INTRODUCTION: The present study aimed to investigate sex differences in response to repetitive transcranial magnetic stimulation (rTMS) in Major Depressive Disorder (MDD) patients. Identifying the factors that mediate treatment response to rTMS in MD...
BACKGROUND: Fine operation has been an eternal topic in neurosurgery. There were many problems in functional neurosurgery field with high precision requirements. Our study aims to explore the operability, accuracy and postoperative effect of robot-as...
OBJECTIVE: Autism spectrum disorder (ASD) is a neurodevelopmental condition with a heterogeneous phenotype. The role of biomarkers in ASD diagnosis has been highlighted; cortical thickness has proved to be involved in the etiopathogenesis of ASD core...
INTRODUCTION: The basic paradigm of rehabilitation is based on the brain plasticity, and for promoting it, test-retest reliability (TRR) of brain activation in which certain area of the brain is repeatedly activated is required. In this study, we inv...
BACKGROUND: Stroke survivors often experience upper-limb motor deficits and achieve limited motor recovery within six months after the onset of stroke. We aimed to systematically review the effects of robot-assisted therapy (RT) in comparison to usua...
INTRODUCTION: Prediction of Alzheimer's disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end, we combine a predictive multi-task m...
INTRODUCTION: Scalp-recorded electrophysiological responses to complex, periodic auditory signals reflect phase-locked activity from neural ensembles within the auditory system. These responses, referred to as frequency-following responses (FFRs), ha...
BACKGROUND: Generalized anxiety disorder (GAD) is difficult to recognize and hard to separate from major depression (MD) in clinical settings. Biomarkers might support diagnostic decisions. This study used machine learning on multimodal biobehavioral...
INTRODUCTION: In recent years, machine-learning techniques have gained growing popularity in medical image analysis. Temporal brain-state classification is one of the major applications of machine-learning techniques in functional magnetic resonance ...
BACKGROUND: We have explored the potential prefrontal hemodynamic biomarkers to characterize subjects with Traumatic Brain Injury (TBI) by employing the multivariate machine learning approach and introducing a novel task-related hemodynamic response ...