Brain Network Fingerprints Under High Working Memory Load Distinguish Multiple Sclerosis Patients
A graph theory and machine learning analysis of task-based fMRI distinguished multiple sclerosis patients from healthy controls with 95.5 percent ...
A graph theory and machine learning analysis of task-based fMRI distinguished multiple sclerosis patients from healthy controls with 95.5 percent ...
A combined structural and functional MRI study of 62 Parkinson's disease patients found cortical thinning in frontal and motor regions ...
A secondary analysis of a randomized trial found that progressive aerobic training produced a larger increase in default mode network ...
Population cohorts combining genetics with multi-organ imaging reveal that brain disorders share a distributed genetic architecture with the heart, retina ...
Researchers used 7-Tesla MRI and a deep learning model to predict Trail-Making Test performance with 0.795 accuracy across psychiatric patients ...
A leakage-controlled multimodal machine learning study of 251 adolescents shows task-evoked fMRI features during emotional response inhibition provide the strongest ...
A five-year Italian study found that early dopamine loss in the caudate nucleus on DAT-SPECT marks a parkinsonian phenotype with ...
A new coordinate-based network mapping study suggests that the scattered gray matter abnormalities reported in idiopathic generalized epilepsy converge most ...
A resting-state fMRI study of 231 participants finds that recurrent depression with suicidal ideation shows distinct impairments in large-scale brain ...
A novel texture similarity network analysis of brain scans has identified two reproducible schizophrenia subtypes with distinct molecular signatures.
© 2025 Scienmag - Science Magazine
© 2025 Scienmag - Science Magazine