The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
The effect of scan length on the reliability of resting-state fMRI connectivity estimates
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Although our sample was adequately powered to detect large group differences in functional connectivity, it is possible that the length of the timeseries of individuals' resting-state data (5 min) was not long enough to generate reliable indices of functional connectivity (Birn et al., 2013), possibly leading to null differences between groups.”
From Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders (2019) · cites this paper as Birn et al., 2013
In the citing paper
“Data were then spatially normalized to the Montreal Neurological Institute template using the structural scans; previous studies suggest that this is adequate for reliable functional connectivity estimates 66, 67, 68.”
From History of early life adversity is associated with increased food addiction and sex-specific alterations in reward network connectivity in obesity (2019) · cites this paper as [66]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Intraclass correlations: Uses in assessing rater reliability.
Shrout, P. E., & Fleiss, J. L. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.2.420 · Cited by 24,532
Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
Measures of the Amount of Ecologic Association Between Species
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
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812
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
Zhang, Y., Brady, M., & Smith, S. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 7,628
Co-planar stereotaxic atlas of the human brain
Laitinen, L. (1989) · Clinical Neurology and Neurosurgery · doi:10.1016/0303-8467(89)90128-5 · Cited by 7,565
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.018 · Cited by 7,429
Cited by
Sorted by citations
Items 501–600 of 871
Dual-echo ASL based assessment of motor networks: a feasibility study
Storti, S. F., Galazzo, I. B., Pizzini, F. B., & Menegaz, G. (2017) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa8b27 · Cited by 9
Stange, J. P., Jenkins, L. M., Bessette, K. L., Kling, L. R., Bark, J. S., Shepard, R., Hamlat, E. J., DelDonno, S. R., Phan, K. L., Passarotti, A. M., et al. (2018) · Brain Connectivity · doi:10.1089/brain.2018.0619 · Cited by 9
Latency structure of BOLD signals within white matter in resting-state fMRI
Guo, B., Zhou, F., Li, M., & Gore, J. C. (2022) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2021.12.010 · Cited by 9
Godoy, P. B. G., Sumiya, F. M., Seda, L., & Shephard, E. (2022) · Brazilian Journal of Psychiatry · doi:10.47626/1516-4446-2021-2222 · Cited by 11
A Novel Brain Network Construction Method for Exploring Age-Related Functional Reorganization
Li, W., Wang, M., Li, Y., Huang, Y., & Chen, X. (2016) · Computational Intelligence and Neuroscience · doi:10.1155/2016/2429691 · Cited by 8
Memory Assessment in the Clinical Context Using Functional Magnetic Resonance Imaging
McAndrews, M. P. (2014) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2014.07.008 · Cited by 9
Taylor, M. B., Hammonds, R., & Filbey, F. M. (2021) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsab054 · Cited by 8
Resting-state cortical hubs in youth organize into four categories
Demeter, D. V., Gordon, E. M., Nugiel, T., Garza, A., Larguinho, T. L., & Church, J. A. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112521 · Cited by 8
Fennema, D., Barker, G. J., O’Daly, O., Duan, S., Carr, E., Goldsmith, K., Young, A. H., Moll, J., & Zahn, R. (2024) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2024.100308 · Cited by 8
Multiple focal pulvinar projection fields in the macaque cortex
Froesel, M., Clavagnier, S., Goudard, Q., Zhu, Q., Vanduffel, W., & Hamed, S. B. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00202 · Cited by 8
Liu, Y., Sundman, M., Ugonna, C., Chen, Y.-C. A., Green, J. M., Haaheim, L. G., Siu, H. M., & Chou, Y. (2024) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2024.1477049 · Cited by 8
Bezek, J. L., Tillem, S., Suarez, G. L., Burt, S. A., Vazquez, A. Y., Michael, C., Sripada, C., Kump, K. L., & Hyde, L. W. (2024) · American Psychologist · doi:10.1037/amp0001279 · Cited by 8
Kolobaric, A., Andreescu, C., Gerlach, A., Jašarević, E., Aizenstein, H. J., Pascoal, T. A., Ferreira, P. C. L., Bellaver, B., Hong, C. H., Roh, H. W., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.14493 · Cited by 8
Franklin, T. R., Jagannathan, K., Spilka, N. H., Keyser, H., Rao, H., Ely, A. V., Janes, A. C., & Wetherill, R. R. (2021) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2021.108593 · Cited by 9
Sahasrabudhe, S. A., Silamongkol, T., Park, Y. W., Colette, A. A., Eberly, L. E., Klimes‐Dougan, B., Coles, L. D., Öz, G., Mueller, B. A., Kartha, R. V., et al. (2021) · Journal of Psychiatry and Brain Science · doi:10.20900/jpbs.20210007 · Cited by 8
Satz, S., Halchenko, Y. O., Ragozzino, R., Lucero, M. M., Phillips, M. L., Swartz, H. A., & Manelis, A. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.749767 · Cited by 8
Sun, J., Du, R., Zhang, B., Hua, Q., Wang, Y., Zhang, Y., Ji, G., He, K., & Wang, K. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00720-y · Cited by 8
Zhang, D., Yu, L., Chen, Y., Shen, J., Du, L., Lin, L., & Wu, J. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhac531 · Cited by 8
Zhou, J., Jiao, X., Hu, Q., Du, L., Wang, J., & Sun, J. (2024) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2024.3368697 · Cited by 8
Boehm, I., Mennigen, E., Geisler, D., Poller, N. W., Gramatke, K., Calhoun, V. D., Roessner, V., King, J. A., & Ehrlich, S. (2024) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13970 · Cited by 8
fMRI in Neurodegenerative Diseases: From Scientific Insights to Clinical Applications
Dickerson, B. C., Agosta, F., & Filippi, M. (2016) · Neuromethods · doi:10.1007/978-1-4939-5611-1_23 · Cited by 8
Zhang, P.-W., Qu, X., Qian, S., Wang, X.-B., Wang, R., Li, Q., Liu, S., Chen, L., & Liu, D. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00516 · Cited by 8
Reliability of BOLD signals in chronic stroke‐induced aphasia
Higgins, J. P., Barbieri, E., Wang, X., Mack, J. W., Caplan, D., Kiran, S., Rapp, B. C., Thompson, C. K., Zinbarg, R. E., & Parrish, T. B. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.14739 · Cited by 8
Acquisition Duration in Resting-State Arterial Spin Labeling. How Long Is Enough?
Vallée, C., Maurel, P., Corouge, I., & Barillot, C. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00598 · Cited by 6
Hengenius, J. B., Bohnen, N. I., Rosso, A. L., Huppert, T. J., & Rosano, C. (2021) · Journal of Neuroimaging · doi:10.1111/jon.12949 · Cited by 8
Yang, J., Hellerstein, D. J., Chen, Y., McGrath, P. J., Stewart, J. W., Peterson, B. S., & Wang, Z. (2022) · Brain Communications · doi:10.1093/braincomms/fcac100 · Cited by 8
Altered functional connectivity in psychotic disorder not otherwise specified
Kim, W., Heo, D.-W., Shen, J., Tsogt, U., Odkhuu, S., Lee, J., Kang, E., Kim, S., Suk, H., & Chung, Y. (2022) · Psychiatry Research · doi:10.1016/j.psychres.2022.114871 · Cited by 8
Waring, J. D., Williams, S. E., Stevens, A., Pogarcic, A., Shimony, J. S., Snyder, A. Z., Bowie, C. R., & Lenze, E. J. (2023) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2023.01.004 · Cited by 9
Li, X., Liu, H., Deng, Y., Li, Z., Jiang, Y., Li, D., & Li, S. (2023) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14171 · Cited by 7
Artiles, O., Masry, Z. A., & Saeed, F. (2023) · Neuroinformatics · doi:10.1007/s12021-023-09639-1 · Cited by 9
Functional connectivity and cognitive changes after donepezil treatment in healthy participants
Péran, P., Salabert, A., Dondaine, T., Leclerc, X., Gros-Dagnac, H., Ranjeva, J., Lopes, R., Lanteaume, L., Blin, O., Thalamas, C., et al. (2021) · Psychopharmacology · doi:10.1007/s00213-021-05923-7 · Cited by 8
Stampacchia, S., Asadi, S., Tomczyk, S., Ribaldi, F., Scheffler, M., Lövblad, K., Pievani, M., Fall, A. B., Preti, M. G., Unshuld, P. G., et al. (2022) · bioRxiv · doi:10.1101/2022.02.04.479112 · Cited by 5
Temporal variability of brain–behavior relationships in fine-scale dynamics of edge time series
Cutts, S. A., Chumin, E. J., Betzel, R. F., & Sporns, O. (2025) · Imaging Neuroscience · doi:10.1162/imag_a_00443 · Cited by 7
Rai, S., Godfrey, K., Graff, K., Tansey, R. C., Merrikh, D., Yin, S., Feigelis, M., Demeter, D. V., Vanderwal, T., Greene, D. J., et al. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.117 · Cited by 9
Rodriguez, R. X., Noble, S., Camp, C., & Scheinost, D. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-02099-7 · Cited by 7
Genetic and environmental factors influencing neonatal resting-state functional connectivity
Blanchett, R., Chen, Y., Aguate, F. M., Xia, K., Cornea, E. A., Burt, S. A., Campos, G. D. L., Gao, W., Gilmore, J. H., & Knickmeyer, R. C. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac383 · Cited by 9
Automatic preprocessing pipeline for white matter functional analyses of large-scale databases
Gao, Y., Lawless, D. R., Li, M., Zhao, Y., Schilling, K. G., Xu, L., Shafer, A. T., Beason‐Held, L. L., Resnick, S. M., Rogers, B. P., et al. (2023) · SPIE Medical Imaging: Image Processing · doi:10.1117/12.2653132 · Cited by 7
Qiu, Y., Wu, X., Liu, B., Huang, R., & Wu, H. (2024) · Human Brain Mapping · doi:10.1002/hbm.26696 · Cited by 6
Averill, C. L., Averill, L. A., Akiki, T. J., Fouda, S., Krystal, J. H., & Abdallah, C. G. (2024) · NPP—Digital Psychiatry and Neuroscience · doi:10.1038/s44277-024-00011-y · Cited by 11
Perez, D. C., Hernandez, J. J., Wulfekuhle, G. E., & Gratton, C. (2024) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2024.11.010 · Cited by 7
Shearer, H., Eilbott, J. A., Vila‐Rodriguez, F., Noble, S., Xu, T., & Vanderwal, T. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00411 · Cited by 7
Champagne, A. A., Coverdale, N. S., Allen, M. D., Tremblay, J. C., MacPherson, R. E. K., Pyke, K. E., Olver, T. D., & Cook, D. J. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-021-00570-0 · Cited by 7
Lalousis, P. A., Malaviya, A., Upthegrove, R., Heinze, K., Diukova, A., Auer, D. P., Liddle, P. F., & Mallikarjun, P. K. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00731-9 · Cited by 7
Deep brain imaging of three participants across 1 year: The Bergen breakfast scanning club project
Wang, M., Korbmacher, M., Eikeland, R., & Specht, K. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.1021503 · Cited by 7
Predicting Antidepressant Treatment Response Using Functional Brain Controllability Analysis
Fang, F. Z., Godlewska, B. R., Selvaraj, S., & Zhang, Y. (2022) · Brain Connectivity · doi:10.1089/brain.2022.0027 · Cited by 7
Functional connectivity analysis of childhood depressive symptoms
Huang, P., Chan, S. Y., Ngoh, Z. M., Nadarajan, R., Chong, Y. S., Gluckman, P. D., Chen, H., Fortier, M. V., Tan, A. P., & Meaney, M. J. (2023) · NeuroImage Clinical · doi:10.1016/j.nicl.2023.103395 · Cited by 7
Functional MRI responses to naturalistic stimuli are increasingly typical across early childhood
Tansey, R. C., Graff, K., Rohr, C. S., Dimond, D., Ip, A., Yin, S., Dewey, D., & Bray, S. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101268 · Cited by 6
Neural responses to children’s faces: Test–retest reliability of structural and functional MRI
Heckendorf, E., Bakermans‐Kranenburg, M. J., van IJzendoorn, M. H., & Huffmeijer, R. (2019) · Brain and Behavior · doi:10.1002/brb3.1192 · Cited by 7
Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia
Vergara, V. M., Damaraju, E., Turner, J. A., Pearlson, G. D., Belger, A., Mathalon, D. H., Potkin, S. G., Preda, A., Vaidya, J. G., van Erp, T. G. M., et al. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00499 · Cited by 7
Striatal dynamics as determinants of reduced gambling vulnerability in the NHE rat model of ADHD
Oggiano, M., Zoratto, F., Palombelli, G., Festucci, F., Laviola, G., Curcio, G., Canese, R., & Adriani, W. (2020) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2020.109886 · Cited by 7
Zhang, M., Dang, J., Sun, J., Tao, Q., Niu, X., Wang, W., Han, S., Cheng, J., & Zhang, Y. (2024) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.240058 · Cited by 6
Age‐ and Sex‐Specific Patterns in Adult Brain Network Segregation
Sidhu, A. S., Duarte, K. T. N., Shahid, T. H., Sharkey, R. J., Lauzon, M. L., Salluzzi, M., McCreary, C. R., Protzner, A. B., Goodyear, B. G., & Frayne, R. (2025) · Human Brain Mapping · doi:10.1002/hbm.70169 · Cited by 6
Häkkinen, S., Voorhies, W. I., Willbrand, E. H., Tsai, Y., Gagnant, T., Yao, J. K., Weiner, K. S., & Bunge, S. A. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.0726-24.2025 · Cited by 7
Dalloul, N., van Huijgevoort, C., Belmont, J., & Barch, D. M. (2025) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2025.106385 · Cited by 8
Jiang, J., Li, W., Cui, H., Zhu, Z., Zhang, L., Hu, Q., Li, H., Wang, Y., Pang, J., Wang, Y., et al. (2023) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2023.111656 · Cited by 6
Huynh, V., Lütolf, R., Rösner, J., Luechinger, R., Curt, A. E. P., Kollias, S. S., Michels, L., & Hubli, M. (2023) · Scientific Reports · doi:10.1038/s41598-023-37783-w · Cited by 6
Freedberg, M. (2023) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2023.108723 · Cited by 6
Cattarinussi, G., Meda, N., Miola, A., & Sambataro, F. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.04.048 · Cited by 6
Kashou, A., Frees, D. M., Kang, K., Parks, C. O., Harralson, H., Fischer, J. T., Rosenbaum, P. E., Baham, M., Sheridan, C. A., & Bickart, K. C. (2024) · Frontiers in Neurology · doi:10.3389/fneur.2024.1487796 · Cited by 6
Tang, L., Kebaya, L., Vahidi, H., Meyerink, P., de Ribaupierre, S., Bhattacharya, S., Lawrence, K. S., & Duerden, E. G. (2024) · Scientific Reports · doi:10.1038/s41598-024-79390-3 · Cited by 6
Singh, A., Bekhbat, M., Goldsmith, D. R., Le, N., Wommack, E. C., Li, Z., Haroon, E., & Felger, J. C. (2025) · Comprehensive Psychoneuroendocrinology · doi:10.1016/j.cpnec.2025.100284 · Cited by 7
Moreau, A. L., Hansen, I. S., & Bogdan, R. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1432253 · Cited by 6
Fernandes, C. D., Varsou, O., Stringer, M. S., MacLeod, M. J., & Schwarzbauer, C. (2020) · Advances in experimental medicine and biology · doi:10.1007/978-3-030-37639-0_3 · Cited by 6
Jiang, Y. B., Chen, Y., Zheng, R., Zhou, B., Wei, Y., Gao, A., Wei, Y., Li, S., Guo, J., Han, S., et al. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.868135 · Cited by 6
Interaction Between Memory Load and Experimental Design on Brain Connectivity and Network Topology
Zhang, H., Di, X., Bart Rypma, A., Yang, H., Meng, C., & Biswal, B. B. (2022) · Neuroscience Bulletin · doi:10.1007/s12264-022-00982-y · Cited by 6
Hranilovich, J. A., Legget, K. T., Dodd, K. C., Wylie, K. P., & Tregellas, J. R. (2023) · Headache The Journal of Head and Face Pain · doi:10.1111/head.14487 · Cited by 6
Feng, Z., Zhang, H., Zhou, T., Yu, X., Zhang, Y., & Yan, X. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02615-y · Cited by 6
Mori, A., Klöbl, M., Okada, G., Reed, M. B., Takamura, M., Michenthaler, P., Takagaki, K., Handschuh, P. A., Yokoyama, S., Murgaš, M., et al. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00289 · Cited by 6
Boissoneault, J., Sevel, L. S., Stennett, B., Alappattu, M. J., Bishop, M. D., & Robinson, M. (2020) · European Journal of Pain · doi:10.1002/ejp.1532 · Cited by 6
Kulkarni, A. P., Chung, M. K., Bendlin, B. B., & Prabhakaran, V. (2020) · doi:10.1109/isbiworkshops50223.2020.9153361 · Cited by 6
Self-citationThe intra‐session reliability of functional connectivity during naturalistic viewing conditions
Hlinka, J., Děchtěrenko, F., Rydlo, J., Androvičová, R., Vejmelka, M., Jajcay, L., Tintěra, J., Lukavský, J., & Horáček, J. (2022) · Psychophysiology · doi:10.1111/psyp.14075 · Cited by 6
Anderson, Z. G., Turner, J. A., Ashar, Y. K., Calhoun, V. D., & Mittal, V. A. (2024) · Aperture Neuro · doi:10.52294/001c.91992 · Cited by 6
Demeter, D. V., Feigelis, M., D’Andrea, C. B., Ali, S., Baim, A. R., Koithan, E. M., Stearns, J., Zreik, S., Ahern, J., Park, S., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.21.665760 · Cited by 10
Stampacchia, S., Bernasconi, F., Van De Ville, D., Amico, E., Pagonabarraga, J., Kulisevsky, J., & Blanke, O. (2025) · doi:10.1101/2025.04.17.649310 · Cited by 5
Allen, C. H., Shold, J. N., Maurer, J. M., Reynolds, B. L., Anderson, N. E., Harenski, C. L., Harenski, K. A., Calhoun, V. D., & Kiehl, K. A. (2023) · NeuroImage Clinical · doi:10.1016/j.nicl.2023.103343 · Cited by 5
Establishing language laterality: does resting-state functional MRI help?
Singh, S., Alhasan, M. S., Wang, Z., Clarke, R. L., Xi, Y., Maldjian, J. A., Wagner, B. C., & Booth, T. N. (2023) · Journal of Neurosurgery Pediatrics · doi:10.3171/2023.1.peds22497 · Cited by 5
Allen, C. H., Maurer, J. M., Gullapalli, A. R., Edwards, B. G., Aharoni, E., Harenski, C. L., Anderson, N. E., Harenski, K. A., Calhoun, V. D., & Kiehl, K. A. (2023) · Frontiers in Neuroimaging · doi:10.3389/fnimg.2023.1216494 · Cited by 5
Hussain, S., Menchaca, I., Shalchy, M. A., Yaghoubi, K. C., Langley, J. A., Seitz, A. R., Hu, X. P., & Peters, M. A. K. (2023) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2023.110733 · Cited by 6
Jin, X., Liang, X., & Gong, G. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00205 · Cited by 5
Advanced EEG and MRI Measurements to Study the Functional Development of the Newborn Brain
Vanhatalo, S., & Fransson, P. (2015) · Neuromethods · doi:10.1007/978-1-4939-3014-2_4 · Cited by 5
Fetal Frontolimbic Connectivity Prospectively Associates With Aggression in Toddlers
Hendrix, C. L., Ji, L., Werchan, D. M., Majbri, A., Trentacosta, C. J., Burt, S. A., & Thomason, M. E. (2022) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2022.09.003 · Cited by 6
Edalati, H., Afzali, M. H., Spinney, S., Bourque, J., Dagher, A., & Conrod, P. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1099772 · Cited by 6
Effects of phase encoding direction on test-retest reliability of human functional connectome
Cao, H., Barber, A. D., Rubio, J. M., Árgyelán, M., Gallego, J. A., Lencz, T., & Malhotra, A. K. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120238 · Cited by 5
Poverty, Brain Development, and Mental Health: Progress, Challenges, and Paths Forward
Monk, C. S., & Hardi, F. A. (2023) · Annual Review of Developmental Psychology · doi:10.1146/annurev-devpsych-011922-012402 · Cited by 9
Churchill, N. W., Roudaia, E., Chen, J. J., Gilboa, A., Sekuler, A. B., Ji, X., Gao, F., Lin, Z., Masellis, M., Goubran, M., et al. (2023) · Brain and Behavior · doi:10.1002/brb3.3212 · Cited by 5
Longitudinal prognosis of Parkinson’s outcomes using causal connectivity
Mellema, C., Nguyen, K. P., Treacher, A., Andrade, A. X., Pouratian, N., Sharma, V. D., O’Suilleabhain, P. E., & Montillo, A. (2024) · NeuroImage Clinical · doi:10.1016/j.nicl.2024.103571 · Cited by 5
Personality reflection in the brain’s intrinsic functional architecture remains elusive
Tomeček, D., Androvičová, R., Fajnerová, I., Děchtěrenko, F., Rydlo, J., Horáček, J., Lukavský, J., Tintěra, J., & Hlinka, J. (2020) · PLoS ONE · doi:10.1371/journal.pone.0232570 · Cited by 5
Xu, S., Sun, Q., Li, M., Luo, J., Cai, G., Chen, R., Zhang, L., & Liu, J. (2021) · Brain Science Advances · doi:10.26599/bsa.2021.9050013 · Cited by 5
Learning Subject-Specific Functional Parcellations from Cortical Surface Measures
Bayrak, R. G., Lyu, I., & Chang, C. E. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16919-9_16 · Cited by 5
Allen, C. H., Maurer, J. M., Edwards, B. G., Gullapalli, A. R., Harenski, C. L., Harenski, K. A., Calhoun, V. D., & Kiehl, K. A. (2022) · Frontiers in Neuroimaging · doi:10.3389/fnimg.2022.971201 · Cited by 5
Verbal fluency and intrinsic brain activity in Alzheimer’s disease
Kljajević, V. (2015) · Croatian Medical Journal · doi:10.3325/cmj.2015.56.573 · Cited by 6
Kehoe, P. D., Saenger, V. M., Lisofsky, N., Kühn, S., Kringelbach, M. L., Schwarzbach, J. V., & Deco, G. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/104232 · Cited by 5
Duda, M., Iraji, A., Ford, J. M., Lim, K. O., Mathalon, D. H., Mueller, B. A., Potkin, S. G., Preda, A., van Erp, T. G. M., & Calhoun, V. D. (2022) · medRxiv · doi:10.1101/2022.03.17.22271783 · Cited by 5
Griffa, A., Mach, M., Dedelley, J., Gutierrez‐Barragan, D., Gozzi, A., Allali, G., Grandjean, J., Ville, D. V. D., & Amico, E. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.09.491115 · Cited by 5
Korponay, C. H., Janes, A. C., & Frederick, B. B. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.08.556939 · Cited by 5
Fear learning sculpts functional brain connectivity at rest beyond the traditional fear network
Fraenz, C., Metzen, D., Merz, C. J., Selpien, H., Friedrich, P., Ocklenburg, S., Axmacher, N., & Genç, E. (2025) · Behavioural Brain Research · doi:10.1016/j.bbr.2025.115764 · Cited by 6
Doucet, G. E., Kruse, J. A., Eden, N. M., Goffman, L., & McGregor, K. K. (2025) · Brain and Language · doi:10.1016/j.bandl.2025.105637 · Cited by 4
Papke, V., Klimes‐Dougan, B., Sahasrabudhe, S. A., Mueller, B. A., Park, Y. W., Öz, G., Eberly, L. E., DiMaggio-Potter, M. E., Kartha, R. V., Cloyd, J. C., et al. (2025) · BJPsych Open · doi:10.1192/bjo.2025.10839 · Cited by 4
Chung, J., Lee, P., Lee, Y., Yoo, K., & Jeong, Y. (2022) · eNeuro · doi:10.1523/eneuro.0358-21.2022 · Cited by 4
Developmental differences of large-scale functional brain networks for spoken word processing
Liu, X., Yin, H., Gao, Y., Booth, J. R., Zhang, L., Zhang, S., Lu, C., & Liu, L. (2022) · Brain and Language · doi:10.1016/j.bandl.2022.105149 · Cited by 4
Metadata
- 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
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-12
- Volume
- 83
- Pages
- 550-558
- ISSN
- 1053-8119 (ISSN-L)
- 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
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review