Results 21 to 30 of about 249,333 (304)

How to Interpret Resting-State fMRI: Ask Your Participants

Journal of Neuroscience, 2021
Resting-state fMRI (rsfMRI) reveals brain dynamics in a task-unconstrained environment as subjects let their minds wander freely. Consequently, resting subjects navigate a rich space of cognitive and perceptual states (i.e., ongoing experience). How this
J. Gonzalez-Castillo, J. Kam, Colin W. Hoy, P. Bandettini   +3 more
semanticscholar   +1 more source

Resting State fMRI Reveals Diminished Functional Connectivity in a Mouse Model of Amyloidosis [PDF]

, 2013
Introduction: Functional connectivity (FC) studies have gained immense popularity in the evaluation of several neurological disorders, such as Alzheimer’s disease (AD). AD is a complex disorder, characterised by several pathological features. The problem
Rafael Delgado Y Palacios, Christian Bigot, Van Der Linden, Anne-Marie, Bigot, Christian, Van der Linden, Annemie, Rafael Delgado y Palacios (498616), Verhoye, Marleen, Disha Shah, Annemie Van der Linden, Christian Bigot (498617), Dany V D'Souza, Shah, Disha, Disha Shah (498613), Annemie Van der Linden (2227165), Elisabeth Jonckers, D'Souza, Dany V., Greetje Vanhoutte, Jonckers, Elisabeth, Jelle Praet (498614), Delgado y Palacios, Rafael, Greetje Vanhoutte (498615), Marleen Verhoye, Praet, Jelle, Marleen Verhoye (95635), Vanhoutte, Greetje, Jelle Praet, Elisabeth Jonckers (353117), Dany V. D’Souza (498618)   +27 more
core   +1 more source

Searching multiregression dynamic models of resting-state fMRI networks using integer programming [PDF]

, 2015
A Multiregression Dynamic Model (MDM) is a class of multivariate time series that represents various dynamic causal processes in a graphical way. One of the advantages of this class is that, in contrast to many other Dynamic Bayesian Networks, the ...
Smith, Jim, Cussens, James, Duff, Eugene P., Nichols, Thomas, Makin, Tamar, Costa, Lilia, Smith, J. Q., Duff, Eugene, Makin, Tamar R., Nichols, Thomas E.   +9 more
core   +1 more source

Resting-state fMRI in the Human Connectome Project

NeuroImage, 2013
Resting-state functional magnetic resonance imaging (rfMRI) allows one to study functional connectivity in the brain by acquiring fMRI data while subjects lie inactive in the MRI scanner, and taking advantage of the fact that functionally related brain ...
Stephen M. Smith, C. Beckmann, J. Andersson, E. Auerbach, J. Bijsterbosch, G. Douaud, E. Duff, D. Feinberg, L. Griffanti, M. Harms, M. Kelly, Timothy O. Laumann, K. Miller, S. Moeller, S. Petersen, Jonathan D. Power, G. Khorshidi, A. Snyder, An T. Vu, M. Woolrich, Junqian Xu, E. Yacoub, K. Uğurbil, D. C. Essen, M. Glasser   +24 more
semanticscholar   +1 more source

Arousal Contributions to Resting-State fMRI Connectivity and Dynamics

Frontiers in Neuroscience, 2019
Resting-state functional magnetic resonance imaging (rsfMRI) is being widely used for charting brain connectivity and dynamics in healthy and diseased brains. However, the resting state paradigm allows an unconstrained fluctuation of brain arousal, which
Yameng Gu, Feng Han, Xiao Liu, Xiao Liu
doaj   +1 more source

Advances in resting state fMRI acquisitions for functional connectomics

NeuroImage, 2021
Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task ...
L. Raimondo, ĺcaro A.F. Oliveira, Jurjen Heij, N. Priovoulos, P. Kundu, R. Leoni, W. Zwaag   +6 more
semanticscholar   +1 more source

Recent progress and outstanding issues in motion correction in resting state fMRI

NeuroImage, 2014
The purpose of this review is to communicate and synthesize recent findings related to motion artifact in resting state fMRI. In 2011, three groups reported that small head movements produced spurious but structured noise in brain scans, causing distance-
Jonathan D. Power, B. Schlaggar, S. Petersen   +2 more
semanticscholar   +1 more source

3T vs. 7T fMRI: capturing early human memory consolidation after motor task utilizing the observed higher functional specificity of 7T

Frontiers in Neuroscience, 2023
ObjectiveFunctional magnetic resonance imaging (fMRI) visualizes brain structures at increasingly higher resolution and better signal-to-noise ratio (SNR) as field strength increases.
Silke Kreitz, Angelika Mennecke, Laura Konerth, Julie Rösch, Armin M. Nagel, Frederik B. Laun, Michael Uder, Arnd Dörfler, Andreas Hess, Andreas Hess   +9 more
doaj   +1 more source

Pattern classification of large-scale functional brain networks : identification of informative neuroimaging markers for epilepsy [PDF]

, 2012
The accurate prediction of general neuropsychiatric disorders, on an individual basis, using resting-state functional magnetic resonance imaging (fMRI) is a challenging task of great clinical significance.
GuangMing Lu, ZhengGe Wang, GuangMing Lu (164664), Cheng, Wei, Jie Zhang (64655), Zhang, ZhiQiang, Jie Zhang, Wang, ZhengGe, Jianfeng Feng (48703), ZhiQiang Zhang, Wei Cheng (52808), ZhengGe Wang (164658), Feng, Jianfeng, Wei Cheng, Jianfeng Feng, WenLian Lu (164662), WenLian Lu, ZhiQiang Zhang (164660), Zhang, Jie, Lu, Wenlian, Lu, GuangMing   +20 more
core   +1 more source

Independent component analysis of interictal fMRI in focal epilepsy: comparison with general linear model-based EEG-correlated fMRI [PDF]

, 2007
The general linear model (GLM) has been used to analyze simultaneous EEG–fMRI to reveal BOLD changes linked to interictal epileptic discharges (IED) identified on scalp EEG. This approach is ineffective when IED are not evident in the EEG.
Lemieux, L., de Martino, F.; id_orcid, De Martino, F., Formisano, E., Duncan, J.S., Laufs, H., Rodionov, R., Carmichael, D.W., Walker, M., Formisano, E.; id_orcid   +9 more
core   +1 more source