Neural substrates underlying delusions in schizophrenia

Brain structural alterations associated with impulsiveness in male violent patients with schizophrenia

BACKGROUND

Violence in schizophrenia (SCZ) is a phenomenon associated with neurobiological factors. However, the neural mechanisms of violence in patients with SCZ are not yet sufficiently understood. Thus, this study aimed to explore the structural changes associated with the high risk of violence and its association with impulsiveness in patients with SCZ to reveal the possible neurobiological basis.

METHOD

The voxel-based morphometry approach and whole-brain analyses were used to measure the alteration of gray matter volume (GMV) for 45 schizophrenia patients with violence (VSC), 45 schizophrenia patients without violence (NSC), and 53 healthy controls (HC). Correlation analyses were used to examine the association of impulsiveness and brain regions associated with violence.

RESULTS

The results demonstrated reduced GMV in the right insula within the VSC group compared with the NSC group, and decreased GMV in the right temporal pole and left orbital part of superior frontal gyrus only in the VSC group compared to the HC group. Spearman correlation analyses further revealed a positive correlation between impulsiveness and GMV of the left superior temporal gyrus, bilateral insula and left medial orbital part of the superior frontal gyrus in the VSC group.

CONCLUSION

Our findings have provided further evidence for structural alterations in patients with SCZ who had engaged in severe violence, as well as the relationship between the specific brain alterations and impulsiveness. This work provides neural biomarkers and improves our insight into the neural underpinnings of violence in patients with SCZ.

Neural mechanism underlying the beneficial effect of Theory of Mind psychotherapy on early-onset schizophrenia: a randomized controlled trial

BACKGROUND

Psychosocial interventions have emerged as an important component of a comprehensive therapeutic approach in early-onset schizophrenia, typically representing a more severe form of the disorder. Despite the feasibility and efficacy of Theory of Mind (ToM) psychotherapy for schizophrenia, relatively little is known regarding the neural mechanism underlying its effect on early-onset schizophrenia.

METHODS

We performed a randomized, active controlled trial in patients with early-onset schizophrenia, who were randomly allocated into either an intervention (ToM psychotherapy) or an active control (health education) group. Diffusion tensor imaging data were collected to construct brain structural networks, with both global and regional topological properties measured using graph theory.

RESULTS

We enrolled 28 patients with early-onset schizophrenia in our study. After 5 weeks of treatment, both the intervention and active control groups showed significant improvement in psychotic symptoms, yet the improvement was greater in the intervention group. Importantly, in contrast with no brain structural network change after treatment in the active control group, the intervention group showed increased nodal centrality of the left insula that was associated with psychotic symptom improvement.

LIMITATIONS

We did not collect important information concerning the participants' cognitive abilities, particularly ToM performance.

CONCLUSION

These findings suggest a potential neural mechanism by which ToM psychotherapy exerts a beneficial effect on early-onset schizophrenia via strengthening the coordination capacity of the insula in brain structural networks, which may provide a clinically translatable biomarker for monitoring or predicting responses to ToM psychotherapy.Clinical trial registration: NCT05577338; ClinicalTrials.gov.

The effects of abnormal visual experience on neurodevelopmental disorders

Normal visual development is supported by intrinsic neurobiological mechanisms and by appropriate stimulation from the environment, both of which facilitate the maturation of visual functions. However, an offset of this balance can give rise to visual disorders. Therefore, understanding the factors that support normal vision during development and in the mature brain is important, as vision guides movement, enables social interaction, and allows children to recognize and understand their environment. In this paper, we review fundamental mechanisms that support the maturation of visual functions and discuss and draw links between the perceptual and neurobiological impairments in autism spectrum disorder (ASD) and schizophrenia. We aim to explore how this is evident in the case of ASD, and how perceptual and neurobiological deficits further degrade social ability. Furthermore, we describe the altered perceptual experience of those with schizophrenia and evaluate theories of the underlying neural deficits that alter perception.

Cerebral blood flow in schizophrenia: A systematic review and meta-analysis of MRI-based studies

INTRODUCTION

Schizophrenia-spectrum disorders (SSD) represent one of the leading causes of disability worldwide and are usually underpinned by neurodevelopmental brain abnormalities observed on a structural and functional level. Nuclear medicine imaging studies of cerebral blood flow (CBF) have already provided insights into the pathophysiology of these disorders. Recent developments in non-invasive MRI techniques such as arterial spin labeling (ASL) have allowed broader examination of CBF across SSD prompting us to conduct an updated literature review of MRI-based perfusion studies. In addition, we conducted a focused meta-analysis of whole brain studies to provide a complete picture of the literature on the topic.

METHODS

A systematic OVID search was performed in Embase, MEDLINEOvid, and PsycINFO. Studies eligible for inclusion in the review involved: 1) individuals with SSD, first-episode psychosis or clinical-high risk for psychosis, or; 2) had healthy controls for comparison; 3) involved MRI-based perfusion imaging methods; and 4) reported CBF findings. No time span was specified for the database queries (last search: 08/2022). Information related to participants, MRI techniques, CBF analyses, and results were systematically extracted. Whole-brain studies were then selected for the meta-analysis procedure. The methodological quality of each included studies was assessed.

RESULTS

For the systematic review, the initial Ovid search yielded 648 publications of which 42 articles were included, representing 3480 SSD patients and controls. The most consistent finding was that negative symptoms were linked to cortical fronto-limbic hypoperfusion while positive symptoms seemed to be associated with hyperperfusion, notably in subcortical structures. The meta-analysis integrated results from 13 whole-brain studies, across 426 patients and 401 controls, and confirmed the robustness of the hypoperfusion in the left superior and middle frontal gyri and right middle occipital gyrus while hyperperfusion was found in the left putamen.

CONCLUSION

This updated review of the literature supports the implication of hemodynamic correlates in the pathophysiology of psychosis symptoms and disorders. A more systematic exploration of brain perfusion could complete the search of a multimodal biomarker of SSD.

State-like changes in the salience network correlate with delusion severity in first-episode psychosis patients

BACKGROUND AND HYPOTHESIS

Delusions are characteristic of psychotic disorders; however, the brain correlates of delusions remain poorly known. Imaging studies on delusions typically compare images across individuals. Related confounding of inter-individual differences beyond delusions may be avoided by comparing delusional and non-delusional states within individuals.

STUDY DESIGN

We studied correlations of delusions using intra-subject correlation (intra-SC) and inter-subject correlation of functional magnetic resonance imaging (fMRI) signal time series, obtained during a movie stimulus at baseline and follow-up. We included 27 control subjects and 24 first-episode psychosis patients, who were free of delusions at follow-up, to calculate intra-SC between fMRI signals obtained during the two time points. In addition, we studied changes in functional connectivity at baseline and during the one-year follow-up using regions where delusion severity correlated with intra-SC as seeds.

RESULTS

The intra-SC correlated negatively with the baseline delusion severity in the bilateral anterior insula. In addition, we observed a subthreshold cluster in the anterior cingulate. These three regions constitute the cortical salience network (SN). Functional connectivity between the bilateral insula and the precuneus was weaker in the patients at baseline than in patients at follow-up or in control subjects at any time point.

CONCLUSIONS

The results suggest that intra-SC is a powerful tool to study brain correlates of symptoms and highlight the role of the SN and internetwork dysconnectivity between the SN and the default mode network in delusions.

Clinical and Structural Differences in Delusions Across Diagnoses: A Systematic Review

Delusions are marked, fixed beliefs that are incongruent with reality. Delusions, with comorbid hallucinations, are a hallmark of certain psychotic disorders (e.g., schizophrenia). Delusions can present transdiagnostically, in neurodegenerative (e.g., Alzheimer's disease and fronto-temporal dementia), nervous system disorders (e.g., Parkinson's disease) and across other psychiatric disorders (e.g., bipolar disorder). The burden of delusions is severe and understanding the heterogeneity of delusions may delineate a more valid nosology of not only psychiatric disorders but also neurodegenerative and nervous system disorders. We systematically reviewed structural neuroimaging studies reporting on delusions in four disorder types [schizophrenia (SZ), bipolar disorder (BP), Alzheimer's disease (AD), and Parkinson's disease (PD)] to provide a comprehensive overview of neural changes and clinical presentations associated with delusions. Twenty-eight eligible studies were identified. This review found delusions were most associated with gray matter reductions in the dorsolateral prefrontal cortex (SZ, BP, and AD), left claustrum (SZ and AD), hippocampus (SZ and AD), insula (SZ, BP, and AD), amygdala (SZ and BP), thalamus (SZ and AD), superior temporal gyrus (SZ, BP, and AD), and middle frontal gyrus (SZ, BP, AD, and PD). However, there was a great deal of variability in the findings of each disorder. There is some support for the current dopaminergic hypothesis of psychosis, but we also propose new hypotheses related to the belief formation network and cognitive biases. We also propose a standardization of assessments to aid future transdiagnostic study approaches. Future studies should explore the neural and biological underpinnings of delusions to hopefully, inform future treatment.

Multi-scale semi-supervised clustering of brain images: Deriving disease subtypes

Disease heterogeneity is a significant obstacle to understanding pathological processes and delivering precision diagnostics and treatment. Clustering methods have gained popularity for stratifying patients into subpopulations (i.e., subtypes) of brain diseases using imaging data. However, unsupervised clustering approaches are often confounded by anatomical and functional variations not related to a disease or pathology of interest. Semi-supervised clustering techniques have been proposed to overcome this and, therefore, capture disease-specific patterns more effectively. An additional limitation of both unsupervised and semi-supervised conventional machine learning methods is that they typically model, learn and infer from data using a basis of feature sets pre-defined at a fixed anatomical or functional scale (e.g., atlas-based regions of interest). Herein we propose a novel method, "Multi-scAle heteroGeneity analysIs and Clustering" (MAGIC), to depict the multi-scale presentation of disease heterogeneity, which builds on a previously proposed semi-supervised clustering method, HYDRA. It derives multi-scale and clinically interpretable feature representations and exploits a double-cyclic optimization procedure to effectively drive identification of inter-scale-consistent disease subtypes. More importantly, to understand the conditions under which the clustering model can estimate true heterogeneity related to diseases, we conducted extensive and systematic semi-simulated experiments to evaluate the proposed method on a sizeable healthy control sample from the UK Biobank (N = 4403). We then applied MAGIC to imaging data from Alzheimer's disease (ADNI, N = 1728) and schizophrenia (PHENOM, N = 1166) patients to demonstrate its potential and challenges in dissecting the neuroanatomical heterogeneity of common brain diseases. Taken together, we aim to provide guidance regarding when such analyses can succeed or should be taken with caution. The code of the proposed method is publicly available at https://github.com/anbai106/MAGIC.

White matter microstructure in schizophrenia patients with a history of violence

Schizophrenia (SCZ) is associated with increased risk of violence compared to the general population. Neuroimaging research suggests SCZ to be a disorder of disrupted connectivity, with diffusion tensor imaging (DTI) indicating white matter (WM) abnormalities. It has been hypothesized that SCZ patients with a history of violence (SCZ-V) have brain abnormalities distinguishing them from SCZ patients with no history of violence (SCZ-NV). Yet, a thorough investigation of the neurobiological underpinnings of state and trait measures of violence and aggression in SCZ derived from DTI indices is lacking. Using tract-based spatial statistics, we compared DTI-derived microstructural indices: fractional anisotropy (FA), mean, axial (AD) and radial diffusivity across the brain; (1) between SCZ-V (history of murder, attempted murder, or severe assault towards other people, n = 24), SCZ-NV (n = 52) and healthy controls (HC, n = 94), and (2) associations with current aggression scores among both SCZ groups. Then, hypothesis-driven region of interest analyses of the uncinate fasciculus and clinical characteristics including medication use were performed. SCZ-V and SCZ-NV showed decreased FA and AD in widespread regions compared to HC. There were no significant differences on any DTI-based measures between SCZ-V and SCZ-NV, and no significant associations between state or trait measures of aggression and any of the DTI metrics in the ROI analyses. The DTI-derived WM differences between SCZ and HC are in line with previous findings, but the results do not support the hypothesis of specific brain WM microstructural correlates of violence or aggression in SCZ.

Atrophy of right inferior frontal orbital gyrus and frontoparietal functional connectivity abnormality in depressed suicide attempters

Although structural and functional brain abnormalities have been observed in depressed suicide attempters (DS), structural deficits and functional impairments together with their relationship in DS remain unclear. To clarify this issue, we aimed to examine the differences in gray matter (GM) alteration, corresponding functional connectivity (FC) change, and their relationship between DS and depressed non-suicide attempters (NDS). Sixty-eight DS, 119 NDS and 103 healthy controls were enrolled and subjected to magnetic resonance imaging scans. The patients were evaluated using the 17-item Hamilton Rating Scale for Depression (HRSD) and Nurses' Global Assessment of Suicide Risk (NGASR) scale. Both voxel-based morphometry and resting-state FC analyses were performed based on functional and structural imaging data. Compared with NDS, the DS group showed reduced GM volume in the right inferior frontal orbital gyrus (IFOG) and left caudate (CAU) but increased GM volume in the left calcarine fissure, weaker negative right IFOG-left rectus gyrus (REG) FC, and weaker positive right IFOG-left inferior parietal lobule (IPL) FC. In DS, the GM volume of the right IFOG and left CAU was negatively correlated with NGASR and HRSD scores, respectively; the right IFOG-left IPL FC was negatively correlated with cognitive factor scores; and the GM volume of the right IFOG was positively correlated with IFOG-REG and IFOG-IPL FC. Our findings indicate that structural deficit with its related functional alterations in brain circuits converged in right IFOG centralized pathways and may play a central role in suicidal behaviors in depression.

Aberrant Gray Matter Volume and Cortical Surface in Paranoid-Type Delusional Disorder

INTRODUCTION

Delusions are core symptoms of schizophrenia-spectrum and related disorders. Despite their clinical relevance, the neural correlates underlying such phenomena are unclear. Recent research suggests that specific delusional content may be associated with distinct neural substrates.

OBJECTIVE

Here, we used structural magnetic resonance imaging to investigate multiple parameters of brain morphology in patients presenting with paranoid type delusional disorder (pt-DD, n = 14) compared to those of healthy controls (HC, n = 25).

METHODS

Voxel- and surface-based morphometry for structural data was used to investigate gray matter volume (GMV), cortical thickness (CT) and gyrification.

RESULTS

Compared to HC, patients with pt-DD showed reduced GMV in bilateral amygdala and right inferior frontal gyrus. Higher GMV in patients was found in bilateral orbitofrontal and in left superior frontal cortices. Patients also had lower CT in frontal and temporal regions. Abnormal gyrification in patients was evident in frontal and temporal areas, as well as in bilateral insula.

CONCLUSIONS

The data suggest the presence of aberrant GMV in a right prefrontal region associated with belief evaluation, as well as distinct structural abnormalities in areas that essentially subserve processing of fear, anxiety and threat in patients with pt-DD. It is possible that cortical features of distinct evolutionary and genetic origin, i.e. CT and gyrification, contribute differently to the pathogenesis of pt-DD.

MK-Curve improves sensitivity to identify white matter alterations in clinical high risk for psychosis

Diffusion kurtosis imaging (DKI) is a diffusion MRI approach that enables the measurement of brain microstructural properties, reflecting molecular restrictions and tissue heterogeneity. DKI parameters such as mean kurtosis (MK) provide additional subtle information to that provided by popular diffusion tensor imaging (DTI) parameters, and thus have been considered useful to detect white matter abnormalities, especially in populations that are not expected to show severe brain pathologies. However, DKI parameters often yield artifactual output values that are outside of the biologically plausible range, which diminish sensitivity to identify true microstructural changes. Recently we have proposed the mean-kurtosis-curve (MK-Curve) method to correct voxels with implausible DKI parameters, and demonstrated its improved performance against other approaches that correct artifacts in DKI. In this work, we aimed to evaluate the utility of the MK-Curve method to improve the identification of white matter abnormalities in group comparisons. To do so, we compared group differences, with and without the MK-Curve correction, between 115 individuals at clinical high risk for psychosis (CHR) and 93 healthy controls (HCs). We also compared the correlation of the corrected and uncorrected DKI parameters with clinical characteristics. Following the MK-curve correction, the group differences had larger effect sizes and higher statistical significance (i.e., lower p-values), demonstrating increased sensitivity to detect group differences, in particular in MK. Furthermore, the MK-curve-corrected DKI parameters displayed stronger correlations with clinical variables in CHR individuals, demonstrating the clinical relevance of the corrected parameters. Overall, following the MK-curve correction our analyses found widespread lower MK in CHR that overlapped with lower fractional anisotropy (FA), and both measures were significantly correlated with a decline in functioning and with more severe symptoms. These observations further characterize white matter alterations in the CHR stage, demonstrating that MK and FA abnormalities are widespread, and mostly overlap. The improvement in group differences and stronger correlation with clinical variables suggest that applying MK-curve would be beneficial for the detection and characterization of subtle group differences in other experiments as well.

Common and Distinct Alterations of Cognitive Function and Brain Structure in Schizophrenia and Major Depressive Disorder: A Pilot Study

Objective: Numerous studies indicate that schizophrenia (SCZ) and major depressive disorder (MDD) share pathophysiological characteristics. Investigating the neurobiological features of psychiatric-affective disorders may facilitate the diagnosis of psychiatric disorders. Hence, we aimed to explore whether patients with SCZ and patients with MDD had the similar or distinct cognitive impairments and GMV alterations to further understand their underlying pathophysiological mechanisms. Methods: We recruited a total of 52 MDD patients, 64 SCZ patients, and 65 healthy controls (HCs). The Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery was used to assess cognitive functions. In addition, voxel-based morphometry (VBM) analysis was used to evaluate the gray matter volume (GMV) by using MRI scanning. One-way ANOVA and post-hoc tests were used to find the differences among the MDD, SCZ, and HCs. Finally, we explored the correlation between structural alterations and cognitive functions. Results: Compared with that of HCs, processing speed was impaired in both patients with SCZ and patients with MDD (F = 49.505, p < 0.001). SCZ patients displayed impaired cognitive performance in all dimensions of cognitive functions compared with HCs (p < 0.001, except social cognition, p = 0.043, Bonferroni corrected). Whole-brain VBM analysis showed that both SCZ and MDD groups had reductions of GMV in the medial superior frontal cortex (cluster-level FWE p < 0.05). Patients with SCZ exhibited declining GMV in the anterior cingulate cortex and right middle frontal cortex (MFC) compared with HCs and MDD patients (cluster-level FWE p < 0.05). The mean values of GMV in the right MFC had a positive correlation with the attention/vigilance function in patients with MDD (p = 0.014, partial. r = 0.349, without Bonferroni correction). Conclusions: In total, our study found that MDD and SCZ groups had common cognitive impairments and brain structural alterations, but the SCZ group exhibited more severe impairment than the MDD group in both fields. The above findings may provide a potential support for recognizing the convergent and divergent brain neural pathophysiological mechanisms between MDD and SCZ.

Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning

Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic cohort, using novel semi-supervised machine learning methods designed to discover patterns associated with disease rather than normal anatomical variation. Structural MRI and clinical measures in established schizophrenia (n = 307) and healthy controls (n = 364) were analysed across three sites of PHENOM (Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging) consortium. Regional volumetric measures of grey matter, white matter, and CSF were used to identify distinct and reproducible neuroanatomical subtypes of schizophrenia. Two distinct neuroanatomical subtypes were found. Subtype 1 showed widespread lower grey matter volumes, most prominent in thalamus, nucleus accumbens, medial temporal, medial prefrontal/frontal and insular cortices. Subtype 2 showed increased volume in the basal ganglia and internal capsule, and otherwise normal brain volumes. Grey matter volume correlated negatively with illness duration in Subtype 1 (r = -0.201, P = 0.016) but not in Subtype 2 (r = -0.045, P = 0.652), potentially indicating different underlying neuropathological processes. The subtypes did not differ in age (t = -1.603, df = 305, P = 0.109), sex (chi-square = 0.013, df = 1, P = 0.910), illness duration (t = -0.167, df = 277, P = 0.868), antipsychotic dose (t = -0.439, df = 210, P = 0.521), age of illness onset (t = -1.355, df = 277, P = 0.177), positive symptoms (t = 0.249, df = 289, P = 0.803), negative symptoms (t = 0.151, df = 289, P = 0.879), or antipsychotic type (chi-square = 6.670, df = 3, P = 0.083). Subtype 1 had lower educational attainment than Subtype 2 (chi-square = 6.389, df = 2, P = 0.041). In conclusion, we discovered two distinct and highly reproducible neuroanatomical subtypes. Subtype 1 displayed widespread volume reduction correlating with illness duration, and worse premorbid functioning. Subtype 2 had normal and stable anatomy, except for larger basal ganglia and internal capsule, not explained by antipsychotic dose. These subtypes challenge the notion that brain volume loss is a general feature of schizophrenia and suggest differential aetiologies. They can facilitate strategies for clinical trial enrichment and stratification, and precision diagnostics.

Transdiagnostic Approach to Olfactory Reference Syndrome: Neurobiological Considerations

Olfactory reference syndrome (ORS) describes a constellation of emotional and behavioral symptoms that cause clinically significant distress or impairment arising from the false belief that one is emitting an offensive odor. Despite cases of ORS reported throughout the world over the last century, our knowledge and understanding of ORS remain relatively poor because of the limited literature-mostly case studies and series, but no clinical trials. ORS continues to pose significant diagnostic challenges within our current frameworks of categorizing mental disorders, including the Diagnostic and Statistical Manual of Mental Disorders and International Classification of Diseases. We review the ORS literature and discuss diagnostic parallels and challenges of placing ORS within specific categories. We also review the current research on the neurocircuitry of olfaction and of disorders with potential clinical relevance to patients presenting with ORS. While no primary neuroscientific research has specifically investigated ORS, an overlapping circuitry has been implicated in the neurobiology of obsessive-compulsive, trauma and stressor, and psychotic spectrum disorders, suggesting that the phenomenology of ORS can best be understood through a dimensional, rather than categorical, approach.

The Amygdala in Schizophrenia and Bipolar Disorder: A Synthesis of Structural MRI, Diffusion Tensor Imaging, and Resting-State Functional Connectivity Findings

Frequently implicated in psychotic spectrum disorders, the amygdala serves as an important hub for elucidating the convergent and divergent neural substrates in schizophrenia and bipolar disorder, the two most studied groups of psychotic spectrum conditions. A systematic search of electronic databases through December 2017 was conducted to identify neuroimaging studies of the amygdala in schizophrenia and bipolar disorder, focusing on structural MRI, diffusion tensor imaging (DTI), and resting-state functional connectivity studies, with an emphasis on cross-diagnostic studies. Ninety-four independent studies were selected for the present review (49 structural MRI, 27 DTI, and 18 resting-state functional MRI studies). Also selected, and analyzed in a separate meta-analysis, were 33 volumetric studies with the amygdala as the region-of-interest. Reduced left, right, and total amygdala volumes were found in schizophrenia, relative to both healthy controls and bipolar subjects, even when restricted to cohorts in the early stages of illness. No volume abnormalities were observed in bipolar subjects relative to healthy controls. Shape morphometry studies showed either amygdala deformity or no differences in schizophrenia, and no abnormalities in bipolar disorder. In contrast to the volumetric findings, DTI studies of the uncinate fasciculus tract (connecting the amygdala with the medial- and orbitofrontal cortices) largely showed reduced fractional anisotropy (a marker of white matter microstructure abnormality) in both schizophrenia and bipolar patients, with no cross-diagnostic differences. While decreased amygdalar-orbitofrontal functional connectivity was generally observed in schizophrenia, varying patterns of amygdalar-orbitofrontal connectivity in bipolar disorder were found. Future studies can consider adopting longitudinal approaches with multimodal imaging and more extensive clinical subtyping to probe amygdalar subregional changes and their relationship to the sequelae of psychotic disorders.

Common gray and white matter abnormalities in schizophrenia and bipolar disorder

This study aimed to investigate abnormalities in the gray matter and white matter (GM and WM, respectively) that are shared between schizophrenia (SZ) and bipolar disorder (BD). We used 3T-magnetic resonance imaging to examine patients with SZ, BD, or healthy control (HC) subjects (aged 20–50 years, N = 65 in each group). We generated modulated GM maps through voxel-based morphometry (VBM) for T1-weighted images and skeletonized fractional anisotropy, mean diffusion, and radial diffusivity maps through tract-based special statistics (TBSS) methods for diffusion tensor imaging (DTI) data. These data were analyzed using a generalized linear model with pairwise comparisons between groups with a family-wise error corrected P < 0.017. The VBM analysis revealed widespread decreases in GM volume in SZ compared to HC, but patients with BD showed GM volume deficits limited to the right thalamus and left insular lobe. The TBSS analysis showed alterations of DTI parameters in widespread WM tracts both in SZ and BD patients compared to HC. The two disorders had WM alterations in the corpus callosum, superior longitudinal fasciculus, internal capsule, external capsule, posterior thalamic radiation, and fornix. However, we observed no differences in GM volume or WM integrity between SZ and BD. The study results suggest that GM volume deficits in the thalamus and insular lobe along with widespread disruptions of WM integrity might be the common neural mechanisms underlying the pathologies of SZ and BD.

Advances in microstructural diffusion neuroimaging for psychiatric disorders

Understanding the neuropathological underpinnings of mental disorders such as schizophrenia, major depression, and bipolar disorder is an essential step towards the development of targeted treatments. Diffusion MRI studies utilizing the diffusion tensor imaging (DTI) model have been extremely successful to date in identifying microstructural brain abnormalities in individuals suffering from mental illness, especially in regions of white matter, although identified abnormalities have been biologically non-specific. Building on DTI's success, in recent years more advanced diffusion MRI methods have been developed and applied to the study of psychiatric populations, with the aim of offering increased sensitivity to subtle neurological abnormalities, as well as improved specificity to candidate pathologies such as demyelination and neuroinflammation. These advanced methods, however, usually come at the cost of prolonged imaging sequences or reduced signal to noise, and they are more difficult to evaluate compared with the more simplified approach taken by the now common DTI model. To date, a limited number of advanced diffusion MRI methods have been employed to study schizophrenia, major depression and bipolar disorder populations. In this review we survey these studies, compare findings across diverse methods, discuss the main benefits and limitations of the different methods, and assess the extent to which the application of more advanced diffusion imaging approaches has led to novel and transformative information with regards to our ability to better understand the etiology and pathology of mental disorders.

Multisite Machine Learning Analysis Provides a Robust Structural Imaging Signature of Schizophrenia Detectable Across Diverse Patient Populations and Within Individuals

Past work on relatively small, single-site studies using regional volumetry, and more recently machine learning methods, has shown that widespread structural brain abnormalities are prominent in schizophrenia. However, to be clinically useful, structural imaging biomarkers must integrate high-dimensional data and provide reproducible results across clinical populations and on an individual person basis. Using advanced multi-variate analysis tools and pooled data from case-control imaging studies conducted at 5 sites (941 adult participants, including 440 patients with schizophrenia), a neuroanatomical signature of patients with schizophrenia was found, and its robustness and reproducibility across sites, populations, and scanners, was established for single-patient classification. Analyses were conducted at multiple scales, including regional volumes, voxelwise measures, and complex distributed patterns. Single-subject classification was tested for single-site, pooled-site, and leave-site-out generalizability. Regional and voxelwise analyses revealed a pattern of widespread reduced regional gray matter volume, particularly in the medial prefrontal, temporolimbic and peri-Sylvian cortex, along with ventricular and pallidum enlargement. Multivariate classification using pooled data achieved a cross-validated prediction accuracy of 76% (AUC = 0.84). Critically, the leave-site-out validation of the detected schizophrenia signature showed accuracy/AUC range of 72-77%/0.73-0.91, suggesting a robust generalizability across sites and patient cohorts. Finally, individualized patient classifications displayed significant correlations with clinical measures of negative, but not positive, symptoms. Taken together, these results emphasize the potential for structural neuroimaging data to provide a robust and reproducible imaging signature of schizophrenia. A web-accessible portal is offered to allow the community to obtain individualized classifications of magnetic resonance imaging scans using the methods described herein.

Meaning in meaninglessness: The propensity to perceive meaningful patterns in coincident events and randomly arranged stimuli is linked to enhanced attention in early sensory processing

Perception of objectively independent events or stimuli as being significantly connected and the associated proneness to perceive meaningful patterns constitute part of the positive symptoms of schizophrenia, which are associated with altered attentional processes in lateralized speech perception. Since perceiving meaningful patterns is to some extent already prevalent in the general population, the aim of the study was to investigate whether the propensity to experience meaningful patterns in co-occurring events and random stimuli may be associated with similar altered attentional processes in lateralized speech perception. Self-reported and behavioral indicators of the perception of meaningful patterns were assessed in non-clinical individuals, along with EEG auditory evoked potentials during the performance of an attention related lateralized speech perception task (Dichotic Listening Test). A greater propensity to perceive meaningful patterns was associated with higher N1 amplitudes of the evoked potentials to the onset of the dichotically presented consonant-vowel syllables, indicating enhanced automatic attention in early sensory processing. The study suggests that more basic mechanisms in how people associate events may play a greater role in the cognitive biases that are manifest in personality expressions such as positive schizotypy, rather than that positive schizotypy moderates these cognitive biases directly.

Understanding Antipsychotic Drug Treatment Effects: A Novel Method to Reduce Pseudospecificity of the Positive and Negative Syndrome Scale (PANSS) Factors

The Positive and Negative Syndrome Scale (PANSS) is the most widely used efficacy measure in acute treatment studies of schizophrenia. However, interpretation of the efficacy of antipsychotics in improving specific symptom domains is confounded by moderate-to-high correlations among standard (Marder) PANSS factors. The authors review the results of an uncorrelated PANSS score matrix (UPSM) transform designed to reduce pseudospecificity in assessment of symptom change in patients with schizophrenia. Based on a factor analysis of five pooled, placebo-controlled lurasidone clinical trials (N=1,710 patients), a UPSM transform was identified that generated PANSS factors with high face validity (good correlation with standard Marder PANSS factors), and high specificity/orthogonality (low levels of between-factor correlation measuring change during treatment). Between-factor correlations were low at baseline for both standard (Marder) PANSS factors and transformed PANSS factors. However, when measured change in symptom severity was measured during treatment (in a pooled 5-study analysis), there was a notable difference for standard PANSS factors, where changes across factors were found to be highly correlated (factors exhibited pseudospecificity), compared to transformed PANSS factors, where factor change scores exhibited the same low levels of between-factor correlation observed at baseline. At Week 6-endpoint, correlations among PANSS factor severity scores were moderate-to-high for standard factors (0.34-0.68), but continued to be low for the transformed factors (-0.22-0.20). As an additional validity check, we analyzed data from one of the original five pooled clinical trials that included other well-validated assessment scales (MADRS, Negative Symptom Assessment scale [NSA]). In this baseline analysis, UPSM-transformed PANSS factor severity scores (negative and depression factors) were found to correlate well with the MADRS and NSA. The availability of transformed PANSS factors with a high degree of orthogonality/specificity, but which retain a high degree of concurrent and face validity, can reduce pseudospecificity as a measurement confound, and should facilitate the drug development process, permitting a more accurate characterization of the efficacy of putative new agents in targeting specific symptom domains in patients with psychotic illness.

Decreased Left Putamen and Thalamus Volume Correlates with Delusions in First-Episode Schizophrenia Patients

BACKGROUND

Delusional thinking is one of the hallmark symptoms of schizophrenia. However, the underlying neural substrate for delusions in schizophrenia remains unknown. In an attempt to further our understanding of the neural basis of delusions, we explored gray matter deficits and their clinical associations in first-episode schizophrenia patients with and without delusions.

METHODS

Twenty-four first-episode schizophrenia patients with delusions and 18 without delusions as well as 26 healthy controls (HC) underwent clinical assessment and whole-brain structural imaging which were acquired a 3.0 T scanner. Voxel-based morphometry was used to explore inter-group differences in gray matter volume using analysis of covariance, and Spearman correlation coefficients (rho) between the Scale for the Assessment of Positive Symptoms (SAPS)-delusion scores and mean regional brain volumes was obtained.

RESULTS

Patients with delusions showed decreased brain gray matter volumes in the left putamen, thalamus, and caudate regions compared with HC. Patients with delusions also showed decreased regional volume in the left putamen and thalamus compared with patients without delusions. SAPS-delusion scores were negatively correlated with the gray matter volumes of the left putamen and thalamus.

DISCUSSION

Left putamen and thalamus volume loss may be biological correlates of delusions in schizophrenia.