We tested the hypothesis that Schizophrenia (SCZ) involves a systematic breakdown in brain network organization across different levels of graph-theoretical hierarchy.

Excoriation disorder (ExD), or skin picking disorder, is a chronic body-focused repetitive behavior (BFRB) that leads to severe tissue damage, disfigurement, and psychological distress. Despite its prevalence, the neurobiological etiology of ExD remains poorly understood, hindering early diagnosis and intervention. This systematic review synthesizes findings from neuroimaging studies reporting on neural correlates of ExD. A comprehensive search of PubMed, PsycINFO, and Web of Science identified 18 studies meeting inclusion criteria. Across 784 ExD participants and 530 controls, consistent patterns emerged in brain regions related to sensorimotor inhibition, habit formation, and perceptual-affective interaction. Structural MRI showed smaller volumes in the orbitofrontal cortex, insula, and cerebellum, but increased size of nucleus accumbens, associated in previous studies with deficient inhibitory control. Task-related fMRI showed increased activation in frontal and parietal regions but diminished engagement of posterior cerebellar-prefrontal circuits during sensorimotor coordination, and amplified insula and amygdala responses to aversive stimuli. Resting-state fMRI linked ExD symptom severity with reduced supplementary motor and prefrontal connectivity. The findings consistently point to deviation in networks subserving sensorimotor-emotional integration, one of the earliest stages of brain-behavior development. A hypothesis of ExD as a developmental disorder is suggested, guiding future research to early markers of detection and prevention.

This commentary article delves into the study by M. Beño-Ruiz-de-la-Sierra et al., which investigates the role of corollary discharge dysfunction in anomalous self-experiences (ASEs) among schizophrenic patients. The study's findings, while insightful, prompt further exploration into the specific brain regions involved, the statistical methods employed, and the implications for different schizophrenia subtypes. This paper aims to supplement the discussion by suggesting areas for future research and methodological enhancements.

Major Depressive Disorder (MDD) is a common mental disorder that severely impacts patients' quality of life and social functioning. Early diagnosis is crucial for improving treatment outcomes, so rapid and accurate diagnosis of MDD is of significant importance. This paper combines static and dynamic functional connectivity analyses based on fMRI data and proposes a novel feature selection method to identify and classify brain network abnormalities in MDD patients. The advantage of this method lies in enhancing classification accuracy through feature fusion while simultaneously reducing feature dimensionality. First, whole-brain correlation analysis is performed based on fMRI functional connectivity, followed by Rich Club analysis and sliding window methods to investigate the topological properties of the intrinsic functional brain network in MDD patients. Finally, the abnormal brain network is used as a feature to classify and diagnose MDD patients and healthy controls, achieving a classification accuracy of 90.28 %. This result validates that the identified abnormal brain networks in this study have clinical significance for assisting in the diagnosis of MDD.

The pathophysiology of schizophrenia and its associated symptoms remains poorly understood despite decades of research utilizing diverse neuroimaging techniques. Recent advancements, such as the analysis of dynamic functional connectivity in resting-state fMRI signals and the application of generative whole-brain models - computational psychiatry tool, offer novel insights into the disorder. In this exploratory study we applied a recently developed phenotypic fitting approach for whole-brain modeling to investigate functional connectivity dynamics correlates of schizophrenia symptoms. Our findings showed that higher hallucination severity was strongly correlated with functional connectivity dynamics resembling those generated by a dynamic mean field model operating with elevated excitation/inhibition balance.

Case studies examining the benefits of transcranial direct current stimulation (tDCS) enhanced exposure response prevention (ERP) reveal clinically significant improvements in symptoms of obsessive-compulsive disorder (OCD). In the absence of control conditions, the validity of these findings requires further study. Efforts are also needed to enhance the longevity of any gains.

Schizophrenia and chronic interictal epileptic psychosis (EPS) are thought to have different underlying pathophysiological mechanisms. We aimed to investigate the neural basis of EPS.

Previous studies have demonstrated the efficacy of transcranial magnetic stimulation (TMS) on treating nicotine addiction. However, the underlying mechanisms remain unclear. This study aims to investigate the effects of repetitive TMS (rTMS) on nicotine addiction using resting-state functional magnetic resonance imaging (rs-fMRI).

The impact of schizophrenia (SZ) and bipolar. disorder (BD) on brain structure is not fully understood, with most evidence derived from European, North American, and Asian populations. Our study aims to evaluate these morphometric changes in cortical thickness(CT) among Afro-descendants and indigenous people. We included neuroimaging data from 23 SZ patients, 20 BD patients, and 21 healthy controls (HC), aged between 22 and 31 years (mean age = 25 years). CT of 68 regions, as defined by the Desikan-Killiany atlas, was obtained using FreeSurfer. Statistical analysis involved analysis of covariance (ANCOVA) controlling for age, with Bonferroni correction for false discovery rate. BD patients showed significantly decreased CT in the right lateral orbitofrontal cortex and left pars orbitalis compared to SZ and HC. In a subset of clinical patients (SZ and BD), depressive symptoms, as measured by Diagnostic Interview for Psychosis and Affective Disorders(DIPAD) subscores, correlated negatively with left parahippocampal gyrus thickness, while manic symptoms correlated negatively with right lateral orbitofrontal CT. These findings underscore the importance of including underrepresented populations in neuroimaging research to better understand the structural brain alterations associated with psychiatric disorders.

Altered functional connectivity in several functional networks has been found in people with psychosis, especially in the default mode (DMN), salience (SAL) and central executive (CEN) networks. Functional connectivity in people with psychosis is influenced by traumatic life experiences. Trauma histories typical of people with psychosis are associated with complex post-traumatic stress disorder (cPTSD), but no studies have explored whether post-traumatic sequelae contribute to functional dysconnectivity in people with psychosis.

A major clinical feature of depression is anhedonia, which is closely linked to dysfunction of the reward system. But there is a lack of research on musical reward and its neuroelectrophysiological characteristics in depression. Therefore, we investigated these characteristics of major depressive disorder (MDD).

This study aims to investigate the structural and functional abnormalities in the hippocampus of pediatric bipolar disorder (PBD) patients, distinguishing between non-psychotic (NP-PBD) and psychotic (P-PBD) subtypes, compared to healthy controls (HCs).

Social anxiety disorder (SAD) is associated with negatively biased, self-focused attention in social situations. Neural correlates of self-referential processing and effects of selective serotonin reuptake inhibitors (SSRIs) on it remain, however, poorly known. Interestingly, these drugs have been shown to modify brain activation related to negative bias already before symptom relief in major depressive disorder. We hypothesized alteration in self-referential processing and modification of such alteration during short-term use of escitalopram in SAD.

Cannabidiol (CBD) is being studied as a potential intervention for the people at clinical high risk for psychosis (CHR), though the mechanisms underlying its effects are not fully understood. Previous studies indicate that a single dose of CBD can normalize alterations in memory-related brain activation and modulate hippocampal glutamate levels in the early stages of psychosis. This study aimed to examine the acute effects of CBD on the relationship between hippocampal glutamate levels and brain activation during verbal memory in individuals at CHR.

Schizophrenia is a heterogeneous disorder with significant variability in neurobiological and clinical presentations. In this study, we aimed to investigate neuroanatomical subtypes of schizophrenia using a data-driven machine-learning algorithm. Structural MRI data from 222 participants (136 schizophrenia patients and 86 healthy controls) were analyzed. Subtypes were identified using HYDRA (Heterogeneity Through Discriminative Analysis), a semi-supervised machine learning algorithm designed to reveal disease-related patterns while minimizing the influence of normal anatomical variation followed by voxel-based morphometry (VBM) analysis to compare these subtypes with healthy controls. The study identified two subtypes among schizophrenia patients. Subtype 1 showed widespread lower grey matter volumes in several cortical regions, mainly in the insula, cingulate, frontal, and temporal regions. Subtype 2 demonstrated increased subcortical volumes, pallidal volumes relative to controls and thalamus, hippocampus relative to subtype 1. Despite significant neuroanatomical differences, the subtypes did not differ in demographic or clinical characteristics. These findings highlight the potential of machine learning to disentangle structural heterogeneity in schizophrenia, offering a refined framework for neuroanatomical subtyping. Identifying distinct subtypes may contribute to personalized treatment approaches and enhance the precision of future clinical and research efforts.

A negative future outlook increases vulnerability to depression and suicide. Understanding neural mechanisms of future-oriented thinking may reveal insights into suicide risk. This study used fMRI to identify brain activation patterns during future imagination in individuals with recent suicide attempts.

The neural correlates of treatment-resistant depression (TRD) are not fully elucidated. Brainstem functional connectivity (FC) in TRD has rarely been investigated, despite the assumed role of several brainstem nuclei in depression. 23 patients and 23 sex- and age-matched healthy controls underwent resting-state functional MRI. Seed-based connectivity (SBC) was calculated for 37 brainstem seeds with motor and arousal functions. Correlations between significant FC and somatic symptom severity were computed. FC of dorsal raphe nucleus, locus coeruleus, cuneiform nucleus and periaqueductal gray to the precentral and postcentral gyrus was increased. The anterior division of the mesencephalic reticular formation showed increased FC to left frontal pole, left superior frontal gyrus and middle temporal gyrus, whereas its lateral division showed decreased FC to frontal orbital and insular cortex, compared to healthy subjects. FC of bilateral locus coeruleus to bilateral postcentral gyrus were positively correlated with depressive symptoms and the intensity of somatic symptoms. We found increased FC between brainstem and sensorimotor and frontal cortical regions in TRD patients compared to healthy controls. Increased brainstem-cortical FC appeared to be linked with depressive and somatic symptom severity.

Childhood sexual abuse (CSA) can cause lasting neurodevelopmental changes, posing significant challenges for survivors. Its specific impact on men remains heavily stigmatized and under-researched. This study examined neurophysiological correlates of CSA in men using diffusion tensor imaging (DTI).

Major depressive disorder (MDD) heterogeneity is frequently overlooked in current diagnostic approaches, despite evidence that certain subtypes, particularly MDD with psychotic symptoms (MDDwP), are associated with poorer prognoses. Eye movement assessment has demonstrated promise as a potential biomarker for psychiatric disorders; however, research into eye movement patterns in MDD with and without psychotic features is scarce. This study aimed to investigate the potential value of eye movement as a biomarker for MDD.

Parkinson's disease (PD) is a progressive neurodegenerative disorder that presents diagnostic challenges, particularly in its early stages. This study proposes a multimodal approach to PD classification that integrates neurological imaging, motor symptom analysis, and non-motor clinical features. Dopamine depletion, a core biomarker of PD, is assessed using PET imaging, where active brain regions are quantified through color segmentation and image processing. A reduction in the active area correlates with disease progression. Tremor detection is performed using the Hough Transform algorithm applied to line-drawing tests, effectively identifying motor irregularities. Non-motor features are analyzed using a publicly available dataset, and the XGBoost algorithm achieves a classification accuracy exceeding 95.42%. The combined approach demonstrates high potential for early, accurate, and interpretable PD diagnosis.

Initially designed to assess executive control deficits for individuals meeting criteria for attention-deficit/hyperactivity disorder (ADHD), the Brown Attention-Deficit Disorder Scale (BADDS) is now frequently used to assess such deficits more broadly. However, no existing studies have investigated whether individuals scoring high on the BADDS are characterized by impairments within higher-order brain regions associated with executive control. Here, we investigated this association among incarcerated adolescents (205 boys and 35 girls). We incorporated the use of source-based morphometry (SBM), a data-driven, multivariate approach to identify large-scale structural brain networks. In separate analyses performed with incarcerated boys and girls, we observed that higher BADDS total scores were related to reduced loading coefficients in SBM components comprised of brain regions associated with executive control (e.g., superior/middle frontal gyrus, superior/inferior parietal lobule, and middle temporal gyrus). These structural impairments suggest participants scoring high on the BADDS are characterized by executive control deficits, including domains such as self-regulation, working memory, and sustained attention. Our results add to a growing body of literature suggesting that the BADDS serves as a reliable measure of executive control deficits. Further, our results support the use of the BADDS in samples beyond individuals strictly meeting criteria for ADHD.