Match!

Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.

Published on Jul 1, 2017in NeuroImage5.812
· DOI :10.1016/j.neuroimage.2017.03.020
Rastko Ciric12
Estimated H-index: 12
(UPenn: University of Pennsylvania),
Daniel H. Wolf39
Estimated H-index: 39
(UPenn: University of Pennsylvania)
+ 11 AuthorsTheodore D. Satterthwaite44
Estimated H-index: 44
(UPenn: University of Pennsylvania)
Abstract
Abstract Since initial reports regarding the impact of motion artifact on measures of functional connectivity, there has been a proliferation of participant-level confound regression methods to limit its impact. However, many of the most commonly used techniques have not been systematically evaluated using a broad range of outcome measures. Here, we provide a systematic evaluation of 14 participant-level confound regression methods in 393 youths. Specifically, we compare methods according to four benchmarks, including the residual relationship between motion and connectivity, distance-dependent effects of motion on connectivity, network identifiability, and additional degrees of freedom lost in confound regression. Our results delineate two clear trade-offs among methods. First, methods that include global signal regression minimize the relationship between connectivity and motion, but result in distance-dependent artifact. In contrast, censoring methods mitigate both motion artifact and distance-dependence, but use additional degrees of freedom. Importantly, less effective de-noising methods are also unable to identify modular network structure in the connectome. Taken together, these results emphasize the heterogeneous efficacy of existing methods, and suggest that different confound regression strategies may be appropriate in the context of specific scientific goals.
  • References (83)
  • Citations (222)
📖 Papers frequently viewed together
1,048 Citations
3,381 Citations
20025.81NeuroImage
5,861 Citations
78% of Scinapse members use related papers. After signing in, all features are FREE.
References83
Newest
#1Kevin Murphy (Cardiff University)H-Index: 37
#2Michael D. Fox (Harvard University)H-Index: 38
The number of resting state functional connectivity MRI studies continues to expand at a rapid rate along with the options for data processing. Of the processing options, few have generated as much controversy as global signal regression and the subsequent observation of negative correlations (anti-correlations). This debate has motivated new processing strategies and advancement in the field, but has also generated significant confusion and contradictory guidelines. In this article, we work tow...
221 CitationsSource
#1Jonathan D. Power (NIH: National Institutes of Health)H-Index: 29
#2Mark Plitt (NIH: National Institutes of Health)H-Index: 8
Last. Alex Martin (NIH: National Institutes of Health)H-Index: 111
view all 4 authors...
Abstract Whole-brain fMRI signals are a subject of intense interest: variance in the global fMRI signal (the spatial mean of all signals in the brain) indexes subject arousal, and psychiatric conditions such as schizophrenia and autism have been characterized by differences in the global fMRI signal. Further, vigorous debates exist on whether global signals ought to be removed from fMRI data. However, surprisingly little research has focused on the empirical properties of whole-brain fMRI signal...
171 CitationsSource
#1Remi Patriat (UW: University of Wisconsin-Madison)H-Index: 9
#2Richard C. Reynolds (NIH: National Institutes of Health)H-Index: 17
Last. Rasmus M. Birn (UW: University of Wisconsin-Madison)H-Index: 17
view all 3 authors...
Abstract Head motion is a significant source of noise in the estimation of functional connectivity from resting-state functional MRI (rs-fMRI). Current strategies to reduce this noise include image realignment, censoring time points corrupted by motion, and including motion realignment parameters and their derivatives as additional nuisance regressors in the general linear model. However, this nuisance regression approach assumes that the motion-induced signal changes are linearly related to the...
12 CitationsSource
#1C BurgessGregoryH-Index: 1
#2KandalaSridharH-Index: 1
Last. M BarchDeannaH-Index: 1
view all 9 authors...
Abstract Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was furthe...
84 CitationsSource
#1Zahra Faraji-Dana (U of T: University of Toronto)H-Index: 2
#2Fred Tam (Sunnybrook Health Sciences Centre)H-Index: 13
Last. Simon J. Graham (U of T: University of Toronto)H-Index: 43
view all 4 authors...
Abstract Prospective motion correction is a promising candidate solution to suppress the effects of head motion during fMRI, ideally allowing the imaging plane to remain fixed with respect to the moving head. Residual signal artifacts may remain, however, because head motion in relation to a fixed multi-channel receiver coil (with non-uniform sensitivity maps) can potentially introduce unwanted signal variations comparable to the weak fMRI BOLD signal (~1%–4% at 1.5–3.0 T). The present work aime...
14 CitationsSource
#1Timothy O. Laumann (WashU: Washington University in St. Louis)H-Index: 23
#2Abraham Z. Snyder (WashU: Washington University in St. Louis)H-Index: 105
Last. Steven E. PetersenH-Index: 97
view all 16 authors...
197 CitationsSource
#1Evan M. GordonH-Index: 22
#2Timothy O. LaumannH-Index: 23
Last. Steven E. PetersenH-Index: 97
view all 6 authors...
The cortical surface is organized into a large number of cortical areas; however, these areas have not been comprehensively mapped in the human. Abrupt transitions in resting-state functional connectivity (RSFC) patterns can noninvasively identify locations of putative borders between cortical areas (RSFC-boundary mapping; Cohen et al. 2008). Here we describe a technique for using RSFC-boundary maps to define parcels that represent putative cortical areas. These parcels had highly homogenous RSF...
382 CitationsSource
#1Theodore D. Satterthwaite (UPenn: University of Pennsylvania)H-Index: 44
#2John J. Connolly (Children's Hospital of Philadelphia)H-Index: 18
Last. Raquel E. Gur (UPenn: University of Pennsylvania)H-Index: 110
view all 17 authors...
Abstract The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale study of child development that combines neuroimaging, diverse clinical and cognitive phenotypes, and genomics. Data from this rich resource is now publicly available through the Database of Genotypes and Phenotypes (dbGaP). Here we focus on the data from the PNC that is available through dbGaP and describe how users can access this data, which is evolving to be a significant resource for the broader neuroscience communit...
97 CitationsSource
#1Timothy O. Laumann (WashU: Washington University in St. Louis)H-Index: 23
#2Evan M. Gordon (WashU: Washington University in St. Louis)H-Index: 22
Last. Steven E. PetersenH-Index: 97
view all 14 authors...
Summary Resting state functional MRI (fMRI) has enabled description of group-level functional brain organization at multiple spatial scales. However, cross-subject averaging may obscure patterns of brain organization specific to each individual. Here, we characterized the brain organization of a single individual repeatedly measured over more than a year. We report a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject-specific task activation...
308 CitationsSource
#1Molly G. Bright (Cardiff University)H-Index: 11
#2Kevin Murphy (Cardiff University)H-Index: 37
Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by ...
80 CitationsSource
Cited By222
Newest
#1Juan Helen Zhou (NUS: National University of Singapore)H-Index: 5
#2Kwun Kei Ng (NUS: National University of Singapore)H-Index: 9
Last. Siwei Liu (NUS: National University of Singapore)H-Index: 5
view all 3 authors...
Neurodegenerative diseases target specific large-scale neuronal networks, leading to distinct behavioral and cognitive dysfunctions. In this chapter, we review recent advances in using network-sensitive resting-state functional magnetic resonance imaging (rsfMRI) to unveil the brain network degeneration underlying cognitive impairment in neurodegenerative diseases, particularly Alzheimer’s disease (AD) and frontotemporal dementia (FTD). We focus on the applications of rsfMRI-based functional con...
Source
#1Jonathan D. Power (Cornell University)H-Index: 29
This chapter introduces a neuroimaging approach that has become popular among scientists over the last decade and that now is starting to attain clinical uses. The technique is called resting-state functional connectivity (RSFC), and it typically utilizes functional magnetic resonance imaging (fMRI) scans collected from subjects at rest (i.e., doing nothing) in the scanner. This chapter covers how the data are collected, processed, and turned into measures of brain organization. Some preliminary...
Source
#1Alysha Gilmore (University of Pittsburgh)H-Index: 1
#2Nicholas J Buser (University of Pittsburgh)H-Index: 1
Last. Jamie L. Hanson (University of Pittsburgh)H-Index: 16
view all 3 authors...
Subject motion can introduce noise into neuroimaging data and result in biased estimations of brain structure. In-scanner motion can compromise data quality in a number of ways and varies widely across developmental and clinical populations. However, quantification of structural image quality is often limited to proxy and indirect measures gathered from functional scans; this may be missing true differences related to these potential artifacts. In this study, we take advantage of novel informati...
Source
#1Binke YuanH-Index: 1
#2Nan Zhang (Fudan University)H-Index: 2
Last. Jinsong Wu (Fudan University)H-Index: 17
view all 6 authors...
Abstract Language processing relies on both a functionally specialized language network and a domain-general cognitive control network. Yet, how the two networks reorganize after damage resulting from diffuse and progressive glioma remains largely unknown. To address this issue, 130 patients with left cerebral gliomas, including 77 patients with low-grade glioma (LGG, WHO grade Ⅰ/II), 53 patients with high-grade glioma (HGG, WHO grade III/IV) and 38 healthy controls (HC) were adopted. The change...
Source
#2Ursula A TooleyH-Index: 1
Last. Danielle S. BassettH-Index: 52
view all 5 authors...
Functional connectivity (FC) networks are typically inferred from resting-state fMRI data using the Pearson correlation between BOLD time series from pairs of brain regions. However, alternate methods of estimating functional connectivity have not been systematically tested for their sensitivity or robustness to head motion artifact. Here, we evaluate the sensitivity of six different functional connectivity measures to motion artifact using resting-state data from the Human Connectome Project. W...
Source
#1Alexander L. Cohen (Boston Children's Hospital)H-Index: 18
#2Michael D. Fox (Harvard University)H-Index: 38
Source
#1Nicholas J. Petrosino (Brown University)H-Index: 1
#2Mascha van 't Wout-Frank (Brown University)H-Index: 3
Last. Noah S. Philip (Brown University)H-Index: 21
view all 7 authors...
Theta burst transcranial magnetic stimulation (TBS) is a potential new treatment for post-traumatic stress disorder (PTSD). We previously reported active intermittent TBS (iTBS) was associated with superior clinical outcomes for up to 1-month, in a sample of fifty veterans with PTSD, using a crossover design. In that study, participants randomized to the active group received a total of 4-weeks of active iTBS, or 2-weeks if randomized to sham. Results were superior with greater exposure to activ...
1 CitationsSource
#1Maria Carbó-Carreté (University of Barcelona)
#2Cristina Cañete-Massé (University of Barcelona)
Last. Joan Guàrdia-OlmosH-Index: 15
view all 4 authors...
Background In the last few years, many investigations have focused on the study of brain activity in general and pathological population using non-invasive techniques such as EEG, PET, fMRI or MRI. However, the study of the use of non-invasive registers of brain signal for evaluating the cognitive activity of people with Down Syndrome (DS) has not been sufficiently addressed. The objective is describe the state of the art on the use of brain signal recorded with functional magnetic resonance ima...
Source
#1Ayumu YamashitaH-Index: 3
#2Yuki SakaiH-Index: 10
Last. Naho Ichikawa (Hiroshima University)H-Index: 4
view all 23 authors...
Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable major depressive disorder (MDD) brain network markers which would distinguish patients from heal...
Source
#1Junjiao Feng (McGovern Institute for Brain Research)
#2Chunhui Chen (McGovern Institute for Brain Research)H-Index: 17
Last. Jintao Sheng (McGovern Institute for Brain Research)
view all 15 authors...
Resting-state functional connectivity profiles have been increasingly shown to be important endophenotypes that are tightly linked to human cognitive functions and psychiatric diseases, yet the genetic architecture of this multidimensional trait is barely understood. Using a unique sample of 1,704 unrelated, young and healthy Chinese Han individuals, we revealed a significant heritability of functional connectivity patterns in the whole brain and several subnetworks. We further proposed a partit...
Source