Evaluation of multi-echo ICA denoising for task based fMRI studies: Block designs, rapid event-related designs, and cardiac-gated fMRI

Multi-echo fMRI, particularly the multi-echo independent component analysis (ME-ICA) algorithm, has previously proven useful for increasing the sensitivity and reducing false positives for functional MRI (fMRI) based resting state connectivity studies. Less is known about its efficacy for task-based...

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Vydané v:	NeuroImage (Orlando, Fla.) Ročník 141; s. 452 - 468
Hlavní autori:	Gonzalez-Castillo, Javier, Panwar, Puja, Buchanan, Laura C., Caballero-Gaudes, Cesar, Handwerker, Daniel A., Jangraw, David C., Zachariou, Valentinos, Inati, Souheil, Roopchansingh, Vinai, Derbyshire, John A., Bandettini, Peter A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Inc 01.11.2016 Elsevier Limited
Predmet:	Adult Algorithms Block design Brain - physiology Brain Mapping - methods Cardiac-Gated Imaging Techniques - methods Datasets Experiments Female Functional magnetic resonance imaging Heart Heart diseases Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Magnetic Resonance Imaging - methods Male ME-ICA Multi-echo fMRI Neural networks Noise Physiology Principal Component Analysis Principal components analysis Rapid event related Repetition Reproducibility of Results Sensitivity Sensitivity and Specificity Signal-To-Noise Ratio Task Performance and Analysis Time series Sensitivity Rapid event related Block design Multi-echo fMRI ME-ICA
ISSN:	1053-8119, 1095-9572
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