Brain connectivity changes occurring following cognitive behavioural therapy for psychosis predict long-term recovery

Uncovering the determinants of brain functioning, behavior and their interplay in the light of context

Notwithstanding the huge progress in molecular and cellular neuroscience, our ability to understand the brain and develop effective treatments promoting mental health is still limited. This can be partially ascribed to the reductionist, deterministic and mechanistic approaches in neuroscience that struggle with the complexity of the central nervous system. Here, I introduce the Context theory of constrained systems proposing a novel role of contextual factors and genetic, molecular and neural substrates in determining brain functioning and behavior. This theory entails key conceptual implications. First, context is the main driver of behavior and mental states. Second, substrates, from genes to brain areas, have no direct causal link to complex behavioral responses as they can be combined in multiple ways to produce the same response and different responses can impinge on the same substrates. Third, context and biological substrates play distinct roles in determining behavior: context drives behavior, substrates constrain the behavioral repertoire that can be implemented. Fourth, since behavior is the interface between the central nervous system and the environment, it is a privileged level of control and orchestration of brain functioning. Such implications are illustrated through the Kitchen metaphor of the brain. This theoretical framework calls for the revision of key concepts in neuroscience and psychiatry, including causality, specificity and individuality. Moreover, at the clinical level, it proposes treatments inducing behavioral changes through contextual interventions as having the highest impact to reorganize the complexity of the human mind and to achieve a long-lasting improvement in mental health.

Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions

Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.

Psychosis spectrum illnesses as disorders of prefrontal critical period plasticity

Emerging research on neuroplasticity processes in psychosis spectrum illnesses-from the synaptic to the macrocircuit levels-fill key gaps in our models of pathophysiology and open up important treatment considerations. In this selective narrative review, we focus on three themes, emphasizing alterations in spike-timing dependent and Hebbian plasticity that occur during adolescence, the critical period for prefrontal system development: (1) Experience-dependent dysplasticity in psychosis emerges from activity decorrelation within neuronal ensembles. (2) Plasticity processes operate bidirectionally: deleterious environmental and experiential inputs shape microcircuits. (3) Dysregulated plasticity processes interact across levels of scale and time and include compensatory mechanisms that have pathogenic importance. We present evidence that-given the centrality of progressive dysplastic changes, especially in prefrontal cortex-pharmacologic or neuromodulatory interventions will need to be supplemented by corrective learning experiences for the brain if we are to help people living with these illnesses to fully thrive.

Chronic traumatic encephalopathy-a blueprint for the bridge between neurological and psychiatric disorders

Chronic traumatic encephalopathy (CTE) is a perplexing condition characterized by a broad and diverse range of neuropathology and psychopathology. While there are no agreed upon or validated clinical criteria for CTE, case series of CTE have described a wide range of neuropsychiatric symptoms that have been attributed to repetitive traumatic brain injuries (rTBI). However, the direct links between the psychopathology of psychiatric and neurological conditions from rTBI to CTE remains poorly understood. Prior studies suggest that repetitive cerebral injuries are associated with damage to neural circuitry involved in emotional and memory processes, but these studies do not offer longitudinal assessments that prove causation. More recent studies on novel targets, such as transmission of misfolded proteins, as well as newly advanced non-invasive imaging techniques may offer more direct evidence of the pathogenesis of CTE by tracing the progression of pathology and display of related behavioral impairments. Understanding this interface in the context of rTBI can play an important role in future approaches to the definition, assessment, prevention, and treatment of CTE and mental illnesses.

Sex Differences in Salience Network Connectivity and its Relationship to Sensory Over-Responsivity in Youth with Autism Spectrum Disorder

Individuals with autism spectrum disorder (ASD) are significantly more likely to experience sensory over-responsivity (SOR) compared to neurotypical controls. SOR in autism has been shown to be related to atypical functional connectivity in the salience network (SN), a brain network thought to help direct attention to the most relevant stimuli in one's environment. However, all studies to date which have examined the neurobiological basis of sensory processing in ASD have used primarily male samples so little is known about sex differences in the neural processing of sensory information. This study examined the relationship between SOR and resting-state functional connectivity in the SN for 37 males and 16 females with autism, ages 8-17 years. While there were no sex differences in parent-rated SOR symptoms, there were significant sex differences in how SOR related to SN connectivity. Relative to females with ASD, males with ASD showed a stronger association between SOR and increased connectivity between the salience and primary sensory networks, suggesting increased allocation to sensory information. Conversely, for females with ASD, SOR was more strongly related to increased connectivity between the SN and prefrontal cortex. Results suggest that the underlying mechanisms of SOR in ASD are sex specific, providing insight into the differences seen in the diagnosis rate and symptom profiles of males and females with ASD. LAY SUMMARY: Sensory over-responsivity (SOR) is common in autism. Most research on the neural basis of SOR has focused on males, so little is known about SOR or its neurobiology in females with autism spectrum disorder. Here despite no sex differences in SOR symptoms, we found sex differences in how SOR related to intrinsic connectivity in a salience detection network. Results show sex differences in the neural mechanisms underlying SOR and inform sex differences seen in diagnosis rates and symptom profiles in autism. Autism Res 2020, 13: 1489-1500. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Cognitive markers related to long-term remission status in Schizophrenia Spectrum Disorders

Cognitive impairment is an established feature of schizophrenia. From a cross-sectional perspective, studies have revealed associations between cognition and remission. Few studies have examined this relationship longitudinally. Here we examine which cognitive domains might be related to long-term remission and symptomatic severity. The present study followed 173 outpatients with schizophrenia for five years, divided into groups based on long-term remission status and symptomatic severity, assessed with the Positive and Negative Syndrome Scale. Cognitive functioning was assessed at baseline, with tests of vigilance, executive functions, processing speed, memory and learning, working memory, and premorbid functioning. Cognitive domains related to long-term remission status were executive functions, working memory, and premorbid functioning. The most prominent cognitive differences were found between the group in stable remission with minimal symptoms, and the non-remission group, the first group demonstrating better cognitive functioning. The study highlights the role of premorbid functioning as a cognitive feature in the prediction of long-term remission. It also indicates the possibility of viewing specific cognitive domains as markers for clinical outcome, highlighting the value of early assessment of cognition. In summary, a certain cognitive profile, in coexistence with long-term non-remission, suggests poorer outcome. Hence, this group is in need of increased support.

Under the Hood: Using Computational Psychiatry to Make Psychological Therapies More Mechanism-Focused

Psychological therapies, such as CBT, are an important part of the treatment of a range of psychiatric disorders such as depression and anxiety. There is a growing desire to understand the mechanisms by which such therapies effect change so as to improve treatment outcomes. Here we argue that adopting a computational framework may be one such approach. Computational psychiatry aims to provide a theoretical framework for moving between higher-level psychological states (like emotions, decisions and beliefs) to neural circuits, by modeling these constructs mathematically. These models are explicit hypotheses that contain quantifiable variables and parameters derived from each individual's behavior. This approach has two advantages. Firstly, some of the variables described by these models appears to reflect the neural activity of specific brain regions. Secondly, the parameters estimated by these models may offer a unique description of a patient's symptoms which can be used to both tailor therapy and track its effect. In doing so this approach may offer some additional granularity in understanding how psychological therapies, such as CBT, are working. Although this field shows significant promise, we also highlight several of the key hurdles that must first be overcome before clinical translation of computational insights can be realized.

Neurocognitive Adaptation and Mental Health Vulnerability Following Maltreatment: The Role of Social Functioning

Childhood maltreatment is associated with a lifetime increase in risk of mental health disorder. We propose that such vulnerability may stem in large part from altered patterns of social functioning. Here, we highlight key findings from the psychological and epidemiological literature indicating that early maltreatment experience compromises social functioning and attenuates social support in ways that increase mental health vulnerability. We then review the extant neuroimaging studies of children and adolescents, focusing on three domains implicated in social functioning: threat processing, reward processing, and emotion regulation. We discuss how adaptations in these domains may increase latent vulnerability to mental health problems by impacting on social functioning via increased stress susceptibility as well as increased stress generation. Finally, we explore how computational psychiatry approaches, alongside systematically reported measures of social functioning, can complement studies of neural function in the creation of a mechanistic framework aimed at informing approaches to prevention and intervention.

Depression's Unholy Trinity: Dysregulated Stress, Immunity, and the Microbiome

Depression remains one of the most prevalent psychiatric disorders, with many patients not responding adequately to available treatments. Chronic or early-life stress is one of the key risk factors for depression. In addition, a growing body of data implicates chronic inflammation as a major player in depression pathogenesis. More recently, the gut microbiota has emerged as an important regulator of brain and behavior and also has been linked to depression. However, how this holy trinity of risk factors interact to maintain physiological homeostasis in the brain and body is not fully understood. In this review, we integrate the available data from animal and human studies on these three factors in the etiology and progression of depression. We also focus on the processes by which this microbiota-immune-stress matrix may influence centrally mediated events and on possible therapeutic interventions to correct imbalances in this triune.

Association of antidepressants with brain morphology in early stages of psychosis: an imaging genomics approach

Depressive symptoms in subjects at Clinical High Risk for Psychosis (CHR-P) or at first-episode psychosis (FEP) are often treated with antidepressants. Our cross-sectional study investigated whether brain morphology is altered by antidepressant medication. High-resolution T₁-weighted structural MRI scans of 33 CHR-P and FEP subjects treated with antidepressants, 102 CHR-P and FEP individuals without antidepressant treatment and 55 controls, were automatically segmented using Freesurfer 6.0. Linear mixed-effects modelling was applied to assess the differences in subcortical volume, surface area and cortical thickness in treated, non-treated and healthy subjects, taking into account converted dosages of antidepressants. Increasing antidepressant dose was associated with larger volume of the pallidum and the putamen, and larger surface of the left inferior temporal gyrus. In a pilot subsample of separately studied subjects of known genomic risk loci, we found that in the right postcentral gyrus, the left paracentral lobule and the precentral gyrus antidepressant dose-associated surface increase depended on polygenic schizophrenia-related-risk score. As the reported regions are linked to the symptoms of psychosis, our findings reflect the possible beneficial effects of antidepressant treatment on an emerging psychosis.

Treating the "E" in "G × E": Trauma-Informed Approaches and Psychological Therapy Interventions in Psychosis

Despite advances in genetic research, causal variants affecting risk for schizophrenia remain poorly characterized, and the top 108 loci identified through genome-wide association studies (GWAS) explain only 3.4% of variance in risk profiles. Such work is defining the highly complex nature of this condition, with omnigenic models of schizophrenia suggesting that gene regulatory networks are sufficiently interconnected such that altered expression of any "peripheral" gene in a relevant cell type has the capacity to indirectly modulate the expression of "core" schizophrenia-associated genes. This wealth of associated genes with small effect sizes makes identifying new druggable targets difficult, and current pharmacological treatments for schizophrenia can involve serious side effects. However, the fact that the majority of schizophrenia genome-wide associated variants fall within non-coding DNA is suggestive of their potential to modulate gene regulation. This would be consistent with risks that can be mediated in a "gene × environment" (G × E) manner. Stress and trauma can alter the regulation of key brain-related pathways over the lifetime of an individual, including modulation of brain development, and neurochemistry in the adult. Recent studies demonstrate a significant overlap between psychotic symptoms and trauma, ranging from prior trauma contributing to psychosis, as well as trauma in response to the experience of psychosis itself or in response to treatment. Given the known effects of trauma on both CNS gene expression and severity of psychosis symptoms, it may be that pharmacological treatment alone risks leaving individuals with a highly stressful and unresolved environmental component that continues to act in a "G × E" manner, with the likelihood that this would negatively impact recovery and relapse risk. This review aims to cover the recent advances elucidating the complex genetic architecture of schizophrenia, as well as the long-term effects of early life trauma on brain function and future mental health risk. Further, the evidence demonstrating the role of ongoing responses to trauma or heightened stress sensitivity, and their impact on the course of illness and recovery, is presented. Finally, the need for trauma-informed approaches and psychological therapy-based interventions is discussed, and a brief overview of the evidence to determine their utility is presented.

Using fMRI and machine learning to predict symptom improvement following cognitive behavioural therapy for psychosis

Cognitive behavioural therapy for psychosis (CBTp) involves helping patients to understand and reframe threatening appraisals of their psychotic experiences to reduce distress and increase functioning. Whilst CBTp is effective for many, it is not effective for all patients and the factors predicting a good outcome remain poorly understood. Machine learning is a powerful approach that allows new predictors to be identified in a data-driven way, which can inform understanding of the mechanisms underlying therapeutic interventions, and ultimately make predictions about symptom improvement at the individual patient level. Thirty-eight patients with a diagnosis of schizophrenia completed a social affect task during functional MRI. Multivariate pattern analysis assessed whether treatment response in those receiving CBTp (n = 22) could be predicted by pre-therapy neural responses to facial affect that was either threat-related (ambiguous ‘neutral’ faces perceived as threatening in psychosis, in addition to angry and fearful faces) or prosocial (happy faces). The models predicted improvement in psychotic (r = 0.63, p = 0.003) and affective (r = 0.31, p = 0.05) symptoms following CBTp, but not in the treatment-as-usual group (n = 16). Psychotic symptom improvement was predicted by neural responses to threat-related affect across sensorimotor and frontal-limbic regions, whereas affective symptom improvement was predicted by neural responses to fearful faces only as well as prosocial affect across sensorimotor and frontal regions. These findings suggest that CBTp most likely improves psychotic and affective symptoms in those endorsing more threatening appraisals and mood-congruent processing biases, respectively, which are explored and reframed as part of the therapy. This study improves our understanding of the neurobiology of treatment response and provides a foundation that will hopefully lead to greater precision and tailoring of the interventions offered to patients.

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Machine learning models using neuroimaging data can predict response to CBTp.

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Neural responses to social threat predicted improvement in psychotic symptoms.

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Activation related to different social stimuli predicted distinct symptom domains.

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Predictors included activity in the hippocampus, frontal, and sensorimotor regions.

Mechanistic insights into the genetics of affective psychosis from Prader-Willi syndrome

Schizophrenia and bipolar disorder are common, severe, and disabling psychotic disorders, which are difficult to research. We argue that the genetically determined neurodevelopmental disorder Prader-Willi syndrome (PWS), which is associated with a high risk of affective psychotic illness, can provide a window into genetic mechanisms and associated neural pathways. People with PWS can all show non-psychotic psychopathology and problem behaviours, but the prevalence of psychotic illness differs markedly by genetic subtype; people with PWS due to chromosome 15 maternal uniparental disomy have higher prevalence of psychotic illness compared with patients with PWS due to 15q11-13 deletions of paternal origin. On the basis of this observation and the neural differences between genetic subtypes, we hypothesise that the combined effects of the absent expression of specific maternally imprinted genes at 15q11-13, and excess maternally imprinted or paternally expressed genes on chromosome 15, affect the γ-aminobutyric acid-glutamatergic pathways and associated neural networks that underpin mood regulation and sensory processing, resulting in psychotic illness. We propose a model of potential mechanisms of psychosis in PWS, which might be relevant in the general population, and should inform future research.