcome was 77% (95% CI: [72%- 83%]). rs-FC of the dorsolateral prefrontal cortex had high predictive value in most studies. However, a high risk of bias was identified in all studies, compromising interpretability. Methodological recommendations are provided based on a comprehensive exploration of the studies' machine learning pipelines, and potential fruitful developments are discussed.

Association of temporal discounting with transdiagnostic symptom dimensions

Temporal discounting (TD), the tendency to devalue future rewards as a function of delay until receipt, is aberrant in many mental disorders. Identifying symptom patterns and transdiagnostic dimensions associated with TD could elucidate mechanisms responsible for clinically impaired decision-making and facilitate identifying intervention targets. Here, we tested in a general population sample (N = 731) the extent to which TD was related to different symptom patterns and whether effects of time framing (dates/delay units) and monetary magnitude (large/small) had particularly strong effects in people scoring higher on specific symptom patterns. Analyses revealed that TD was related to symptom patterns loading on anxious-depression and inattention-impulsivity-overactivity dimensions. Moreover, TD was lower in the date than the delay version and with higher magnitudes, especially in people scoring higher on the inattention-impulsivity-overactivity dimension. Overall, this study provides evidence for TD as a transdiagnostic process across affective and impulsivity-related dimensions. Future studies should test framing interventions in clinical populations characterized by impulsivity.Preregistration: This research was preregistered at https://osf.io/fg9sc .

A multidimensional investigation of sleep and biopsychosocial profiles with associated neural signatures

Sleep is essential for optimal functioning and health. Interconnected to multiple biological, psychological and socio-environmental factors (i.e., biopsychosocial factors), the multidimensional nature of sleep is rarely capitalized on in research. Here, we deployed a data-driven approach to identify sleep-biopsychosocial profiles that linked self-reported sleep patterns to inter-individual variability in health, cognition, and lifestyle factors in 770 healthy young adults. We uncovered five profiles, including two profiles reflecting general psychopathology associated with either reports of general poor sleep or an absence of sleep complaints (i.e., sleep resilience) respectively. The three other profiles were driven by sedative-hypnotics-use and social satisfaction, sleep duration and cognitive performance, and sleep disturbance linked to cognition and mental health. Furthermore, identified sleep-biopsychosocial profiles displayed unique patterns of brain network organization. In particular, somatomotor network connectivity alterations were involved in the relationships between sleep and biopsychosocial factors. These profiles can potentially untangle the interplay between individuals' variability in sleep, health, cognition and lifestyle - equipping research and clinical settings to better support individual's well-being.

Amphetamine increases motivation of humans and mice as measured by breakpoint, but does not affect an Electroencephalographic biomarker

Translation of drug targets from preclinical studies to clinical trials has been aided by cross-species behavioral tasks, but evidence for brain-based engagement during task performance is still required. Cross-species progressive ratio breakpoint tasks (PRBTs) measure motivation-related behavior and are pharmacologically and clinically sensitive. We recently advanced elevated parietal alpha power as a cross-species electroencephalographic (EEG) biomarker of PRBT engagement. Given that amphetamine increases breakpoint in mice, we tested its effects on breakpoint and parietal alpha power in both humans and mice. Twenty-three healthy participants performed the PRBT with EEG after amphetamine or placebo in a double-blind design. C57BL/6J mice were trained on PRBT with EEG (n = 24) and were treated with amphetamine or vehicle. A second cohort of mice was trained on PRBT without EEG (n = 40) and was treated with amphetamine or vehicle. In humans, amphetamine increased breakpoint. In mice, during concomitant EEG, 1 mg/kg of amphetamine significantly decreased breakpoint. In cohort 2, however, 0.3 mg/kg of amphetamine increased breakpoint consistent with human findings. Increased alpha power was observed in both species as they reached breakpoint, replicating previous findings. Amphetamine did not affect alpha power in either species. Amphetamine increased effort in humans and mice. Consistent with previous reports, elevated parietal alpha power was observed in humans and mice as they performed the PRBT. Amphetamine did not affect this EEG biomarker of effort. Hence, these findings support the pharmacological predictive validity of the PRBT to measure effort in humans and mice and suggest that this EEG biomarker is not directly reflective of amphetamine-induced changes in effort.

Integrating Biobehavioral and Environmental Components of Developmental Psychopathology via Interpersonal Dynamics: An RDoC-Advancing Model

Although the Research Diagnostic Criteria (RDoC) framework proposes biological and environmental mechanisms intersect in the etiology of psychopathology, there is no guidance on how to define or measure experiences in the environment within the RDoC matrix. Interpersonal dynamics during caregiver-child interactions involve temporal coordination of interacting partners' biobehavioral functioning; repeated experiences of signaling to caregivers and responding to caregivers' signals shape children's subsequent socioemotional and brain development. We begin with a review of the extant literature on caregiver-child dynamics, which reveals that RDoC's units of analysis (brain circuits, physiology, behavior, and self-report) are inextricably linked with moment-to-moment changes in the caregiving environment. We then offer a proof-of-concept for integrating biobehavioral RDoC units and environmental components via caregiver-child dynamics. Our approach uses dynamic structural equation models to estimate within-dyad dynamics involving arousal, social, cognitive, and negative or positive affective processes based on second-by-second changes in parasympathetic activity (RSA) during a conflict discussion and a positive event-planning task. Our results illustrate variation in parent-child RSA synchrony, suggesting differences depending on the driver (i.e., child- or parent-led) and on the unique and intersecting domains involved (e.g., positive or negative affect valence systems). We conclude with recommendations for conducting robust, methodologically rigorous studies of interpersonal dynamics that advance the RDoC framework and provide a summary of the clinical implications of this research. Examining caregiver-child dynamics during and across multiple dyadic interaction paradigms that differentially elicit key domains of functioning can deepen understanding of how caregiver- and child-led interpersonal dynamics contribute to child psychopathology risk.

Integrating mindfulness into the extended process model of emotion regulation: The dual-mode model of mindful emotion regulation

Extensive research has been conducted regarding how people manage their emotions. Within this research, there has been growing attention toward the role of mindfulness in emotion regulation. While prior reviews have discussed mindfulness in the context of emotion regulation, they have not provided a thorough integration using the prevailing models of emotion regulation or mindfulness. The present review discusses the Extended Process Model of Emotion Regulation and Monitoring and Acceptance Theory of mindfulness in order to propose a novel integrated framework, the Dual-mode Model of Mindful Emotion Regulation (D-MER). This model proposes two "modes" of mindfulness: Implementation and facilitation. Implementation posits that mindfulness skills can be used as emotion regulation strategies through attentional deployment and cognitive change. Facilitation posits that mindfulness as a state or trait affects emotion generation and regulation through effects on cognitive processes and positive or negative valence systems. Further, the D-MER posits that mindfulness experience can improve the efficiency of mindfulness-based emotion regulation strategies (implementation) while effects of mindfulness on emotion regulation processes become increasingly trait-like and automatic over time (facilitation). Empirical and theoretical support for this model are discussed, specific hypotheses to guide further research are provided, and clinical implications are presented. Use of this model may identify mechanisms underlying the interaction between mindfulness and emotion regulation which can be used in ongoing affective and clinical research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Relationship Between Emotion Dysregulation and Error Monitoring in Adolescents with ADHD

Attention-deficit/hyperactivity disorder (ADHD) is emblematic of the limitations of existing diagnostic categories. One potential solution, consistent with the Research Domain Criteria (RDoC) initiative, is to interrogate psychological mechanisms at the behavioral and physiological level together to try and identify meaningful subgroups within existing categories. Such approaches provide a way to revise diagnostic boundaries and clarify individual variation in mechanisms. Here, we illustrate this approach to help resolve heterogeneity in ADHD using a combination of behaviorally-rated temperament measures from the Early Adolescent Temperament Questionnaire; cognitive performance on three difference conditions of an emotional go/no-go task; and electroencephalogram (EEG)-measured variation in multiple stages of error processing, including the error-related negativity (ERN) and positivity (Pe). In a large (N = 342), well-characterized sample of adolescents with ADHD, latent profile analysis identified two ADHD temperament subgroups: 1) emotionally regulated and 2) emotionally dysregulated (with high negative affect). Cognitive and EEG assessment in a subset of 272 adolescents (nADHD = 151) found that the emotionally dysregulated group showed distinct patterns of change in early neural response to errors (ERN) across emotional task conditions as compared to emotionally-regulated ADHD adolescents and typically-developing controls. Both ADHD groups showed blunted later response to errors (Pe) that was stable across emotional task conditions. Overall, neural response patterns identified important differences in how trait and state emotion interact to affect cognitive processing. Results highlight important temperament variation within ADHD that helps clarify its relationship to the ERN, one of the most prominent putative neural biomarkers for psychopathology.

More reliable biomarkers and more accurate prediction for mental disorders using a label-noise filtering-based dimensional prediction method

The integration of neuroimaging with artificial intelligence is crucial for advancing the diagnosis of mental disorders. However, challenges arise from incomplete matching between diagnostic labels and neuroimaging. Here, we propose a label-noise filtering-based dimensional prediction (LAMP) method to identify reliable biomarkers and achieve accurate prediction for mental disorders. Our method proposes to utilize a label-noise filtering model to automatically filter out unclear cases from a neuroimaging perspective, and then the typical subjects whose diagnostic labels align with neuroimaging measures are used to construct a dimensional prediction model to score independent subjects. Using fMRI data of schizophrenia patients and healthy controls (n = 1,245), our method yields consistent scores to independent subjects, leading to more distinguishable relabeled groups with an enhanced classification accuracy of 31.89%. Additionally, it enables the exploration of stable abnormalities in schizophrenia. In summary, our LAMP method facilitates the identification of reliable biomarkers and accurate diagnosis of mental disorders using neuroimages.

The High Rates of Comorbidity among Neurodevelopmental Disorders: Reconsidering the Clinical Utility of Distinct Diagnostic Categories

The boundaries between neurodevelopmental disorders are often indistinct, even among specialists. But do these boundaries exist, or do experts struggle to distinguish and categorize symptoms in order to arrive at a dominant diagnosis while comorbidity continually leaves questions about where each disorder ends and begins? What should be reconsidered? The introduction of the term 'spectrum of neurodevelopmental disorders' could pave the way for a re-appraisal of the clinical continuum of neurodevelopmental disorders. This study aims to highlight the problems that emerge in the field of the differential diagnosis of neurodevelopmental disorders and propose a renegotiation of the distinctiveness criteria.

Assessing pragmatic language difficulties using the Revised Children's Communication Checklist-2. Exploratory structural equation modeling and associations with restricted and repetitive behaviors

In this paper, we investigated the psychometric properties of the Child Communication Checklist-Revised (CCC-R) for the first time with an English-speaking sample. We used a confirmatory application of exploratory structural equation modeling (ESEM) to re-evaluate the CCC-R's psychometric properties. We found strong support for its use as an assessment for pragmatic and structural language. Our second main aim was to explore associations between pragmatic and structural language and restricted and repetitive behaviors (RRBs), two hallmark characteristics of autism. We used the CCC-R and Repetitive Behavior Questionnaire (RBQ-2) to investigate these associations in a diverse non-clinical sample of children, taking a transdiagnostic approach. We intentionally excluded autism and other neurodevelopmental diagnoses to test, (1) the CCC-R in a broad sample and (2) the association between pragmatic language and RRB in children not already selected for that association. The sample comprised two groups of children, one was community sampled (n = 123) and the other (n = 143) included children with non-specific behavioral, emotional and/or cognitive difficulties referred to an assessment unit by schools. We found clear associations between pragmatic language difficulties and RRBs in both groups. Regression analysis showed that pragmatic language was the only significant contributor to RRBs even after Grammatical-Semantic score, age, sex, and socioeconomic status were controlled. The pattern was the same for both recruitment groups. However, the effects were stronger for the school-referred group which also had more pragmatic difficulties, grammatical-semantic difficulties and RRBs. A robust link between pragmatic language and RRBs, established in autism, has continuity across the broader non-clinical population.

The cognitive neuroscience of self-awareness: Current framework, clinical implications, and future research directions

Self-awareness, the ability to take oneself as the object of awareness, has been an enigma for our species, with different answers to this question being provided by religion, philosophy, and, more recently, science. The current review aims to discuss the neurocognitive mechanisms underlying self-awareness. The multidimensional nature of self-awareness will be explored, suggesting how it can be thought of as an emergent property observed in different cognitive complexity levels, within a predictive coding approach. A presentation of alterations of self-awareness in neuropsychiatric conditions will ground a discussion on alternative frameworks to understand this phenomenon, in health and psychopathology, with future research directions being indicated to fill current gaps in the literature. This article is categorized under: Philosophy > Consciousness Psychology > Brain Function and Dysfunction Neuroscience > Cognition.

Machine Learning of Functional Connectivity to Biotype Alcohol and Nicotine Use Disorders

BACKGROUND

Magnetic resonance imaging provides noninvasive tools to investigate alcohol use disorder (AUD) and nicotine use disorder (NUD) and neural phenotypes for genetic studies. A data-driven transdiagnostic approach could provide a new perspective on the neurobiology of AUD and NUD.

METHODS

Using samples of individuals with AUD (n = 140), individuals with NUD (n = 249), and healthy control participants (n = 461) from the UK Biobank, we integrated clinical, neuroimaging, and genetic markers to identify biotypes of AUD and NUD. We partitioned participants with AUD and NUD based on resting-state functional connectivity (FC) features associated with clinical metrics. A multitask artificial neural network was trained to evaluate the cluster-defined biotypes and jointly infer AUD and NUD diagnoses.

RESULTS

Three biotypes-primary NUD, mixed NUD/AUD with depression and anxiety, and mixed AUD/NUD-were identified. Multitask classifiers incorporating biotype knowledge achieved higher area under the curve (AUD: 0.76, NUD: 0.74) than single-task classifiers without biotype differentiation (AUD: 0.61, NUD: 0.64). Cerebellar FC features were important in distinguishing the 3 biotypes. The biotype of mixed NUD/AUD with depression and anxiety demonstrated the largest number of FC features (n = 5), all related to the visual cortex, that significantly differed from healthy control participants and were validated in a replication sample (p < .05). A polymorphism in TNRC6A was associated with the mixed AUD/NUD biotype in both the discovery (p = 7.3 × 10-5) and replication (p = 4.2 × 10-2) sets.

CONCLUSIONS

Biotyping and multitask learning using FC features can characterize the clinical and genetic profiles of AUD and NUD and help identify cerebellar and visual circuit markers to differentiate the AUD/NUD group from the healthy control group. These markers support a new growing body of literature.

What's next for the field of multigenerational mental health? The need for deep behavioral phenotyping via a prenatal mental health registry

From its inception, development and psychopathology theorists have sought to uncover the earliest forms of risk for mental health challenges in children, to prevent the development of more severe, intractable manifestations of psychopathology. Large familial risk registries have advanced our understanding of early, potentially modifiable factors that could prevent or mitigate the expression of challenging symptoms of neurodevelopmental conditions, and similar registries have been proposed to advance understanding of ADHD and related phenotypes. Data from single-site studies, largely focused on perinatal exposure to maternal mood disorders, reveal that a robust predictor of child psychopathology is parental psychopathology. However, early developmental trajectories of psychopathology risk may be better captured using transdiagnostic approaches in pregnancy, capturing the full range of mental health symptoms. We describe here the need for a parental mental health registry that begins prenatally that includes deep behavioral phenotyping across a range of transdiagnostic indicators of mental health risk to prevent psychopathology in children. This registry has the potential to uncover pathways to psychopathology risk in childhood and support the discovery of novel mechanisms to be targeted for prevention and intervention.

Feedback negativity and feedback-related P3 in individuals at risk for depression: Comparing surface potentials and current source densities

Blunted responses to reward feedback have been linked to major depressive disorder (MDD) and depression risk. Using a monetary incentive delay task (win, loss, break-even), we investigated the impact of family risk for depression and lifetime history of MDD and anxiety disorder with 72-channel electroencephalograms (EEG) recorded from 29 high-risk and 32 low-risk individuals (15-58 years, 30 male). Linked-mastoid surface potentials (ERPs) and their corresponding reference-free current source densities (CSDs) were quantified by temporal principal components analysis (PCA). Each PCA solution revealed a midfrontal feedback negativity (FN; peak around 310 ms) and a posterior feedback-P3 (fb-P3; 380 ms) as two distinct reward processing stages. Unbiased permutation tests and multilevel modeling of component scores revealed greater FN to loss than win and neutral for all stratification groups, confirming FN sensitivity to valence. Likewise, all groups had greater fb-P3 to win and loss than neutral, confirming that fb-P3 indexes motivational salience and allocation of attention. By contrast, group effects were subtle, dependent on data transformation (ERP, CSD), and did not confirm reduced FN or fb-P3 for at-risk individuals. Instead, CSD-based fb-P3 was overall reduced in individuals with than without MDD history, whereas ERP-based fb-P3 was greater for high-risk individuals than for low-risk individuals for monetary, but not neutral outcomes. While the present findings do not support blunted reward processing in depression and depression risk, our side-by-side comparison underscores how the EEG reference choice affects the characterization of subtle group differences, strongly advocating the use of reference-free techniques.