Publications by authors named "X Caseras"
Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model.
View Article and Find Full Text PDFCortical and Subcortical Brain Alterations in Specific Phobia and Its Animal and Blood-Injection-Injury Subtypes: A Mega-Analysis From the ENIGMA Anxiety Working Group.
Am J Psychiatry
August 2024
Article Synopsis
- - The ENIGMA Anxiety Working Group studied brain structural differences between individuals with specific phobias and healthy participants, focusing on subtypes of phobias like animal and blood-injection-injury (BII) while examining how these differences relate to symptom severity and age.
- - A total of 1,452 participants with phobias and 2,991 healthy subjects were analyzed, revealing that those with phobias exhibited smaller subcortical volumes and varying cortical thickness, especially noted in adults rather than youths.
- - The results indicate that brain alterations in specific phobias are more significant than in other anxiety disorders, revealing distinct neural underpinnings linked to fear processing across different phobia types, highlighting a
Recent research has highlighted the role of complement genes in shaping the microstructure of the brain during early development, and in contributing to common allele risk for Schizophrenia. We hypothesised that common risk variants for schizophrenia within complement genes will associate with structural changes in white matter microstructure within tracts innervating the frontal lobe. Results showed that risk alleles within the complement gene set, but also intergenic alleles, significantly predict axonal density in white matter tracts connecting frontal cortex with parietal, temporal and occipital cortices.
View Article and Find Full Text PDFArticle Synopsis
- The study evaluates different normative models for analyzing brain structure data to find the most effective approach for research and clinical applications.
- They tested eight algorithms using data from over 37,000 healthy individuals across multiple regions and identified multivariate fractional polynomial regression (MFPR) as the best-performing model.
- The MFPR proved to be highly accurate across various age groups and maintains stability over time, offering valuable insights for understanding brain development and assisting in future research.
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.
View Article and Find Full Text PDF