Background: People with early-life experiences of deprivation are more likely to develop psychotic symptoms. While the mechanisms of this relationship are poorly understood, research suggests a role of cortical development.
Methods: In 6323 youth from the Adolescent Brain Cognitive Development study, we examined associations between total, material, interpersonal, cognitive and neighbourhood deprivation at age 9-11 years and psychotic-like experiences (PLEs) 2 years later. We then investigated whether associations were mediated by variation in cortical volume at baseline or rate of change from baseline to follow-up. Sex-specific effects were examined throughout.
Results: All deprivation measures were associated with greater PLEs. Most of these associations were partially mediated by variation in cortical structure in widespread regions, including lower baseline cortical volume in ventral visual and sensorimotor regions and particularly in females, steeper cortical volume decline in association areas.
Conclusions: Early-life deprivation may be associated with psychotic-like experiences via disruption to cortical structure. This phenomenon is common to several forms of deprivation and continues into early adolescence in certain regions.
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http://dx.doi.org/10.1111/jcpp.14150 | DOI Listing |
Eur J Appl Physiol
March 2025
Faculty of Sports Sciences, CETAPS EA 3832, University of Rouen, Rouen, France.
Purpose: The study investigated the changes in cardiovascular and cerebral hemodynamics elicited by the diving response during static (S) and dynamic (DYN) breath-holding (BH) in moderately trained recreational breath-hold divers (BHDs).
Methods: Nineteen BHDs (42.9 ± 7.
J Psychiatry Neurosci
March 2025
From the Department of Psychiatry, Dalhousie University, Halifax, N.S. (Selitser, Dietze, McWhinney, Hajek) and the Charles University, Third Faculty of Medicine, Prague, Czech Republic (Hajek).
Background: Cardiometabolic risk factors - including diabetes, hypertension, and obesity - have long been linked with adverse health outcomes such as strokes, but more subtle brain changes in regional brain volumes and cortical thickness associated with these risk factors are less understood. Computer models can now be used to estimate brain age based on structural magnetic resonance imaging data, and subtle brain changes related to cardiometabolic risk factors may manifest as an older-appearing brain in prediction models; thus, we sought to investigate the relationship between cardiometabolic risk factors and machine learning-predicted brain age.
Methods: We performed a systematic search of PubMed and Scopus.
Neuroscience
March 2025
The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou 510370, China; Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China. Electronic address:
Childhood trauma acts as an independent risk factor for mental disorders. This study utilized multi-modal MRI techniques to integrate cortical structural measurements and functional connectivity (FC) to identify neurobiological markers of trauma. This study recruited 215 participants, divided into a trauma group (n = 57) and a well-matched non-trauma group (n = 158) based on the childhood trauma questionnaire.
View Article and Find Full Text PDFMedicine (Baltimore)
March 2025
Rehabilitation Engineering Lab, Department of Health and Kinesiology, University of Illinois at Urbana-Champaign, Urbana, IL.
Background: Biomarkers play an important role in the diagnosis of early-stage Alzheimer disease (AD), with the hippocampal emerging as the most reliable indicator of AD pathology. Elucidation of the patient's left and right hippocampal volumes warrants further consideration. Therefore, caution should be exercised regarding the constraints inherent in the measurement method.
View Article and Find Full Text PDFBiomech Model Mechanobiol
March 2025
Division of Neuronic Engineering, KTH Royal Institute of Technology, 14152, Stockholm, Sweden.
Finite element (FE) models of the human head are important injury assessment tools but developing a high-quality, hexahedral-meshed FE head model without compromising geometric accuracy is a challenging task. Important brain features, such as the cortical folds and ventricles, were captured only in a handful of FE head models that were primarily developed from two meshing techniques, i.e.
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