Aberrant brain voxel‐wise resting state fMRI in patients with thyroid‐associated ophthalmopathy

2021 ◽  
Author(s):  
Wen Chen ◽  
Qian Wu ◽  
Lu Chen ◽  
Jiang Zhou ◽  
Huan‐Huan Chen ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Thyroid Associated Ophthalmopathy

Resting-state fMRI used for intraoperative neuronavigation in children

2013 ◽  
Vol 44 (S 01) ◽  
Author(s):  
C Dorfer ◽  
T Czech ◽  
G Kasprian ◽  
A Azizi ◽  
J Furtner ◽  
...  
Keyword(s):  
Resting State ◽  
Resting State Fmri

scholarly journals Development of the default-mode network during childhood and adolescence: A longitudinal resting-state fMRI study

NeuroImage ◽  
2021 ◽  
Vol 226 ◽  
pp. 117581
Author(s):  
Fengmei Fan ◽  
Xuhong Liao ◽  
Tianyuan Lei ◽  
Tengda Zhao ◽  
Mingrui Xia ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Resting State Fmri ◽  
Childhood And Adolescence ◽  
Default Mode ◽  
Fmri Study

A Critical, Event-Related Appraisal of Denoising in Resting-State fMRI Studies

2020 ◽  
Vol 30 (10) ◽  
pp. 5544-5559 ◽  
Author(s):  
Jonathan D Power ◽  
Charles J Lynch ◽  
Babatunde Adeyemo ◽  
Steven E Petersen
Keyword(s):  
Resting State ◽  
Resting State Fmri ◽  
Critical Event ◽  
Head Motion ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Decay Properties ◽  
Signal Decay ◽  
Biological Variables ◽  
Related Approach

Abstract This article advances two parallel lines of argument about resting-state functional magnetic resonance imaging (fMRI) signals, one empirical and one conceptual. The empirical line creates a four-part organization of the text: (1) head motion and respiration commonly cause distinct, major, unwanted influences (artifacts) in fMRI signals; (2) head motion and respiratory changes are, confoundingly, both related to psychological and clinical and biological variables of interest; (3) many fMRI denoising strategies fail to identify and remove one or the other kind of artifact; and (4) unremoved artifact, due to correlations of artifacts with variables of interest, renders studies susceptible to identifying variance of noninterest as variance of interest. Arising from these empirical observations is a conceptual argument: that an event-related approach to task-free scans, targeting common behaviors during scanning, enables fundamental distinctions among the kinds of signals present in the data, information which is vital to understanding the effects of denoising procedures. This event-related perspective permits statements like “Event X is associated with signals A, B, and C, each with particular spatial, temporal, and signal decay properties”. Denoising approaches can then be tailored, via performance in known events, to permit or suppress certain kinds of signals based on their desirability.

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