[HTML][HTML] Brain networks, dimensionality, and global signal averaging in resting-state fMRI: Hierarchical network structure results in low-dimensional spatiotemporal …

SJ Gotts, AW Gilmore, A Martin - NeuroImage, 2020 - Elsevier
One of the most controversial practices in resting-state fMRI functional connectivity studies is
whether or not to regress out the global average brain signal (GS) during artifact removal …

Resting-state fMRI confounds and cleanup

K Murphy, RM Birn, PA Bandettini - Neuroimage, 2013 - Elsevier
The goal of resting-state functional magnetic resonance imaging (fMRI) is to investigate the
brain's functional connections by using the temporal similarity between blood oxygenation …

The connectivity domain: Analyzing resting state fMRI data using feature-based data-driven and model-based methods

A Iraji, VD Calhoun, NM Wiseman, E Davoodi-Bojd… - Neuroimage, 2016 - Elsevier
Spontaneous fluctuations of resting state functional MRI (rsfMRI) have been widely used to
understand the macro-connectome of the human brain. However, these fluctuations are not …

The nuisance of nuisance regression: spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional …

MN Hallquist, K Hwang, B Luna - Neuroimage, 2013 - Elsevier
Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that
head motion during fMRI acquisition systematically influences connectivity estimates despite …

Correcting brain-wide correlation differences in resting-state FMRI

ZS Saad, RC Reynolds, HJ Jo, SJ Gotts, G Chen… - Brain …, 2013 - liebertpub.com
Brain function in “resting” state has been extensively studied with functional magnetic
resonance imaging (FMRI). However, drawing valid inferences, particularly for group …

[HTML][HTML] Identifying and removing widespread signal deflections from fMRI data: Rethinking the global signal regression problem

KM Aquino, BD Fulcher, L Parkes, K Sabaroedin… - Neuroimage, 2020 - Elsevier
One of the most controversial procedures in the analysis of resting-state functional magnetic
resonance imaging (rsfMRI) data is global signal regression (GSR): the removal, via linear …

Characterizing the modulation of resting-state fMRI metrics by baseline physiology

PPW Chu, AM Golestani, JB Kwinta, YB Khatamian… - Neuroimage, 2018 - Elsevier
The blood-oxygenation level dependent (BOLD) functional magnetic resonance imaging
(fMRI) signal is commonly used to assess functional connectivity across brain regions …

Enhanced subject‐specific resting‐state network detection and extraction with fast fMRI

B Akin, HL Lee, J Hennig, P LeVan - Human brain mapping, 2017 - Wiley Online Library
Resting‐state networks have become an important tool for the study of brain function. An
ultra‐fast imaging technique that allows to measure brain function, called Magnetic …

Time–frequency dynamics of resting-state brain connectivity measured with fMRI

C Chang, GH Glover - Neuroimage, 2010 - Elsevier
Most studies of resting-state functional connectivity using fMRI employ methods that assume
temporal stationarity, such as correlation and data-driven decompositions computed across …

Quantifying temporal correlations: A test–retest evaluation of functional connectivity in resting-state fMRI

M Fiecas, H Ombao, D Van Lunen, R Baumgartner… - NeuroImage, 2013 - Elsevier
There have been many interpretations of functional connectivity and proposed measures of
temporal correlations between BOLD signals across different brain areas. These …