Results 81 to 90 of about 271,169 (372)
Resting state fMRI: A personal history
NeuroImage, 2012 The goal of this review is to describe, from a personal perspective, the development and emergence of the resting state fMRI. In particular, various concepts derived from the resting state data are discussed in detail, including connectivity, amplitude of the fluctuations, analysis techniques, and use in clinical populations.
openaire +2 more sources
Multi‐Site Transfer Classification of Major Depressive Disorder: An fMRI Study in 3335 Subjects
Advanced Science, EarlyView.The study proposes graph convolution network with sparse pooling to learn the hierarchical features of brain graph for MDD classification. Experiment is done on multi‐site fMRI samples (3335 subjects, the largest functional dataset of MDD to date) and transfer learning is applied, achieving an average accuracy of 70.14%.
Jianpo Su +14 more
wiley +1 more source
NeuroImage: Clinical, 2019 Olfactory dysfunction is an early manifestation of Parkinson's disease (PD). The present study aimed to illustrate potential differences between PD patients and healthy controls in terms of neural activity and functional connectivity within the olfactory
Charalampos Georgiopoulos +6 more
doaj +1 more source
, 2018 We propose a matrix factorization technique that decomposes the resting state fMRI (rs-fMRI) correlation matrices for a patient population into a sparse set of representative subnetworks, as modeled by rank one outer products.
A Venkataraman +8 more
core +1 more source
Machine Learning for Neuroimaging with Scikit-Learn [PDF]
, 2013 Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g. multivariate analysis of activation images or resting-state time series.
Abraham, Alexandre +8 more
core +4 more sources
EEG Alpha Power Modulation of fMRI Resting-State Connectivity [PDF]
Brain Connectivity, 2012 In the past decade, the fast and transient coupling and uncoupling of functionally related brain regions into networks has received much attention in cognitive neuroscience. Empirical tools to study network coupling include functional magnetic resonance imaging (fMRI)-based functional and/or effective connectivity, and electroencephalography (EEG ...
Scheeringa, R +4 more
openaire +4 more sources
Ecologically‐Valid Emotion Signatures Enhance Mood Disorder Diagnostics
Advanced Science, EarlyView.This study identifies ecologically‐valid Divergent Emotional Functional Networks (DEFN), derived from dynamic functional connectivity during naturalistic movie watching. The DEFN reliably enhances diagnostic accuracy for mood disorders, including major depressive and bipolar disorders, demonstrating strong reproducibility across demographic factors and
Shuyue Xu +6 more
wiley +1 more source
Loss of resting-state posterior cingulate flexibility is associated with memory disturbance in left temporal lobe epilepsy. [PDF]
PLoS ONE, 2015 The association between cognition and resting-state fMRI (rs-fMRI) has been the focus of many recent studies, most of which use stationary connectivity.
Linda Douw +6 more
doaj +1 more source
The effects of hemodynamic lag on functional connectivity and behavior after stroke [PDF]
, 2015 Stroke disrupts the brain's vascular supply, not only within but also outside areas of infarction. We investigated temporal delays (lag) in resting state functional magnetic resonance imaging signals in 130 stroke patients scanned two weeks, three months
Corbetta, Maurizio +4 more
core +1 more source
Altered Topological Properties of Static/Dynamic Functional Networks and Cognitive Function After Radiotherapy for Nasopharyngeal Carcinoma Using Resting-State fMRI [PDF]
, 2021 Xi Leng +10 more
openalex +1 more source