Publications by authors named "J L Frijling"
Background: Intrusive traumatic re-experiencing domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective.
Methods: Data were collected from 9 sites taking part in the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) PTSD Consortium ( 584) and included itemized PTSD symptom scores and resting-state functional connectivity (rsFC) data.
Article Synopsis
- The study explores the lesser-known role of the cerebellum in PTSD by analyzing cerebellar volume differences in a large sample of 4,215 adults, with 1,642 diagnosed with PTSD and 2,573 as healthy controls.
- Using advanced deep-learning techniques, researchers assessed the total cerebellum volume and 28 subregions, revealing significant reductions in both gray and white matter in individuals with PTSD, especially in specific posterior lobe and vermis areas.
- The results suggest that changes in cerebellar structure are linked to cognitive and emotional dysfunctions in PTSD, highlighting the cerebellum's importance beyond its traditional role in motor control.
Alexithymia, an inability to recognise one's emotions, has been associated with trauma-exposure and posttraumatic stress disorder (PTSD). Previous research suggests involvement of the oxytocin system, and socio-emotional neural processes. However, the paucity of neurobiological research on alexithymia, particularly in trauma-exposed populations, warrants further investigation.
View Article and Find Full Text PDFPosttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries.
View Article and Find Full Text PDFArticle Synopsis
- * Researchers utilized various MRI data types to identify brain features that can distinguish PTSD from controls, revealing that classification accuracy decreases significantly when using multi-site data compared to single-site studies.
- * The denoising variational autoencoder (DVAE) model showed improved generalization on new datasets, indicating its potential for better classification of PTSD, although overall performance still remained only slightly above chance levels.