Transdiagnostic neural markers of emotion-cognition interaction in psychotic disorders

Crisis of objectivity: using a personalized network model to understand maladaptive sensemaking in a patient with psychotic, affective, and obsessive-compulsive symptoms

Introduction

Psychiatric comorbidities have proven a consistent challenge. Recent approaches emphasize the need to move away from categorical descriptions of symptom clusters towards a dimensional view of mental disorders. From the perspective of phenomenological psychopathology, this shift is not enough, as a more detailed understanding of patients' lived experience is necessary as well. One phenomenology-informed approach suggests that we can better understand the nature of psychiatric disorders through personalized network models, a comprehensive description of a person's lifeworld in the form of salient nodes and the relationships between them. We present a detailed case study of a patient with multiple comorbidities, maladaptive coping mechanisms, and adverse childhood experiences.

Methods

The case was followed for a period of two years, during which we collected multiple streams of data, ranging from phenomenological interviews, neuropsychological assessments, language analysis, and semi-structured interviews (Examination of Anomalous Self Experience and Examination of Anomalous World Experience). We analytically constructed a personalized network model of his lifeworld.

Results

We identified an experiential category "the crisis of objectivity" as the core psychopathological theme of his lifeworld. It refers to his persistent mistrust towards any information that he obtains that he appraises as originating in his subjectivity. We can developmentally trace the crisis of objectivity to his adverse childhood experience, as well as him experiencing a psychotic episode in earnest. He developed various maladaptive coping mechanisms in order to compensate for his psychotic symptoms. Interestingly, we found correspondence between his subjective reports and other sources of data.

Discussion

Hernan exhibits difficulties in multiple Research Domain Criteria constructs. While we can say that social sensorimotor, positive valence, and negative valence systems dysfunctions are likely associated with primary deficit (originating in his adverse childhood experience), his cognitive symptoms may be tied to his maladaptive coping mechanisms (although, they might be related to his primary disorder as well).

Cognitive insight in first-episode psychosis: Exploring the complex relationship between executive functions and social cognition

Social cognition (SC) and executive function (EF) have been described as important variables for social functioning and recovery of patients with psychosis. However, the relationship between SC and EF in first-episode psychosis (FEP) deserves further investigation, especially focusing on gender differences.

AIMS

To investigate the relationship between EF and different domains of SC in FEP patients and to explore gender differences in the relationship between these domains.

METHODS

A cross-sectional study of 191 patients with new-onset psychosis recruited from two multicenter clinical trials. A comprehensive cognitive battery was used to assess SC (Hinting Task, Face Test and IPSAQ) and EF (TMT, WSCT, Stroop Test and digit span - WAIS-III). Pearson correlations and linear regression models were performed.

RESULTS

A correlation between Theory of Mind (ToM), Emotional Recognition (ER) and EF was found using the complete sample. Separating the sample by gender showed different association profiles between these variables in women and men.

CONCLUSIONS

A relationship between different domains of SC and EF is found. Moreover, women and men presented distinct association profiles between EF and SC. These results should be considered in order to improve the treatment of FEP patients and designing personalized interventions by gender.

White matter integrity in adolescent irritability: A preliminary study

Irritability is a prevalent, impairing transdiagnostic symptom, especially during adolescence, yet little is known about irritability's neural mechanisms. A few studies examined the integrity of white matter tracts that facilitate neural communication in irritability, but only with extreme, disorder-related symptom presentations. In this preliminary study, we used a group connectometry approach to identify white matter tracts correlated with transdiagnostic irritability in a community/clinic-based sample of 35 adolescents (mean age = 14 years, SD = 2.0). We found positive and negative associations with irritability in local white matter tract bundles including sections of the longitudinal fasciculus; frontoparietal, parolfactory, and parahippocampal cingulum; corticostriatal and thalamocortical radiations; and vertical occipital fasciculus. Our findings support functional neuroimaging studies that implicate widespread neural pathways, particularly emotion and reward networks, in irritability. Our findings of positive and negative associations reveal a complex picture of what is "good" white matter connectivity. By characterizing irritability's neural underpinnings, targeted interventions may be developed.

Neural Connectivity Underlying Reward and Emotion-Related Processing: Evidence From a Large-Scale Network Analysis

Neuroimaging techniques have advanced our knowledge about neurobiological mechanisms of reward and emotion processing. It remains unclear whether reward and emotion-related processing share the same neural connection topology and how intrinsic brain functional connectivity organization changes to support emotion- and reward-related prioritized effects in decision-making. The present study addressed these challenges using a large-scale neural network analysis approach. We applied this approach to two independent functional magnetic resonance imaging datasets, where participants performed a reward value or emotion associative matching task with tight control over experimental conditions. The results revealed that interaction between the Default Mode Network, Frontoparietal, Dorsal Attention, and Salience networks engaged distinct topological structures to support the effects of reward, positive and negative emotion processing. Detailed insights into the properties of these connections are important for understanding in detail how the brain responds in the presence of emotion and reward related stimuli. We discuss the linking of reward- and emotion-related processing to emotional regulation, an important aspect of regulation of human behavior in relation to mental health.

Linking RDoC and HiTOP: A new interface for advancing psychiatric nosology and neuroscience

The Research Domain Criteria (RDoC) and the Hierarchical Taxonomy of Psychopathology (HiTOP) represent major dimensional frameworks proposing two alternative approaches to accelerate progress in the way psychopathology is studied, classified, and treated. RDoC is a research framework rooted in neuroscience aiming to further the understanding of transdiagnostic biobehavioral systems underlying psychopathology and ultimately inform future classifications. HiTOP is a dimensional classification system, derived from the observed covariation among symptoms of psychopathology and maladaptive traits, which seeks to provide more informative research and treatment targets (i.e., dimensional constructs and clinical assessments) than traditional diagnostic categories. This article argues that the complementary strengths of RDoC and HiTOP can be leveraged in order to achieve their respective goals. RDoC's biobehavioral framework may help elucidate the underpinnings of the clinical dimensions included in HiTOP, whereas HiTOP may provide psychometrically robust clinical targets for RDoC-informed research. We present a comprehensive mapping between dimensions included in RDoC (constructs and subconstructs) and HiTOP (spectra and subfactors) based on narrative review of the empirical literature. The resulting RDoC-HiTOP interface sheds light on the biobehavioral correlates of clinical dimensions and provides a broad set of dimensional clinical targets for etiological and neuroscientific research. We conclude with future directions and practical recommendations for using this interface to advance clinical neuroscience and psychiatric nosology. Ultimately, we envision that this RDoC-HiTOP interface has the potential to inform the development of a unified, dimensional, and biobehaviorally-grounded psychiatric nosology.

What we think about when we think about predictive processing

The predictive processing framework (PPF) attempts to tackle deep philosophical problems, including how the brain generates consciousness, how our bodies influence cognition, and how cognition alters perception. As such, it provides a zeitgeist that incorporates concepts from physics, computer science, mathematics, artificial intelligence, economics, psychology, and neuroscience, leveraging and, in turn, influencing recent advances in reinforcement learning and deep learning that underpin the artificial intelligence in many of the applications with which we interact daily. PPF purports to provide no less than a grand unifying theory of mind and brain function, underwriting an account of perception, cognition, and action and their dynamic relationships. While mindful of legitimate criticisms of the framework, to which we return below, an important test of PPF is its utility in accounting for individual differences such as psychopathology. These, then, are the central concern of this special section of the Journal of Abnormal Psychology: What is the state of the art with regards to applying the PPF to the symptoms of mental illness? How might we leverage its insights to elevate and systematize our explanations, and ideally treatments, of those symptoms? And, conversely, can we refine and refute aspects of the PPF by considering the particular challenges that our patients experience as departures from the parametric estimates of the PPF? (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum

The Hierarchical Taxonomy of Psychopathology (HiTOP) is a scientific effort to address shortcomings of traditional mental disorder diagnoses, which suffer from arbitrary boundaries between psychopathology and normality, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. This paper synthesizes evidence on the validity and utility of the thought disorder and detachment spectra of HiTOP. These spectra are composed of symptoms and maladaptive traits currently subsumed within schizophrenia, other psychotic disorders, and schizotypal, paranoid and schizoid personality disorders. Thought disorder ranges from normal reality testing, to maladaptive trait psychoticism, to hallucinations and delusions. Detachment ranges from introversion, to maladaptive detachment, to blunted affect and avolition. Extensive evidence supports the validity of thought disorder and detachment spectra, as each spectrum reflects common genetics, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, biomarkers, and treatment response. Some of these characteristics are specific to one spectrum and others are shared, suggesting the existence of an overarching psychosis superspectrum. Further research is needed to extend this model, such as clarifying whether mania and dissociation belong to thought disorder, and explicating processes that drive development of the spectra and their subdimensions. Compared to traditional diagnoses, the thought disorder and detachment spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and higher acceptability to clinicians. Validated measures are available to implement the system in practice. The more informative, reliable and valid characterization of psychosis-related psychopathology offered by HiTOP can make diagnosis more useful for research and clinical care.

Transdiagnostic psychiatry: a systematic review

The usefulness of current psychiatric classification, which is based on ICD/DSM categorical diagnoses, remains questionable. A promising alternative has been put forward as the "transdiagnostic" approach. This is expected to cut across existing categorical diagnoses and go beyond them, to improve the way we classify and treat mental disorders. This systematic review explores whether self-defining transdiagnostic research meets such high expectations. A multi-step Web of Science literature search was performed according to an a priori protocol, to identify all studies that used the word "transdiagnostic" in their title, up to May 5, 2018. Empirical variables which indexed core characteristics were extracted, complemented by a bibliometric and conceptual analysis. A total of 111 studies were included. Most studies were investigating interventions, followed by cognition and psychological processes, and neuroscientific topics. Their samples ranged from 15 to 91,199 (median 148) participants, with a mean age from 10 to more than 60 (median 33) years. There were several methodological inconsistencies relating to the definition of the gold standard (DSM/ICD diagnoses), of the outcome measures and of the transdiagnostic approach. The quality of the studies was generally low and only a few findings were externally replicated. The majority of studies tested transdiagnostic features cutting across different diagnoses, and only a few tested new classification systems beyond the existing diagnoses. About one fifth of the studies were not transdiagnostic at all, because they investigated symptoms and not disorders, a single disorder, or because there was no diagnostic information. The bibliometric analysis revealed that transdiagnostic research largely restricted its focus to anxiety and depressive disorders. The conceptual analysis showed that transdiagnostic research is grounded more on rediscoveries than on true innovations, and that it is affected by some conceptual biases. To date, transdiagnostic approaches have not delivered a credible paradigm shift that can impact classification and clinical care. Practical "TRANSD"iagnostic recommendations are proposed here to guide future research in this field.