The effect of scan length on the reliability of resting-state fMRI connectivity estimates.

doi:10.1016/J.NEUROIMAGE.2013.05.099

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The effect of scan length on the reliability of resting-state fMRI connectivity estimates.

Journal Article•DOI•

The effect of scan length on the reliability of resting-state fMRI connectivity estimates.

Rasmus M. Birn¹, Erin K. Molloy¹, Remi Patriat¹, Taurean Parker², Timothy B. Meier¹, Gregory R. Kirk¹, Veena A. Nair¹, M. Elizabeth Meyerand¹, Vivek Prabhakaran¹ - Show less +5 more•Institutions (2)

University of Wisconsin-Madison¹, University of Rochester²

01 Dec 2013-NeuroImage (Neuroimage)-Vol. 83, pp 550-558

TL;DR: Reliability and similarity of resting-state functional connectivity can be greatly improved by increasing the scan lengths, and that both the increase in the number of volumes as well as the length of time over which these volumes was acquired drove this increase in reliability.

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About: This article is published in NeuroImage.The article was published on 2013-12-01 and is currently open access. It has received 668 citations till now. The article focuses on the topics: Resting state fMRI & Reliability (statistics).

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Journal Article•DOI•

ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data

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Raimon H. R. Pruim¹, Maarten Mennes¹, Daan van Rooij², Alberto Llera¹, Jan K. Buitelaar¹, Christian F. Beckmann³ - Show less +2 more•Institutions (3)

Radboud University Nijmegen¹, University Medical Center Groningen², University of Oxford³

15 May 2015-NeuroImage

TL;DR: The results show that ICA-AROMA effectively reduces motion-induced signal variations in fMRI data, is applicable across datasets without requiring classifier re-training, and preserves the temporal characteristics of the f MRI data.

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1,214 citations

Journal Article•DOI•

Functional System and Areal Organization of a Highly Sampled Individual Human Brain.

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Timothy O. Laumann¹, Evan M. Gordon¹, Babatunde Adeyemo¹, Abraham Z. Snyder¹, Sung Jun Joo², Mei Yen Chen², Adrian W. Gilmore¹, Kathleen B. McDermott¹, Steven M. Nelson³, Nico U.F. Dosenbach¹, Bradley L. Schlaggar¹, Jeanette A. Mumford⁴, Russell A. Poldrack, Steven E. Petersen¹ - Show less +10 more•Institutions (4)

Washington University in St. Louis¹, University of Texas at Austin², University of Texas at Dallas³, University of Wisconsin-Madison⁴

05 Aug 2015-Neuron

TL;DR: The brain organization of a single individual repeatedly measured over more than a year is characterized and a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject- specific task activations is reported.

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763 citations

Cites background or result from "The effect of scan length on the re..."

...This result is consistent with recent reports (Anderson et al., 2011; Birn et al., 2013; Hacker et al., 2013)....
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...However, more recent reports have suggested that reliability is substantially improved with more than 10 min of data (Anderson et al., 2011; Birn et al., 2013; Hacker et al., 2013)....
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Journal Article•DOI•

Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: A systems neuroscience perspective

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Xi-Nian Zuo¹, Xiu-Xia Xing²•Institutions (2)

Chinese Academy of Sciences¹, Beijing University of Technology²

01 Sep 2014-Neuroscience & Biobehavioral Reviews

TL;DR: A meta-summary reliability analysis of seven common brain networks revealed that the heteromodal associative networks were mostly reliable across the seven networks, and observations can guide the use of reliable metrics and further improvement of test-retest reliability for other metics in functional connectomics.

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545 citations

Journal Article•DOI•

Building a Science of Individual Differences from fMRI.

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Julien Dubois¹, Ralph Adolphs¹•Institutions (1)

California Institute of Technology¹

01 Jun 2016-Trends in Cognitive Sciences

TL;DR: It is emphasized that individual assessment of neural function with fMRI presents specific challenges and necessitates careful consideration of anatomical and vascular between- subject variability as well as sources of within-subject variability.

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524 citations

Cites background from "The effect of scan length on the re..."

...Most subjects can lie quietly in the scanner for 5 or more minutes [159] (for more advanced analyses, up to 100 minutes of data may be required for best results [160])....
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Journal Article•DOI•

Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion.

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Ru Kong¹, Jingwei Li¹, Csaba Orban¹, Mert R. Sabuncu², Hesheng Liu³, Alexander Schaefer¹, Nanbo Sun¹, Xi-Nian Zuo⁴, Avram J. Holmes⁵, Simon B. Eickhoff⁶, B.T. Thomas Yeo - Show less +7 more•Institutions (6)

National University of Singapore¹, Cornell University², Harvard University³, Chinese Academy of Sciences⁴, Yale University⁵, University of Düsseldorf⁶

01 Jun 2019-Cerebral Cortex

TL;DR: Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography Estimated by other parcellation approaches, similar to connectivity strength, which might also serve as a fingerprint of human behavior.

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Abstract: Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimating individual-specific cortical networks and investigate whether individual-specific network topography can predict human behavior. The multiple layers of the MS-HBM explicitly differentiate intra-subject (within-subject) from inter-subject (between-subject) network variability. By ignoring intra-subject variability, previous network mappings might confuse intra-subject variability for inter-subject differences. Compared with other approaches, MS-HBM parcellations generalized better to new rs-fMRI and task-fMRI data from the same subjects. More specifically, MS-HBM parcellations estimated from a single rs-fMRI session (10 min) showed comparable generalizability as parcellations estimated by 2 state-of-the-art methods using 5 sessions (50 min). We also showed that behavioral phenotypes across cognition, personality, and emotion could be predicted by individual-specific network topography with modest accuracy, comparable to previous reports predicting phenotypes based on connectivity strength. Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography estimated by other parcellation approaches. Thus, similar to connectivity strength, individual-specific network topography might also serve as a fingerprint of human behavior.

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417 citations

Cites background from "The effect of scan length on the re..."

...; https://doi.org/10.1101/213041doi: bioRxiv preprint 37 provide reliable measurements (Van Dijk et al., 2010; Birn et al., 2013), more recent studies have suggested the need for 25 to 30 minutes of data (Anderson et al., 2011; Laumann et al., 2015; Gordon et al., 2017c)....
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...reliable measurements (Van Dijk et al. 2010; Birn et al. 2013), more recent studies have suggested the need for 25–30min of data (Anderson et al....
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TL;DR: In this article, the authors present guidelines for choosing among six different forms of the intraclass correlation for reliability studies in which n target are rated by k judges, and the confidence intervals for each of the forms are reviewed.

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Abstract: Reliability coefficients often take the form of intraclass correlation coefficients. In this article, guidelines are given for choosing among six different forms of the intraclass correlation for reliability studies in which n target are rated by k judges. Relevant to the choice of the coefficient are the appropriate statistical model for the reliability and the application to be made of the reliability results. Confidence intervals for each of the forms are reviewed.

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...In other words, both intrasession and intersession ICCs for single ratings with random effects were computed for each connection (matrix) separately using the following equation,whereMSb is the between subject mean squares andMSw is the within subjectmean squares (Shrout and Fleiss, 1979):...
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...…connection (matrix) separately using the following equation,whereMSb is the between subject mean squares andMSw is the within subjectmean squares (Shrout and Fleiss, 1979): ICC ¼ MSb−MSw MSbþ k−1ð ÞMSw : When the between subject variance is much greater than the within subject variance, the ICC…...
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