OBJECTIVE
Obsessive-compulsive disorder (OCD) is a chronic condition in which impaired inhibitory control and excessive error monitoring may contribute to maintenance of obsessions and compulsions. This mega-analysis investigates neural activation during response inhibition and error processing using adult (OCD=563; co...
N. Džinalija, O. A. van den Heuvel, H. B. Simpson et al.· Biological Psychiatry· 0 citations
Alzheimer's disease (AD) affects an estimated 55 million people worldwide and is projected to nearly double by 2050, creating a need for scalable, non-invasive AI systems that can classify disease stage, support multimodal clinical reasoning, and interact in natural language. Most deep learning work on AD focuses o...
Sohail Haresh Gidwani, Tamoghna Chattopadhyay, S. Thomopoulos et al.· Frontiers in Computational N...· 0 citations
Brain-age prediction from resting-state fMRI provides a quantitative framework for characterizing age-related changes in spontaneous brain dynamics and for identifying functional signatures. Existing studies have linked fractal and multifractal scaling to age and examined the reliability of individual features. However...
Yu Chang, An-Zhe Cheng, Jia-Hao Chen et al.· 0 citations
Importance
Bulimia nervosa (BN) ranks second among eating disorders in both prevalence and disease burden, but its neurobiology is poorly understood. Progress has been limited by neuroimaging studies with inconsistent findings across small samples.
Objective
To identify reliable structural brain correlates of BN diag...
Laura A. Berner, Anusha Phadnis, M. Westwater et al.· JAMA psychiatry· 0 citations
TIER-MoE is introduced, a risk-guided subspace mixture-of-experts model that defines sample-specific modality reliability as the prediction loss its unimodal predictor is expected to incur, and demonstrates its superiority over state-of-the-art methods in predictive performance and probability calibration.
