Predicting individual brain maturity using dynamic functional connectivity
Open accessAbstract
Neuroimaging-based functional connectivity (FC) analyses have revealed significant developmental trends in specific intrinsic connectivity networks linked to cognitive and behavioral maturation. However, knowledge of how brain functional maturation is associated with FC dynamics at rest is limited. Here, we examined age-related differences in the temporal variability of FC dynamics with data publicly released by the Nathan Kline Institute (NKI; n = 183, ages 7-30) and showed that dynamic inter-region interactions can be used to accurately predict individual brain maturity across development. Furthermore, we identified a significant age-dependent trend underlying dynamic inter-network FC, including increasing variability of the connections between the visual network, default mode network (DMN) and cerebellum as well as within the cerebellum and DMN and decreasing variability within the cerebellum and between the cerebellum and DMN as well as the cingulo-opercular network. Overall, the results suggested significant developmental changes in dynamic inter-network interaction, which may shed new light on the functional organization of typical developmental brains.
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
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?
Over development, rs-fcMRI networks show increased within-subject variability, consistent with EEG studies showing increased signal complexity.
“Over development, rs-fcMRI networks show increased within-subject variability (Hutchison and Morton, 2015; Marusak et al., 2016; Qin et al., 2015), consistent with EEG studies showing that signal complexity increases over development (McIntosh et al., 2008; Vakorin et al., 2011).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Qin et al., 2015
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The organization of the human cerebellum estimated by intrinsic functional connectivity
Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., & Yeo, B. T. T. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00339.2011 · Cited by 7,304 · see citing works
Tracking whole-brain connectivity dynamics in the resting state
Allen, E. A., Damaraju, E., Plis, S. M., Erhardt, E. B., Eichele, T., & Calhoun, V. D. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhs352 · Cited by 2,992 · see citing works
Dynamic functional connectivity: Promise, issues, and interpretations
Hutchison, R. M., Womelsdorf, T., Allen, E. A., Bandettini, P. A., Calhoun, V. D., Corbetta, M., Della Penna, S., Duyn, J. H., Glover, G. H., Gonzalez-Castillo, J., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.079 · Cited by 2,962 · see citing works
The influence of head motion on intrinsic functional connectivity MRI
Van Dijk, K. R. A., Sabuncu, M. R., & Buckner, R. L. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.07.044 · Cited by 2,344 · see citing works
Prediction of individual brain maturity using fMRI
Dosenbach, N. U. F., Nardos, B., Cohen, A. L., Fair, D. A., Power, J. D., Church, J. A., Nelson, S. M., Wig, G. S., Vogel, A. C., Lessov-Schlaggar, C. N., et al. (2010) · Science · doi:10.1126/science.1194144 · Cited by 2,183 · see citing works
A default mode of brain function: a brief history of an evolving idea
Raichle, M. E., & Snyder, A. Z. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.02.041 · Cited by 2,173 · see citing works
Decoding subject-driven cognitive states with whole-brain connectivity patterns
Shirer, W. R., Ryali, S., Rykhlevskaia, E., Menon, V., & Greicius, M. D. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhr099 · Cited by 1,843 · see citing works
Time–frequency dynamics of resting-state brain connectivity measured with fMRI
Chang, C., & Glover, G. H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.011 · Cited by 1,808 · see citing works
Neurodevelopmental Trajectories of the Human Cerebral Cortex
Shaw, P., Kabani, N. J., Lerch, J. P., Eckstrand, K., Lenroot, R., Gogtay, N., Greenstein, D., Clasen, L., Evans, A., Rapoport, J. L., et al. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.5309-07.2008 · Cited by 1,644 · see citing works
Functional brain networks develop from a local to distributed organization
Fair, D. A., Cohen, A. L., Power, J. D., Dosenbach, N. U. F., Church, J. A., Miezin, F. M., Schlaggar, B. L., & Petersen, S. E. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000381 · Cited by 1,530 · see citing works
Resting-state fMRI in the human connectome project
Smith, S. M., Beckmann, C. F., Andersson, J., Auerbach, E. J., Bijsterbosch, J., Douaud, G., Duff, E., Feinberg, D. A., Griffanti, L., Harms, M. P., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.039 · Cited by 1,502 · see citing works
The maturing architecture of the brain's default network
Fair, D. A., Cohen, A. L., Dosenbach, N. U. F., Church, J. A., Miezin, F. M., Barch, D. M., Raichle, M. E., Petersen, S. E., & Schlaggar, B. L. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800376105 · Cited by 1,314 · see citing works
Development of distinct control networks through segregation and integration
Fair, D. A., Dosenbach, N. U. F., Church, J. A., Cohen, A. L., Brahmbhatt, S., Miezin, F. M., Barch, D. M., Raichle, M. E., Petersen, S. E., & Schlaggar, B. L. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0705843104 · Cited by 1,244 · see citing works
Satterthwaite, T. D., Wolf, D. H., Loughead, J., Ruparel, K., Elliott, M. A., Hakonarson, H., Gur, R. C., & Gur, R. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.063 · Cited by 1,125 · see citing works
Damaraju, E., Allen, E. A., Belger, A., Ford, J. M., McEwen, S. C., Mathalon, D. H., Mueller, B. A., Pearlson, G. D., Potkin, S. G., Preda, A., et al. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.07.003 · Cited by 1,066 · see citing works
Functional brain development in humans
Johnson, M. H. (2001) · Nature Reviews Neuroscience · doi:10.1038/35081509 · Cited by 980 · see citing works
The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry
Nooner, K. B., Colcombe, S., Tobe, R. H., Mennes, M., Benedict, M. M., Moreno, A. L., Panek, L. J., Brown, S., Zavitz, S. T., Li, Q., et al. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00152 · Cited by 855 · see citing works
On spurious and real fluctuations of dynamic functional connectivity during rest
Leonardi, N., & Van De Ville, D. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.09.007 · Cited by 828 · see citing works
Betzel, R. F., Byrge, L., He, Y., Goñi, J., Zuo, X.-N., & Sporns, O. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.07.067 · Cited by 807 · see citing works
Development of large-scale functional brain networks in children
Supekar, K., Musen, M., & Menon, V. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000157 · Cited by 807 · see citing works
Life-Span Changes of the Human Brain White Matter: Diffusion Tensor Imaging (DTI) and Volumetry
Westlye, L. T., Walhovd, K. B., Dale, A. M., Bjornerud, A., Due-Tonnessen, P., Engvig, A., Grydeland, H., Tamnes, C. K., Ostby, Y., & Fjell, A. M. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp280 · Cited by 765 · see citing works
Time-resolved resting-state brain networks
Zalesky, A., Fornito, A., Cocchi, L., Gollo, L. L., & Breakspear, M. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1400181111 · Cited by 753 · see citing works
Hallquist, M. N., Hwang, K., & Luna, B. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.116 · Cited by 753 · see citing works
Zeng, L.-L., Shen, H., Liu, L., Wang, L., Li, B., Fang, P., Zhou, Z., Li, Y., & Hu, D. (2012) · Brain · doi:10.1093/brain/aws059 · Cited by 748 · see citing works
Self-citationA Brain-Wide Study of Age-Related Changes in Functional Connectivity
Geerligs, L., Renken, R. J., Saliasi, E., Maurits, N. M., & Lorist, M. M. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu012 · Cited by 729 · see citing works
Hutchison, R. M., Womelsdorf, T., Gati, J. S., Everling, S., & Menon, R. S. (2012) · Human Brain Mapping · doi:10.1002/hbm.22058 · Cited by 715 · see citing works
Liu, X., & Duyn, J. H. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1216856110 · Cited by 647 · see citing works
Sakoğlu, Ü., Pearlson, G. D., Kiehl, K. A., Wang, Y. M., Michael, A. M., & Calhoun, V. D. (2010) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-010-0197-8 · Cited by 620 · see citing works
Uncovering Intrinsic Modular Organization of Spontaneous Brain Activity in Humans
Yong He, A., Wang, J., Wang, L. Y., Chen, Z. J., Yan, C., Yang, H., Tang, H., Zhu, C., Gong, Q., Zang, Y., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005226 · Cited by 619 · see citing works
Amplitude of low frequency fluctuation within visual areas revealed by resting-state functional MRI
Yang, H., Long, X., Yang, Y., Yan, H., Zhu, C.-Z., Zhou, X.-P., Zang, Y., & Gong, Q. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.01.054 · Cited by 613 · see citing works
Development of Anterior Cingulate Functional Connectivity from Late Childhood to Early Adulthood
Kelly, A. M. C., Di Martino, A., Uddin, L. Q., Shehzad, Z., Gee, D. G., Reiss, P. T., Margulies, D. S., Castellanos, F. X., & Milham, M. P. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn117 · Cited by 572 · see citing works
The functional architecture of the infant brain as revealed by resting-state fMRI
Fransson, P., Åden, U., Blennow, M., & Lagercrantz, H. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq071 · Cited by 542 · see citing works
Supekar, K., Uddin, L. Q., Prater, K. E., Amin, H., Greicius, M. D., & Menon, V. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.009 · Cited by 524 · see citing works
Uddin, L. Q., Supekar, K. S., Ryali, S., & Menon, V. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.4465-11.2011 · Cited by 520 · see citing works
Age-related alterations in default mode network: Impact on working memory performance
Sambataro, F., Murty, V. P., Callicott, J. H., Tan, H.-Y., Das, S., Weinberger, D. R., & Mattay, V. S. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2008.05.022 · Cited by 517 · see citing works
Sadaghiani, S., Scheeringa, R., Lehongre, K., Morillon, B., Giraud, A.-L., & Kleinschmidt, A. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.1004-10.2010 · Cited by 504 · see citing works
LUNA, B., & SWEENEY, J. A. (2004) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1308.035 · Cited by 467 · cited 2× · see citing works
“Both of the groups have a high prediction accuracy (for the first group, MAE = 4.7 years, SE = 0.3 years, and for the second group, MAE = 4.8 years, SE = 0.4 years).”
BackgroundInfluentialHan, Y., Wang, J., Zhao, Z., Min, B., Lu, J., Li, K., Yong He, A., & Jia, J. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.11.059 · Cited by 442 · see citing works
Increased Brain Signal Variability Accompanies Lower Behavioral Variability in Development
McIntosh, A. R., Kovacevic, N., & Itier, R. J. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000106 · Cited by 431 · see citing works
Non-Stationarity in the “Resting Brain’s” Modular Architecture
Jones, D. T., Vemuri, P., Murphy, M. C., Gunter, J. L., Senjem, M. L., Machulda, M. M., Przybelski, S. A., Gregg, B. E., Kantarci, K., Knopman, D. S., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0039731 · Cited by 427 · see citing works
Rubia, K., Smith, A. B., Taylor, E., & Brammer, M. (2007) · Human Brain Mapping · doi:10.1002/hbm.20347 · Cited by 417 · see citing works
Mind wandering away from pain dynamically engages antinociceptive and default mode brain networks
Kucyi, A., Salomons, T. V., & Davis, K. D. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1312902110 · Cited by 402 · see citing works
Blood Oxygen Level-Dependent Signal Variability Is More than Just Noise
Garrett, D. D., Kovacevic, N., McIntosh, A. R., & Grady, C. L. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.5166-09.2010 · Cited by 396 · see citing works
Neurodevelopmental changes in working memory and cognitive control
Bunge, S. A., & Wright, S. B. (2007) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2007.02.005 · Cited by 381 · see citing works
Dynamic functional connectivity of the default mode network tracks daydreaming
Kucyi, A., & Davis, K. D. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.044 · Cited by 355 · see citing works
Atypical default network connectivity in youth with attention-deficit/hyperactivity disorder
Fair, D. A., Posner, J., Nagel, B. J., Bathula, D., Dias, T. G. C., Mills, K. L., Blythe, M. S., Giwa, A., Schmitt, C. F., & Nigg, J. T. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.07.003 · Cited by 354 · see citing works
Shen, H., Wang, L., Liu, Y., & Hu, D. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.11.011 · Cited by 352 · see citing works
Self-citationGrady, C. L., Protzner, A. B., Kovacevic, N., Strother, S. C., Afshin‐Pour, B., Wojtowicz, M., Anderson, J. A. E., Churchill, N. W., & McIntosh, A. R. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhp207 · Cited by 327 · see citing works
Glerean, E., Salmi, J., Lahnakoski, J. M., Jääskeläinen, I. P., & Sams, M. (2012) · Brain Connectivity · doi:10.1089/brain.2011.0068 · Cited by 313 · see citing works
Neurobiological basis of head motion in brain imaging
Zeng, L., Wang, D., Fox, M., Sabuncu, M. R., Hu, D., Ge, M., Buckner, R. L., & Liu, H. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1317424111 · Cited by 281 · see citing works
Self-citationChanges in the interaction of resting-state neural networks from adolescence to adulthood
Stevens, M. C., Pearlson, G. D., & Calhoun, V. D. (2009) · Human Brain Mapping · doi:10.1002/hbm.20673 · Cited by 256 · see citing works
Frequency‐specific alternations in the amplitude of low‐frequency fluctuations in schizophrenia
Yu, R., Chien, Y., Wang, H. S., Liu, C., Liu, C., Hwang, T., Hsieh, M. H., Hwu, H., & Tseng, W. I. (2012) · Human Brain Mapping · doi:10.1002/hbm.22203 · Cited by 230 · see citing works
Tracking the Brain's Functional Coupling Dynamics over Development
Hutchison, R. M., & Morton, J. B. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4638-14.2015 · Cited by 214 · see citing works
Spatiotemporal Dependency of Age-Related Changes in Brain Signal Variability
McIntosh, A. R., Vakorin, V. A., Kovacevic, N., Wang, H., Diaconescu, A. O., & Protzner, A. B. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht030 · Cited by 206 · see citing works
Cingulate Activation Increases Dynamically with Response Speed under Stimulus Unpredictability
Hahn, B., Ross, T. J., & Stein, E. A. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhl075 · Cited by 203 · see citing works
Meier, T. B., Desphande, A. S., Vergun, S., Nair, V. A., Song, J., Biswal, B. B., Meyerand, M. E., Birn, R. M., & Prabhakaran, V. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.12.052 · Cited by 182 · see citing works
Challis, E., Hurley, P. D., Serra, L., Bozzali, M., Oliver, S., & Cercignani, M. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.037 · Cited by 179 · see citing works
Network structure shapes spontaneous functional connectivity dynamics
Shen, K., Hutchison, R. M., Bezgin, G., Everling, S., & McIntosh, A. R. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.4903-14.2015 · Cited by 171 · see citing works
Vakorin, V. A., Lippé, S., & McIntosh, A. R. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.3153-10.2011 · Cited by 171 · see citing works
Quantifying Head Motion Associated with Motor Tasks Used in fMRI
Seto, E., Gal Sela, D., McIlroy, W. E., Black, S. E., Staines, R. W., Bronskill, M. J., McIntosh, A. R., & Graham, S. J. (2001) · NeuroImage · doi:10.1006/nimg.2001.0829 · Cited by 170 · see citing works
Networks of task co-activations
Laird, A. R., Eickhoff, S. B., Rottschy, C., Bzdok, D., Ray, K. L., & Fox, P. T. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.073 · Cited by 168 · see citing works
Dynamic functional connectivity
Ioannides, A. A. (2007) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2007.03.008 · Cited by 152 · see citing works
Brain Noise Is Task Dependent and Region Specific
Mišić, B., Mills, T., Taylor, M. J., & McIntosh, A. R. (2010) · Journal of Neurophysiology · doi:10.1152/jn.00648.2010 · Cited by 151 · see citing works
Default-mode function and task-induced deactivation have overlapping brain substrates in children
Thomason, M. E., Chang, C. E., Glover, G. H., Gabrieli, J. D. E., Greicius, M. D., & Gotlib, I. H. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.029 · Cited by 142 · see citing works
Wang, L.-B., Shen, H., Tang, F., Zang, Y., & Hu, D. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.080 · Cited by 117 · see citing works
Self-citationDecoding lifespan changes of the human brain using resting-state functional connectivity MRI
Wang, L., Su, L., Shen, H., & Hu, D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0044530 · Cited by 115 · see citing works
Self-citationDynamic Coordination in the Brain
(2010) · The MIT Press eBooks · doi:10.7551/mitpress/9780262014717.001.0001 · Cited by 109 · see citing works
Yang, Z., Craddock, R. C., Margulies, D. S., Yan, C., & Milham, M. P. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.02.014 · Cited by 100 · see citing works
Age effects on the default mode and control networks in typically developing children
Sato, J. R., Salum, G. A., Gadelha, A., Picon, F. A., Pan, P. M., Vieira, G., Zugman, A., Hoexter, M. Q., Anés, M., Moura, L. M., et al. (2014) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2014.07.004 · Cited by 85 · see citing works
Spatial frequency processing in scene-selective cortical regions
Kauffmann, L., Ramanoël, S., Guyader, N., Chauvin, A., & Peyrin, C. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.058 · Cited by 68 · see citing works
Oler, J. A., Birn, R. M., Patriat, R., Fox, A. S., Shelton, S. E., Burghy, C. A., Stodola, D. E., Essex, M. J., Davidson, R. J., & Kalin, N. H. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.045 · Cited by 67 · see citing works
Hunyadi, B., Tousseyn, S., Dupont, P. J., Huffel, S. V., Vos, M. D., & Paesschen, W. V. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.03.011 · Cited by 37 · see citing works
Shen, H., Li, Z., Zeng, L., Yuan, L., Chen, F., Liu, Z., & Hu, D. (2014) · Neuroreport · doi:10.1097/wnr.0000000000000267 · Cited by 24 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
The dynamic functional connectome: State-of-the-art and perspectives
Preti, M. G., Bolton, T. A. W., & Ville, D. V. D. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.061 · Cited by 1,425 · see citing works
Grayson, D. S., & Fair, D. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.079 · Cited by 411 · see citing works
“Over development, rs-fcMRI networks show increased within-subject variability (Hutchison and Morton, 2015; Marusak et al., 2016; Qin et al., 2015), consistent with EEG studies showing that signal complexity increases over development (McIntosh et al., 2008; Vakorin et al., 2011).”
BackgroundNorthoff, G., & Lamme, V. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.07.019 · Cited by 247 · see citing works
Dynamic functional connectivity of neurocognitive networks in children
Marusak, H. A., Calhoun, V. D., Brown, S., Crespo, L. M., Sala‐Hamrick, K., Gotlib, I. H., & Thomason, M. E. (2016) · Human Brain Mapping · doi:10.1002/hbm.23346 · Cited by 237 · see citing works
Zhang, C., Dougherty, C. C., Baum, S. A., White, T. J. H., & Michael, A. M. (2018) · Human Brain Mapping · doi:10.1002/hbm.23950 · Cited by 217 · see citing works
Liu, J., Liao, X., Xia, M., & Yong He, A. (2017) · Human Brain Mapping · doi:10.1002/hbm.23890 · Cited by 205 · see citing works
Deery, H. A., Paolo, R. D., Moran, C., Egan, G. F., & Jamadar, S. D. (2022) · Psychophysiology · doi:10.1111/psyp.14159 · Cited by 167 · see citing works
Fong, A. H. C., Yoo, K., Rosenberg, M. D., Zhang, S., Li, C.-S. R., Scheinost, D., Constable, R. T., & Chun, M. M. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.11.057 · Cited by 159 · see citing works
Tools of the trade: estimating time-varying connectivity patterns from fMRI data
Iraji, A., Faghiri, A., Lewis, N., Fu, Z., Rachakonda, S., & Calhoun, V. D. (2020) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsaa114 · Cited by 152 · see citing works
Predicting Age From Brain EEG Signals—A Machine Learning Approach
Zoubi, O. A., Wong, C. K., Kuplicki, R., Yeh, H., Mayeli, A., Refai, H. H., Paulus, M. P., & Bodurka, J. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00184 · Cited by 156 · see citing works
Toward Developmental Connectomics of the Human Brain
Cao, M., Huang, H., Peng, Y., Dong, Q., & Yong He, A. (2016) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2016.00025 · Cited by 147 · see citing works
Stevens, M. C. G. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.07.027 · Cited by 138 · see citing works
Meng, X., Jiang, R., Lin, D., Bustillo, J., Jones, T., Chen, J., Yu, Q., Du, Y., Zhang, Y., Jiang, T., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.026 · Cited by 106 · see citing works
Battaglia, D. A., Boudou, T., Hansen, E. C. A., Lombardo, D., Chettouf, S., Daffertshofer, A., McIntosh, A. R., Zimmermann, J., Ritter, P., & Jirsa, V. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117156 · Cited by 98 · see citing works
Brain Dynamics Underlying Cognitive Flexibility Across the Lifespan
Kupis, L. B., Goodman, Z. T., Kornfeld, S., Hoang, S., Romero, C., Dirks, B., Dehoney, J., Chang, C. E., Spreng, R. N., Nomi, J. S., et al. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab156 · Cited by 103 · see citing works
He, C., Chen, Y., Jian, T., Chen, H., Guo, X., Wang, J., Wu, L., Chen, H., & Duan, X. (2018) · Autism Research · doi:10.1002/aur.2020 · Cited by 102 · see citing works
Accelerated functional brain aging in pre-clinical familial Alzheimer’s disease
Gonneaud, J., Baria, A. T., Binette, A. P., Gordon, B. A., Chhatwal, J. P., Cruchaga, C., Jucker, M., Levin, J., Salloway, S., Farlow, M. R., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25492-9 · Cited by 109 · see citing works
Changing brain connectivity dynamics: From early childhood to adulthood
Faghiri, A., Stephen, J. M., Wang, Y., Wilson, T. W., & Calhoun, V. D. (2017) · Human Brain Mapping · doi:10.1002/hbm.23896 · Cited by 97 · see citing works
Predicting age from cortical structure across the lifespan
Madan, C. R., & Kensinger, E. A. (2018) · European Journal of Neuroscience · doi:10.1111/ejn.13835 · Cited by 91 · see citing works
Naik, S., Banerjee, A., Bapi, R. S., Deco, G., & Roy, D. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.04.007 · Cited by 89 · see citing works
Neuronal Cascades Shape Whole-Brain Functional Dynamics at Rest
Rabuffo, G., Fousek, J., Bernard, C., & Jirsa, V. (2021) · eNeuro · doi:10.1523/eneuro.0283-21.2021 · Cited by 83 · see citing works
Test-retest reliability of dynamic functional connectivity in resting state fMRI
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 82 · see citing works
Estimating dynamic functional brain connectivity with a sparse hidden Markov model
Zhang, G.-M., Cai, B., Zhang, A.-Y., Stephen, J., Wilson, T., Calhoun, V., & Wang, Y.-P. (2019) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2019.2929959 · Cited by 64 · see citing works
Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan
Davison, E. N., Turner, B. O., Schlesinger, K. J., Miller, M. B., Grafton, S. T., Bassett, D. S., & Carlson, J. M. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005178 · Cited by 55 · see citing works
Estimation of dynamic sparse connectivity patterns from resting state fMRI
Cai, B., Zille, P., Stephen, J., Wilson, T., Calhoun, V., & Wang, Y.-P. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2017.2786553 · Cited by 52 · see citing works
González-Castillo, J., Caballero‐Gaudes, C., Topolski, N., Handwerker, D. A., Pereira, F., & Bandettini, P. A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116129 · Cited by 54 · see citing works
Abnormal dynamic properties of functional connectivity in disorders of consciousness
Cao, B., Chen, Y., Yu, R., Chen, L., Chen, P., Weng, Y., Chen, Q., Song, J., Xie, Q., & Huang, R. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.102071 · Cited by 55 · see citing works
Fan, L., Su, J., Qin, J., Hu, D., & Shen, H. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00881 · Cited by 58 · see citing works
Self-citationA Novel Individual Metabolic Brain Network for 18F-FDG PET Imaging
Huang, S., Hsu, J., Lin, K., & Hsiao, I. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00344 · Cited by 53 · see citing works
Neural and metabolic basis of dynamic resting state fMRI
Thompson, G. J. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.09.010 · Cited by 52 · see citing works
Age-Related Decline in the Variation of Dynamic Functional Connectivity: A Resting State Analysis
Chen, Y., Wang, W., Zhao, X. W., Sha, M., Liu, Y., Zhang, X., Ma, J., Ni, H., & Ming, D. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00203 · Cited by 49 · see citing works
Wang, X., Jiao, Y., & Li, L. (2018) · Scientific Reports · doi:10.1038/s41598-018-30308-w · Cited by 48 · see citing works
Age-dependent changes in task-based modular organization of the human brain
Schlesinger, K. J., Turner, B. O., Lopez, B. A., Miller, M. B., & Carlson, J. M. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.001 · Cited by 42 · see citing works
Valsasina, P., de la Cruz, M. H., Filippi, M., & Rocca, M. A. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00618 · Cited by 42 · see citing works
Developmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence
López-Vicente, M., Agcaoglu, O., Pérez‐Crespo, L., Estévez‐López, F., Heredia‐Genestar, J. M., Mulder, R. H., Flournoy, J. C., van Duijvenvoorde, A. C. K., Güroğlu, B., White, T. J. H., et al. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.724805 · Cited by 44 · see citing works
Mining Time-Resolved Functional Brain Graphs to an EEG-Based Chronnectomic Brain Aged Index (CBAI)
Dimitriadis, S. I., & Salis, C. I. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00423 · Cited by 40 · see citing works
Joint embedding: A scalable alignment to compare individuals in a connectivity space
Nenning, K., Xu, T., Schwartz, E., Arroyo, J., Wöehrer, A., Franco, A. R., Vogelstein, J. T., Margulies, D. S., Liu, H., Smallwood, J., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117232 · Cited by 40 · see citing works
Corps, J., & Rekik, I. (2019) · Scientific Reports · doi:10.1038/s41598-019-46145-4 · Cited by 38 · see citing works
Long, Y., Liu, X., & Liu, Z. (2023) · Brain Sciences · doi:10.3390/brainsci13030429 · Cited by 36 · see citing works
Progressive Stabilization of Brain Network Dynamics during Childhood and Adolescence
Lei, T., Liao, X., Chen, X., Zhao, T., Xu, Y., Xia, M., Zhang, J., Xia, Y., Sun, X., Wei, Y., et al. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab263 · Cited by 36 · see citing works
Self-citationChiang, S., Vankov, E. R., Yeh, H. J., Guindani, M., Vannucci, M., Haneef, Z., & Stern, J. M. (2018) · PLoS ONE · doi:10.1371/journal.pone.0190220 · Cited by 35 · see citing works
Long, Y., Ouyang, X., Yan, C., Wu, Z., Huang, X., Pu, W., Cao, H., Liu, Z., & Palaniyappan, L. K. (2023) · Human Brain Mapping · doi:10.1002/hbm.26202 · Cited by 32 · see citing works
Refined measure of functional connectomes for improved identifiability and prediction
Cai, B., Zhang, G.-M., Hu, W.-X., Zhang, A.-Y., Zille, P., Zhang, Y., Stephen, J., Wilson, T., Calhoun, V., & Wang, Y.-P. (2019) · Human Brain Mapping · doi:10.1002/hbm.24741 · Cited by 28 · see citing works
Zöller, D., Bolton, T. A. W., Karahanoğlu, F. I., D, S. E. M., Schaer, M., & Ville, D. V. D. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2863944 · Cited by 31 · see citing works
Distinct networks of periaqueductal gray columns in pain and threat processing
Wang, S., Veinot, J., Goyal, A., Khatibi, A., Lazar, S. W., & Hashmi, J. A. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.118936 · Cited by 30 · see citing works
The brain's functional connectome in young children with prenatal alcohol exposure
Long, X., Kar, P., Gibbard, B., Tortorelli, C., & Lebel, C. A. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.102082 · Cited by 27 · see citing works
Modeling early phenotypes of Parkinson’s disease by age-induced midbrain-striatum assembloids
Barmpa, K., Saraiva, C., Lopez‐Pigozzi, D., Gomez‐Giro, G., Gabassi, E., Spitz, S., Brandauer, K., Rodriguez-Gatica, J. E., Antony, P. M. A., Robertson, G., et al. (2024) · Communications Biology · doi:10.1038/s42003-024-07273-4 · Cited by 30 · see citing works
Age-related early/late variations of functional connectivity across the human lifespan
Chen, Y., Zhao, X. W., Zhang, X., Liu, Y., Zhou, P., Ni, H., Ma, J., & Ming, D. (2018) · Neuroradiology · doi:10.1007/s00234-017-1973-1 · Cited by 25 · see citing works
Fan, L., Zhong, Q., Qin, J., Li, N., Su, J., Zeng, L., Hu, D., & Shen, H. (2020) · Human Brain Mapping · doi:10.1002/hbm.25303 · Cited by 26 · see citing works
Self-citationWei, Y., Zhang, W., Li, Y., Liu, X., Zha, B., Hu, S., Wang, Y., Wang, X., Yu, X.-C., Yang, J., et al. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.737993 · Cited by 23 · see citing works
Huang, J., Ke, P., Chen, X., Li, S., Zhou, J., Xiong, D., Huang, Y., Li, H., Ning, Y., Duan, X., et al. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.823502 · Cited by 23 · see citing works
Self-citationLou, W., Wang, D., Wong, A., Chu, C. W., Mok, V., & Shi, L. (2018) · Human Brain Mapping · doi:10.1002/hbm.24376 · Cited by 22 · see citing works
Development of Dynamic Functional Architecture during Early Infancy
Wen, X., Wang, R., Yin, W., Lin, W., Zhang, H., & Shen, D. G. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa128 · Cited by 22 · see citing works
The Transitions Between Dynamic Micro-States Reveal Age-Related Functional Network Reorganization
Chen, Y., Liu, Y., Zhou, P., Zhang, X., Wu, Q., Zhao, X. W., & Ming, D. (2019) · Frontiers in Physiology · doi:10.3389/fphys.2018.01852 · Cited by 22 · see citing works
White matter substrates of functional connectivity dynamics in the human brain
Basile, G. A., Bertino, S., Nozais, V., Bramanti, A., Ciurleo, R., Anastasi, G., Milardi, D., & Cacciola, A. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119391 · Cited by 21 · see citing works
Parcellating the human brain using resting-state dynamic functional connectivity
Peng, L., Luo, Z., Zeng, L., Hou, C., Shen, H., Zhou, Z., & Hu, D. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac293 · Cited by 22 · see citing works
Self-citationSchlemm, E., Frey, B. M., Mayer, C., Petersen, M., Fiehler, J., Hanning, U. M. P., Kühn, S., Twerenbold, R., Gallinat, J., Gerloff, C. P., et al. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.03.019 · Cited by 20 · see citing works
Shen, H., Xu, H., Wang, L., Lei, Y., Yang, L., Zhang, P., Qin, J., Zeng, L., Zhou, Z., Zheng, Y., et al. (2017) · Human Brain Mapping · doi:10.1002/hbm.23693 · Cited by 20 · see citing works
Self-citationTang, S., Wu, Z., Cao, H., Chen, X., Wu, G., Tan, W., Liu, D., Yang, J., Long, Y., & Liu, Z. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.809853 · Cited by 19 · see citing works
Self-citationJusseaume, K., & Valova, I. (2022) · Sensors · doi:10.3390/s22218112 · Cited by 19 · see citing works
Arbabyazd, L., Petkoski, S., Breakspear, M. J., Solodkin, A., Battaglia, D. A., & Jirsa, V. (2023) · Network Neuroscience · doi:10.1162/netn_a_00332 · Cited by 19 · see citing works
A GICA-TVGL Framework to Study Sex Differences in Resting State fMRI Dynamic Connectivity
Cai, B., Zhang, G.-M., Zhang, A.-Y., Hu, W.-X., Stephen, J., Wilson, T., Calhoun, V., & Wang, Y.-P. (2019) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2019.108531 · Cited by 14 · see citing works
Mapping efficacious deep brain stimulation for pediatric dystonia
Coblentz, A. C., Elias, G. J. B., Boutet, A., Germann, J., Algarni, M., de Oliveira, L. M., Neudorfer, C., Widjaja, E., Ibrahim, G. M., Kalia, S. K., et al. (2021) · Journal of Neurosurgery Pediatrics · doi:10.3171/2020.7.peds20322 · Cited by 19 · see citing works
Zhong, S., Chen, P., Lai, S., Chen, G., Zhang, Y., Lv, S., He, J., Tang, G., Pan, Y., Wang, Y., et al. (2022) · Journal of Affective Disorders · doi:10.1016/j.jad.2022.09.050 · Cited by 16 · see citing works
Wu, K., Jelfs, B., Neville, K. L., Cai, A., & Fang, Q. (2024) · IEEE Access · doi:10.1109/access.2024.3445580 · Cited by 16 · see citing works
Decision Tree in Working Memory Task Effectively Characterizes EEG Signals in Healthy Aging Adults
Javaid, H., Manor, R., Kumarnsit, E., & Chatpun, S. (2021) · IRBM · doi:10.1016/j.irbm.2021.12.001 · Cited by 16 · see citing works
Kozhemiako, N., Buckley, A. W., Chervin, R. D., Redline, S. S., & Purcell, S. (2023) · NeuroImage Clinical · doi:10.1016/j.nicl.2023.103552 · Cited by 16 · see citing works
Abrol, A., Fu, Z., Du, Y., Wilson, T. W., Wang, Y., Stephen, J. M., & Calhoun, V. D. (2023) · Human Brain Mapping · doi:10.1002/hbm.26200 · Cited by 13 · see citing works
Hu, J., Luo, J., Xu, Z., Liao, B., Dong, S., Peng, B., & Hou, G. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.08.014 · Cited by 12 · see citing works
Resting-state dynamic functional connectivity predicts the psychosocial stress response
Liu, Y., Ren, X., Zeng, M., Li, J., Zhao, X., Zhang, X., & Yang, J. (2021) · Behavioural Brain Research · doi:10.1016/j.bbr.2021.113618 · Cited by 12 · see citing works
Battaglia, D. A., Boudou, T., Hansen, E. C. A., Lombardo, D., Chettouf, S., Daffertshofer, A., McIntosh, A. R., Zimmermann, J., Ritter, P., & Jirsa, V. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/107243 · Cited by 13 · see citing works
Dimitriadis, S. I., Simos, P. G., Fletcher, J. M., & Papanicolaou, A. C. (2019) · Brain Sciences · doi:10.3390/brainsci9120380 · Cited by 10 · see citing works
Metastability of cortical BOLD signals in maturation and senescence
Naik, S., Subbareddy, O., Banerjee, A., Roy, D., & Bapi, R. S. (2017) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2017.7966435 · Cited by 10 · see citing works
Zhou, J., Chen, Y., Jin, X., Mao, W., Xiao, Z., Zhang, S., Zhang, T., Liu, T., Kendrick, K. M., & Jiang, X. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106592 · Cited by 9 · see citing works
Basile, G. A., Quartarone, A., Cerasa, A., Ielo, A., Bonanno, L., Bertino, S., Rizzo, G., Milardi, D., Anastasi, G., Saranathan, M., et al. (2024) · Human Brain Mapping · doi:10.1002/hbm.70062 · Cited by 8 · see citing works
Dynamic visual cortical connectivity analysis based on functional magnetic resonance imaging
Zhao, L., Zeng, W., Shi, Y., Nie, W., & Yang, J. (2020) · Brain and Behavior · doi:10.1002/brb3.1698 · Cited by 9 · see citing works
Transformer3: A Pure Transformer Framework for fMRI-Based Representations of Human Brain Function
Xiao-xi, T., Ma, H., Guan, Y., Xu, L., Liu, J., & Tian, L. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3471186 · Cited by 8 · see citing works
Introducing an adolescent cognitive maturity index
Damaty, S. E., Darcey, V. L., McQuaid, G. A., Picci, G., Stoianova, M., Mucciarone, V., Chun, Y., Laws, M. L., Campano, V., Hecke, K. V., et al. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1017317 · Cited by 8 · see citing works
Ramos‐Loyo, J., Olguín-Rodríguez, P. V., Espinosa-Denenea, S. E., Llamas-Alonso, L. A., Rivera-Tello, S., & Müller, M. (2022) · Frontiers in Network Physiology · doi:10.3389/fnetp.2022.890906 · Cited by 8 · see citing works
Dall’Aglio, L., Estévez‐López, F., López-Vicente, M., Xu, B., Agcaoglu, O., Boroda, E., Lim, K. O., Calhoun, V. D., Tiemeier, H. W., & Muetzel, R. L. (2023) · NeuroImage Clinical · doi:10.1016/j.nicl.2023.103382 · Cited by 6 · see citing works
Gao, X., & Xu, Y. (2025) · Japanese Journal of Radiology · doi:10.1007/s11604-025-01832-3 · Cited by 5 · see citing works
Fan, L., Xu, H., Su, J., Qin, J., Gao, K., Ou, M., Peng, S., Shen, H., & Li, N. (2021) · Brain and Behavior · doi:10.1002/brb3.2414 · Cited by 4 · see citing works
Self-citationAge-induced midbrain-striatum assembloids model early phenotypes of Parkinson’s diseasePreprint
Barmpa, K., Saraiva, C., Gomez‐Giro, G., Gabassi, E., Spitz, S., Brandauer, K., Rodriguez-Gatica, J. E., Antony, P. M. A., Robertson, G., Papastefanaki, F., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.28.564305 · Cited by 5 · see citing works
Duffy, K. A., Wiglesworth, A., Roediger, D. J., Island, E., Mueller, B. A., Luciana, M. M., Klimes‐Dougan, B., Cullen, K. R., & Fiecas, M. J. A. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121238 · Cited by 4 · see citing works
Goallec, A. L., Diai, S., Collin, S., Vincent, T., & Patel, C. J. (2021) · medRxiv · doi:10.1101/2021.06.22.21259280 · Cited by 4 · see citing works
Hu, P., Wang, P., Zhao, R., Yang, H., & Biswal, B. B. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1248610 · Cited by 3 · see citing works
Bezmaternykh, D. D., Мельников, М. Е., Петровский, Е. Д., Kozlova, L. I., Stark, M. B., Savelov, A. A., Шубина, О. С., & Natarova, K. A. (2018) · Bulletin of Experimental Biology and Medicine · doi:10.1007/s10517-018-4185-8 · Cited by 3 · see citing works
Li, Y., Zeng, W., Shi, Y., Deng, J., Nie, W., Luo, S., & Yang, J. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.756938 · Cited by 3 · see citing works
Yoshimoto, T., Tokunaga, K., & Chikazoe, J. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120911 · Cited by 3 · see citing works
Minowa, Y., Onoda, K., Takamura, M., Yamaguchi, S., Okamoto, N., & Akama, H. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.14.503923 · Cited by 3 · see citing works
Mapping Typical and Altered Neurodevelopment with Sleep Macro- and Micro-ArchitecturePreprint
Kozhemiako, N., Buckley, A. W., Chervin, R. D., Redline, S. S., & Purcell, S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.15.520643 · Cited by 3 · see citing works
Gregorich, M., Simpson, S. L., & Heinze, G. (2024) · Statistics in Medicine · doi:10.1002/sim.10091 · Cited by 2 · see citing works
Huang, Z., & Yin, D. (2025) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2025.101528 · Cited by 2 · see citing works
Supervised Multidimensional Scaling and its Application in MRI-Based Individual Age Predictions
Cao, X., Chen, C., & Tian, L. (2020) · Neuroinformatics · doi:10.1007/s12021-020-09476-6 · Cited by 2 · see citing works
Cognitive and Psychiatric Relevance of Dynamic Functional Connectivity States in ChildrenPreprint
Fu, Z., Jing Sui （Beijing Normal University）， my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Iraji, A., Liu, J., & Calhoun, V. D. (2023) · Research Square · doi:10.21203/rs.3.rs-1964400/v2 · Cited by 2 · see citing works
Measuring functional connectivity in frequency‐domain helps to better characterize brain function
Peng, L., Su, J., Hu, D., Yu, Y., Wei, H., & Li, M. (2024) · Human Brain Mapping · doi:10.1002/hbm.26726 · Cited by 1 · see citing works
Self-citationCognition and brain network connectivity in timed up & go performance
Varela‐López, B., Galdo‐Álvarez, S., Felpete, A., Habeck, C. G., Stern, Y., & Facal-Mayo, D. (2025) · GeroScience · doi:10.1007/s11357-025-02016-7 · Cited by 1 · see citing works
Dynamic Resting-State Network Markers of Disruptive Behavior Problems in Youth
Shappell, H. M., Liu, Z., Khodaei, M., He, G. S., Gee, D. G., Lindquist, M. A., Sukhodolsky, D. G., McCarthy, G., & Ibrahim, K. (2026) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2026.100689 · Cited by 2 · see citing works
Markovics, J. A. (2021) · Artificial intelligence · doi:10.5772/intechopen.98343 · Cited by 1 · see citing works
Dynamic functional connectivity
França, L. G. S., Fenn‐Moltu, S., & Batallé, D. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-85280-7.00006-3 · Cited by 1 · see citing works
- Authors
- Qin, J., Chen, S.-G., Hu, D., Zeng, L.-L., Fan, Y.-M., Chen, X.-P., & Shen, H.
- Affiliations
- National University of Defense Technology (CN)
- Corresponding author
- Shen, Hui
- Venue
- Frontiers in Human Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2015-07-16
- Volume
- 9
- Pages
- 418-418
- ISSN
- 1662-5161 (ISSN-L)
- PMC
- PMC4503925
- OpenAlex
- W1587698431
- Cited by
- 117
- References
- 73
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 10 · 2023: 11 · 2022: 17 · 2021: 16 · 2020: 12 · 2019: 12 · 2018: 12 · 2017: 11 · 2016: 8
- FWCI
- 6.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Human Neuroscience (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Key Laboratory of Human Factors Engineering
- National Natural Science Foundation of China (2013CB329401, 61375034, 61375111)
- National Key Research and Development Program of China (61375034, 61375111, 2013CB329401)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- dynamic functional connectivity, brain maturation, developmental trajectories, individual differences, default mode network, cerebellum, visual network, cingulo-opercular network, resting-state functional connectivity
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
