Cited by 875Functional Brain Connectivity StudiesAdvanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and Applications

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

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Birn, Rasmus M., Molloy, Erin K., Patriat, Rémi, Parker, Taurean, Meier, Timothy B., Kirk, Gregory R., Nair, Veena A., Meyerand, M. Elizabeth, Prabhakaran, Vivek·2013·NeuroImage

DOI 10.1016/j.neuroimage.2013.05.099PMC PMC4104183

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Abstract

There has been an increasing use of functional magnetic resonance imaging (fMRI) by the neuroscience community to examine differences in functional connectivity between normal control groups and populations of interest. Understanding the reliability of these functional connections is essential to the study of neurological development and degenerate neuropathological conditions. To date, most research assessing the reliability with which resting-state functional connectivity characterizes the brain's functional networks has been on scans between 3 and 11 min in length. In our present study, we examine the test-retest reliability and similarity of resting-state functional connectivity for scans ranging in length from 3 to 27 min as well as for time series acquired during the same length of time but excluding half the time points via sampling every second image. Our results show that reliability and similarity can be greatly improved by increasing the scan lengths from 5 min up to 13 min, and that both the increase in the number of volumes as well as the increase in the length of time over which these volumes was acquired drove this increase in reliability. This improvement in reliability due to scan length is much greater for scans acquired during the same session. Gains in intersession reliability began to diminish after 9-12 min, while improvements in intrasession reliability plateaued around 12-16 min. Consequently, new techniques that improve reliability across sessions will be important for the interpretation of longitudinal fMRI studies.

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Shrout, P. E., & Fleiss, J. L. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.2.420 · Cited by 24,532
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Dice, L. R. (1945) · Ecology · doi:10.2307/1932409 · Cited by 12,187
Co-Planar Stereotaxic Atlas of the Human Brain
Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798
AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
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The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
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Stability of low-frequency fluctuation amplitudes in prolonged resting-state fMRI
Küblböck, M., Woletz, M., Höflich, A. S., Sladky, R., Kranz, G. S., Hoffmann, A., Lanzenberger, R. R., & Windischberger, C. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.09.038 · Cited by 100
Experiences of Discrimination Are Associated With Greater Resting Amygdala Activity and Functional Connectivity
Clark, U. S., Miller, E. R., & Hegde, R. R. (2017) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2017.11.011 · Cited by 106
Presurgical thalamocortical connectivity is associated with response to vagus nerve stimulation in children with intractable epilepsy
Ibrahim, G. M., Sharma, P., Hyslop, A. E., Guillen, M. R., Morgan, B. R., Wong, S. M., Abel, T. J., Elkaim, L. M., Cajigas, I., Shah, A. H., et al. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.09.015 · Cited by 99
Resting state connectivity of the bed nucleus of the stria terminalis at ultra‐high field
Torrisi, S., O’Connell, K., Davis, A., Reynolds, R. C., Balderston, N. L., Fudge, J. L., Grillon, C., & Ernst, M. (2015) · Human Brain Mapping · doi:10.1002/hbm.22899 · Cited by 104
Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults
Deng, S., Franklin, C. G., O’Boyle, M. W., Zhang, W., Heyl, B. L., Jerabek, P. A., Lu, H., & Fox, P. T. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.118923 · Cited by 99
Resting State fMRI: Going Through the Motions
Maknojia, S., Churchill, N. W., Schweizer, T. A., & Graham, S. J. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00825 · Cited by 108
Functional connectivity-based subtypes of individuals with and without autism spectrum disorder
Easson, A. K., Fatima, Z., & McIntosh, A. R. (2019) · Network Neuroscience · doi:10.1162/netn_a_00067 · Cited by 95
Longitudinal reproducibility of default-mode network connectivity in healthy elderly participants: A multicentric resting-state fMRI study
Jovicich, J., Minati, L., Marizzoni, M., Marchitelli, R., Sala‐Llonch, R., Bartrés‐Faz, D., Arnold, J., Benninghoff, J., Fiedler, U., Roccatagliata, L., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.010 · Cited by 96
Levodopa modulates small‐world architecture of functional brain networks in Parkinson's disease
Berman, B. D., Smucny, J., Wylie, K. P., Shelton, E., Kronberg, E., Leehey, M. A., & Tregellas, J. R. (2016) · Movement Disorders · doi:10.1002/mds.26713 · Cited by 96
Striving toward translation: strategies for reliable fMRI measurement
Elliott, M. L., Knodt, A. R., & Hariri, A. R. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2021.05.008 · Cited by 93
Effect of Resting-State fNIRS Scanning Duration on Functional Brain Connectivity and Graph Theory Metrics of Brain Network
Geng, S., Liu, X., Biswal, B. B., & Niu, H. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00392 · Cited by 95
Reproducibility of Graph-Theoretic Brain Network Metrics: A Systematic Review
Welton, T., Kent, D. A., Auer, D. P., & Dineen, R. A. (2014) · Brain Connectivity · doi:10.1089/brain.2014.0313 · Cited by 96
The Influence of Physiological Noise Correction on Test–Retest Reliability of Resting-State Functional Connectivity
Birn, R. M., Cornejo, M. D., Molloy, E. K., Patriat, R., Meier, T. B., Kirk, G. R., Nair, V. A., Meyerand, M. E., & Prabhakaran, V. (2014) · Brain Connectivity · doi:10.1089/brain.2014.0284 · Cited by 91
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Liu, J., Chen, L., Chen, X., Hu, K., Tu, Y., Lin, M., Huang, J., Liu, W., Wu, J., Qiu, Z., et al. (2019) · British Journal of Anaesthesia · doi:10.1016/j.bja.2019.06.017 · Cited by 90
Reliability and stability challenges in ABCD task fMRI data
Kennedy, J. T., Harms, M. P., Korucuoglu, O., Astafiev, S. V., Barch, D. M., Thompson, W. K., Bjork, J. M., & Anokhin, A. P. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119046 · Cited by 89
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Yamashita, M., Yoshihara, Y., Hashimoto, R., Yahata, N., Ichikawa, N., Sakai, Y., Yamada, T., Matsukawa, N., Okada, G., Tanaka, S., et al. (2018) · eLife · doi:10.7554/elife.38844 · Cited by 92
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Shao, L., Fu, C., You, Y., & Fu, D. (2021) · Cognitive Neurodynamics · doi:10.1007/s11571-021-09683-0 · Cited by 92
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Ooi, L. Q. R., Orbán, C., Zhang, S., Nichols, T. E., Tan, T. W. K., Kong, R., Marek, S. A., Dosenbach, N. U. F., Laumann, T. O., Gordon, E. M., et al. (2025) · Nature · doi:10.1038/s41586-025-09250-1 · Cited by 94
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Xia, M., & Yong He, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.031 · Cited by 85
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Tomasi, D. G., Kojori, E. S., & Volkow, N. D. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv171 · Cited by 87
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Ebner, N. C., Chen, H., Porges, E., Lin, T., Fischer, H., Feifel, D., & Cohen, R. A. (2016) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2016.03.013 · Cited by 84
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Chen, J. J., Jann, K., & Wang, D. J. J. (2015) · Brain Connectivity · doi:10.1089/brain.2015.0344 · Cited by 84
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Zhang, C., Baum, S. A., Adduru, V. R., Biswal, B. B., & Michael, A. M. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.021 · Cited by 84
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Authors: Birn, R. M., Molloy, E. K., Patriat, R., Parker, T., Meier, T. B., Kirk, G. R., Nair, V. A., Meyerand, M. E., & Prabhakaran, V.
Affiliations: University of Wisconsin–Madison (US)
University of Rochester (US)
Corresponding author: Birn, Rasmus M.
ORCID: Birn, Rasmus M.
Molloy, Erin K.
Patriat, Rémi
Meier, Timothy B.
Nair, Veena A.
Meyerand, M. Elizabeth
Prabhakaran, Vivek
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2013-12
Volume: 83
Pages: 550-558
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2013.05.099
PMC: PMC4104183
OpenAlex: W2084892943
Cited by: 875
References: 40
Citations by year: 2026: 81 · 2025: 93 · 2024: 72 · 2023: 91 · 2022: 77 · 2021: 101 · 2020: 82 · 2019: 59 · 2018: 62 · 2017: 48 · 2016: 43 · 2015: 40 · 2014: 22 · 2013: 3
FWCI: 19.39
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
Funders: NIH (RC1MH090912)
Health Emotions Research Institute
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Keywords: resting-state functional connectivity, scan length, test-retest reliability, inter-session reliability, within-session reliability, time series length, sampling frequency, longitudinal fMRI, functional brain networks
MeSH terms: Adult, Brain, Brain Mapping, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Nerve Net, Rest, Sensitivity and Specificity, Signal Processing, Computer-Assisted, Reproducibility of Results, Information Storage and Retrieval, Sample Size, Connectome

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

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