Publications by authors named "Tomyshev A"

Article Synopsis
  • The study investigates the relationship between different types of delusions in schizophrenia spectrum disorders and corresponding brain changes using a systematic review approach, following PRISMA guidelines.
  • Researchers analyzed 1,752 records and included 95 relevant studies that utilized imaging techniques like fMRI and sMRI to identify structural and functional brain alterations linked to delusions.
  • Key findings indicate that both specific and nonspecific delusions, particularly paranoia, are associated with changes in brain regions including the superior temporal cortex, anterior cingulate/medial prefrontal cortex, and insula.
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A large body of research has shown that schizophrenia patients demonstrate increased brain structural aging. Although this process may be coupled with aberrant changes in intrinsic functional architecture of the brain, they remain understudied. We hypothesized that there are brain regions whose whole-brain functional connectivity at rest is differently associated with brain structural aging in schizophrenia patients compared to healthy controls.

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Article Synopsis
  • * This large-scale study analyzed MRI scans from over 2,000 schizophrenia patients and 2,800 healthy controls to assess brain volume and microstructural integrity, using advanced modeling techniques.
  • * Results showed that aggressive behavior was significantly associated with reduced cortical and white matter volumes, particularly in key brain areas, suggesting a direct neurological link to aggression in schizophrenia patients.
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Article Synopsis
  • Schizophrenia is characterized by significant changes in brain structure, but it's not clear if these changes relate to the brain's network organization.
  • Researchers analyzed MRI scans from nearly 2,500 people with schizophrenia alongside healthy controls to see how structural changes connect to brain networks.
  • The study found that certain regions in the brain that are crucial for connectivity are more affected in schizophrenia, indicating a link between brain network vulnerability and the disease's impact, with some similarities to bipolar disorder but not major depressive disorder.
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Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK).

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We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates.

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Importance: The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in individuals at psychosis risk may be nested within the range observed in healthy individuals.

Objective: To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder.

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We analyzed the relationships between morphometric characteristics of brain gray matter and schizotypy. Mentally healthy subjects (n=164, age 18-35 years) completed Russian version of SPQ-74 test and underwent high-field 3T MRI. Cortical thickness in the right frontal pole (determined with FreeSurfer 6.

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Objective: To establish the structural features of the brain (cortical and subcortical) in depressive patients at clinical risk for psychosis.

Material And Methods: Nineteen right-handed male patients with youth depression, who were assessed for high risk of psychotic manifestation, and 20 healthy controls underwent MRI and clinical examination. T1-weighted images were processed in FreeSurfer 7.

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Article Synopsis
  • The study looked at how the brain's left and right sides might differ in people with schizophrenia compared to those without it, using brain scans from over 5,000 patients and 6,000 control subjects.
  • Researchers found that people with schizophrenia had slightly thinner areas in the left side of their brains, especially in certain regions, compared to those without the disorder.
  • The differences in brain structure might be linked to how schizophrenia affects brain functions, like language, but more research is needed to understand why they happen.
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Importance: The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in the majority of individuals at psychosis risk may be nested within the range observed in healthy individuals.

Objective: To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high-risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder.

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Article Synopsis
  • Schizophrenia can make the brain age faster, leading to more cognitive problems and health issues.
  • A study looked at brain scans of 2,803 people with schizophrenia and 2,598 healthy people to see how much older their brains looked compared to their actual ages.
  • The results showed that people with schizophrenia had brains that looked about 3.55 years older than they should be, but this wasn’t linked to how long they had the illness or how severe their symptoms were.
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Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis.

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Article Synopsis
  • The study examines the differences in the morphology of the human cerebral cortex across various psychiatric disorders, suggesting that early growth patterns in the cortex may influence later variations in surface area and mental health outcomes.
  • Using data from over 27,000 MRI scans, researchers identified significant differences in cortical area among individuals with conditions like ADHD, schizophrenia, and major depression, particularly in association cortices linked to cognitive processing.
  • The findings indicate a correlation between these structural differences and prenatal gene expression related to cell types important for brain development, highlighting how prenatal factors may play a crucial role in the risk of developing mental illnesses.
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Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders.

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We analyzed morphometric MRI parameters indirectly attesting to structural changes in the supragranular layer in 33 non-converted individuals at clinical high risk for endogenous psychosis (follow-up period of 6.7±0.6 years) and in 34 sex- and age-matched healthy controls.

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Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants.

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Article Synopsis
  • - The ENIGMA initiative focuses on identifying neurobiological markers that indicate the risk of developing psychosis, utilizing the largest neuroimaging sample of individuals classified as clinically high risk (CHR) so far.
  • - A study analyzed baseline MRI data from 3169 participants across 31 international sites, comparing structural brain differences between CHR individuals and healthy controls, as well as between those who later developed psychosis (CHR-PS+) and those who did not (CHR-PS-).
  • - Results showed that CHR individuals had significantly lower cortical thickness in certain brain regions compared to healthy controls, indicating potential neurobiological changes linked to the progression to psychosis.
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Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness.

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Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry.

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For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females).

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The present study analyzed diffusion characteristics of white matter tracts and grey matter anatomy in 48 mentally healthy participants, including first-degree relatives of patients with schizophrenia (N=13) and affective spectrum disorders (N=13). The subgroup with familial risk of schizophrenia displayed abnormalities in the structural connectivity and increased cortical thickness in the superior frontal gyrus. No differences in the analyzed characteristics were revealed in the subgroup with familial risk for affective disorders.

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Article Synopsis
  • The ENIGMA Consortium aims to enhance neuroimaging studies by combining data from various institutions, tackling the issue of small sample sizes but facing challenges due to diverse scanning devices.
  • This study tested the effectiveness of the ComBat batch adjustment method to reduce site-related differences and improve statistical outcomes in comparing brain structure between individuals with schizophrenia and healthy controls.
  • Results showed that using ComBat significantly boosted statistical significance and power in analyses, making it a recommended tool for ENIGMA and other multi-site neuroimaging projects, with user-friendly R functions available for implementation.
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Objective: Goldberg, the author of the "novelty-routinization" framework, suggested a new pair of cognitive styles for agent-centered decision-making (DM), context-dependency/independency (CD/CI), quantified by the Cognitive Bias Task (CBT) and supposedly reflecting functional brain hemispheric specialization. To date, there are only three lesion and activation neuroimaging studies on the CBT with the largest sample of 12 participants. The present study is the first to analyze whole-brain functional connectivity (FC) of the dorsolateral prefrontal cortex (DLPFC), involved in contextual agent-centered DM.

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Aim: To determine neuroanatomical peculiarities of grey matter in some regions of the prefrontal cortex and several subcortical structures in patients with juvenile shift like schizophrenia (F20 ICD-10).

Material And Methods: Forty-three young male patients and 54 mentally healthy men without family history of mental diseases underwent structural MRI with T1 high resolution images.

Results: As compared to mentally healthy subjects, there was a decrease of grey matter thickness in all tested regions of the prefrontal cortex in patients.

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