Major Depressive Disorder (MDD) is a common mental disorder characterized by cognitive impairment, and its pathophysiology remains to be explored. In this study, we aimed to explore the efficacy of brain network topological properties (TPs) in identi...
INTRODUCTION: Major depressive disorder (MDD) is a common, relapse-prone psychiatric disorder with unknown pathogenesis. Previous studies on resting-state functional magnetic resonance imaging of MDD have mostly focused on the spontaneous activity of...
Positron emission tomography (PET) utilizes radiotracers like [F]fluorodeoxyglucose (FDG) to measure brain activity in health and disease. Performing behavioral tasks between the FDG injection and the PET scan allows the FDG signal to reflect task-re...
Cortex; a journal devoted to the study of the nervous system and behavior
Nov 8, 2024
Diagnosis of dyslexia often occurs in late schooling years, leading to academic and psychological challenges. Furthermore, diagnosis is time-consuming, costly, and reliant on arbitrary cutoffs. On the other hand, automated algorithms hold great poten...
Current neuroimaging studies frequently use complex machine learning models to classify human fMRI data, distinguishing healthy and disordered brains, often to validate new methods or enhance prediction accuracy. Yet, where prediction accuracy is a c...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Modeling functional brain networks (FBNs) for attention deficit hyperactivity disorder (ADHD) has sparked significant interest since the abnormal functional connectivity is discovered in certain functional magnetic resonance imaging (fMRI)-based brai...
PURPOSE: This study investigates the feasibility of using complex-valued neural networks (NNs) to estimate quantitative transmit magnetic RF field (B ) maps from multi-slice localizer scans with different slice orientations in the human head at 7T, a...
Previous studies have found alterations in the local regional homogeneity of brain activity in individuals diagnosed with major depressive disorder. However, many studies have failed to consider that even during resting states, brain activity is dyna...
Anhedonia is one of the core features of the negative symptoms of schizophrenia and can be extremely burdensome. Our study applied resting-state functional magnetic resonance imaging (fMRI)-based support vector regression (SVR) to predict anhedonia i...
IEEE journal of biomedical and health informatics
Sep 5, 2024
Learning-based methods offer performance leaps over traditional methods in classification analysis of high-dimensional functional MRI (fMRI) data. In this domain, deep-learning models that analyze functional connectivity (FC) features among brain reg...
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