Results 21 to 30 of about 72,622 (298)

A DCM for resting state fMRI

NeuroImage, 2014
This technical note introduces a dynamic causal model (DCM) for resting state fMRI time series based upon observed functional connectivity--as measured by the cross spectra among different brain regions. This DCM is based upon a deterministic model that generates predicted crossed spectra from a biophysically plausible model of coupled neuronal ...
Karl J. Friston, Joshua Kahan, Bharat B. Biswal, Adeel Razi   +3 more
openaire   +3 more sources

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

Large-scale DCMs for resting-state fMRI [PDF]

Network Neuroscience, 2017
This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity. This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI ...
Adeel Razi, Mohamed L. Seghier, Yuan Zhou, Peter McColgan, Peter Zeidman, Hae‐Jeong Park, Olaf Sporns, Geraint Rees, Karl J. Friston   +8 more
openaire   +5 more sources

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

Lag structure in resting-state fMRI

Journal of Neurophysiology, 2014
The discovery that spontaneous fluctuations in blood oxygen level-dependent (BOLD) signals contain information about the functional organization of the brain has caused a paradigm shift in neuroimaging. It is now well established that intrinsic brain activity is organized into spatially segregated resting-state networks (RSNs). Less is known regarding
A, Mitra, A Z, Snyder, C D, Hacker, M E, Raichle   +3 more
openaire   +3 more sources

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
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On nodes and modes in resting state fMRI

NeuroImage, 2014
ISSN:1095 ...
Karl J. Friston, Joshua Kahan, Adeel Razi, Klaas Enno Stephan, Olaf Sporns   +4 more
openaire   +5 more sources

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

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