Simon Červenka

This study compares thalamic nucleus volumes across multiple psychiatric and neurological disorders using MRI, finding significant volume reductions in specific regions associated with different conditions.

The paper benchmarks and optimizes a normative modeling framework for brain morphometry across the lifespan using MFPR, showing excellent accuracy and stability.

The paper analyzes cortical thickness trajectories in 17,075 individuals to show peak thickness in childhood, steep decline in early adulthood, and slower decline later, with notable exceptions and significant inter-individual variability.

The paper assesses the correlation between [11C]raclopride and [11C]FLB 457 binding potential in extrastriatal brain regions and finds weak to moderate correlations, suggesting caution in using [11C]raclopride for D2-R quantification.

The paper identifies genetic loci associated with brainstem volumes and finds genetic overlaps with psychiatric and neurological disorders.

This study validates kinfitr, an open-source R tool for PET kinetic modelling, showing high agreement with the commercial PMOD software in binding estimates and test-retest reliability.

This study uses diffusion tensor imaging and machine learning to predict brain age in schizophrenia and bipolar disorder patients, finding age overestimation in both groups compared to controls.

The study investigates the association between dopamine D1 receptor availability and delusional ideation in healthy controls using PET and questionnaire data, finding little to no linear association.

This study analyzes subcortical volume changes across the lifespan using MRI data from 18,605 individuals, finding age-related declines in some structures and increases in others.

The paper estimates brain age gaps using MRI and machine learning in individuals with and without brain disorders, finding heritability and genetic overlap with common disorders.

This study evaluates the validity and reliability of [11C]raclopride PET for quantifying D2/3R binding outside the striatum, finding it unreliable in extrastriatal regions.

This study evaluates test-retest reliability and convergent validity of (R)-[11C]PK11195 binding measures without arterial input function, finding poor reliability and weak correlations for most methods.

This study evaluates the accuracy and reliability of specific binding estimates for [11C]PBR28 using the SIME method, showing good precision and reliability for VS but variability in BPND.

This study uses Bayesian hypothesis testing to replicate a previous finding of a link between 5-HT1A receptor binding and self-transcendence traits, finding no significant association.

The paper develops deep learning models to assess the quality of subcortical brain shape models from MRI, reducing human rater time by 46-70%.

This paper investigates brain structural heterogeneity in schizophrenia and finds that polygenic risk is associated with thinner fronto-temporal cortices and smaller hippocampal subfields, but not with increased variability.

This study attempts to replicate previous findings linking dopamine D1 receptor availability to social behavior using PET and personality scales but finds no significant correlations.

This work uses machine learning to automate quality control of 3D brain shape models, reducing human workload by 30-70% across multiple datasets and diseases.