Bolton, T., Freitas, L., Jochaut, D., Giraud, A. L., & Van De Ville, D. (2020). Neural responses in autism during movie watching: inter-individual response variability co-varies with symptomatology. NeuroImage, 216, 116571. https://doi.org/10.1016/j.neuroimage.2020.116571

Article  PubMed  Google Scholar 

Bolton, T., Jochaut, D., Giraud, A. L., & Van De Ville, D. (2018). Brain dynamics in ASD during movie-watching show idiosyncratic functional integration and segregation. Human Brain Mapping, 39, 2391–2404. https://doi.org/10.1002/hbm.24009

Article  PubMed  PubMed Central  Google Scholar 

Chen, C., Cao, X., & Tian, L. (2019). Partial least squares regression performs well in MRI-based individualized estimations. Frontiers in Neuroscience, 13, 1282. https://doi.org/10.3389/fnins.2019.01282

Article  PubMed  PubMed Central  Google Scholar 

Cui, Z., & Gong, G. (2018). The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features. NeuroImage, 178, 622–637. https://doi.org/10.1016/j.neuroimage.2018.06.001

Article  PubMed  Google Scholar 

Eickhoff, S. B., Milham, M., & Vanderwal, T. (2020). Towards clinical applications of movie fMRI. NeuroImage, 217, 116860. https://doi.org/10.1016/j.neuroimage.2020.116860

Article  PubMed  Google Scholar 

Fiecas, M., Ombao, H., van Lunen, D., Baumgartner, R., Coimbra, A., & Feng, D. (2013). Quantifying temporal correlations: a test-retest evaluation of functional connectivity in resting-state fMRI. NeuroImage, 65, 231–241. https://doi.org/10.1016/j.neuroimage.2012.09.052

Article  PubMed  Google Scholar 

Gao, J., Chen, G., Wu, J., Wang, Y., Hu, Y., Xu, T., Zuo, X. N., & Yang, Z. (2020). Reliability map of individual differences reflected in inter-subject correlation in naturalistic imaging. NeuroImage, 223, 117277. https://doi.org/10.1016/j.neuroimage.2020.117277

Article  PubMed  Google Scholar 

Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., Wu-Minn, H. C. P., Consortium. (2013). The minimal preprocessing pipelines for the Human Connectome Project. NeuroImage, 80, 105–124. https://doi.org/10.1016/j.neuroimage.2013.04.127

Article  PubMed  Google Scholar 

Guo, C. C., Kurth, F., Zhou, J., Mayer, E. A., Eickhoff, S. B., Kramer, J. H., & Seeley, W. W. (2012). One-year test-retest reliability of intrinsic connectivity network fMRI in older adults. NeuroImage, 61, 1471–1483. https://doi.org/10.1016/j.neuroimage.2012.03.027

Article  PubMed  Google Scholar 

Hasson, U., Nir, Y., Levy, I., Fuhrmann, G., & Malach, R. (2004). Intersubject synchronization of cortical activity during natural vision. Science, 303, 1634–1640. https://doi.org/10.1126/science.1089506

Article  CAS  PubMed  Google Scholar 

Herbec, A., Kauppi, J. P., Jola, C., Tohka, J., & Pollick, F. E. (2015). Differences in fMRI intersubject correlation while viewing unedited and edited videos of dance performance. Cortex: A Journal Devoted to the Study of the Nervous System and Behavior, 71, 341–348. https://doi.org/10.1016/j.cortex.2015.06.026

Article  PubMed  Google Scholar 

Hlinka, J., Děchtěrenko, F., Rydlo, J., Androvičová, R., Vejmelka, M., Jajcay, L., Tintěra, J., Lukavský, J., & Horáček, J. (2022). The intra-session reliability of functional connectivity during naturalistic viewing conditions. Psychophysiology, e14075. https://doi.org/10.1111/psyp.14075.

Kim, D., Kay, K., Shulman, G. L., & Corbetta, M. (2018). A new modular brain organization of the BOLD signal during natural vision. Cerebral Cortex, 28, 3065–3081. https://doi.org/10.1093/cercor/bhx175

Article  PubMed  Google Scholar 

Nastase, S. A., Gazzola, V., Hasson, U., & Keysers, C. (2019). Measuring shared responses across subjects using intersubject correlation. Social Cognitive and Affective Neuroscience, 14, 667–685. https://doi.org/10.1093/scan/nsz037

Article  PubMed  PubMed Central  Google Scholar 

Noble, S., Scheinost, D., & Constable, R. T. (2019). A decade of test-retest reliability of functional connectivity: a systematic review and meta-analysis. NeuroImage, 203, 116157. https://doi.org/10.1016/j.neuroimage.2019.116157

Article  PubMed  Google Scholar 

Power, J. D., Cohen, A. L., Nelson, S. M., Wig, G. S., Barnes, K. A., Church, J. A., Vogel, A. C., Laumann, T. O., Miezin, F. M., Schlaggar, B. L., & Petersen, S. E. (2011). Functional network organization of the human brain. Neuron, 72, 665–678. https://doi.org/10.1016/j.neuron.2011.09.006

Article  CAS  PubMed  PubMed Central  Google Scholar 

Rosenthal, G., Tanzer, M., Simony, E., Hasson, U., Behrmann, M., & Avidan, G. (2017). Altered topology of neural circuits in congenital prosopagnosia. eLife, 6, e25069. https://doi.org/10.7554/eLife.25069

Article  PubMed  PubMed Central  Google Scholar 

Schwarz, A. J., & McGonigle, J. (2011). Negative edges and soft thresholding in complex network analysis of resting state functional connectivity data. NeuroImage, 55, 1132–1146. https://doi.org/10.1016/j.neuroimage.2010.12.047

Article  PubMed  Google Scholar 

Simony, E., & Chang, C. (2020). Analysis of stimulus-induced brain dynamics during naturalistic paradigms. NeuroImage, 216, 116461. https://doi.org/10.1016/j.neuroimage.2019.116461

Article  PubMed  Google Scholar 

Simony, E., Honey, C. J., Chen, J., Lositsky, O., Yeshurun, Y., Wiesel, A., & Hasson, U. (2016). Dynamic reconfiguration of the default mode network during narrative comprehension. Nature Communications, 7, 12141. https://doi.org/10.1038/ncomms12141

Article  CAS  PubMed  PubMed Central  Google Scholar 

Smith, S. M., Beckmann, C. F., Andersson, J., Auerbach, E. J., Bijsterbosch, J., Douaud, G., WU-Minn HCP Consortium. (2013). Resting-state fMRI in the human connectome project. NeuroImage, 80, 144–168. https://doi.org/10.1016/j.neuroimage.2013.05.039

Article  PubMed  Google Scholar 

Sonkusare, S., Breakspear, M., & Guo, C. (2019). Naturalistic stimuli in neuroscience: critically acclaimed. Trends in Cognitive Sciences, 23, 699–714. https://doi.org/10.1016/j.tics.2019.05.004

Article  PubMed  Google Scholar 

Tian, L., Ye, M., Chen, C., Cao, X., & Shen, T. (2021). Consistency of functional connectivity across different movies. NeuroImage, 233, 117926. https://doi.org/10.1016/j.neuroimage.2021.117926

Article  PubMed  Google Scholar 

Tian, L., Ma, L., Wang, L. (2016). Alterations of functional connectivities from early to middle adulthood: Clues from multivariate pattern analysis of resting-state fMRI data. NeuroImage, 129, 389-400.https://doi.org/10.1016/j.neuroimage.2016.01.039

Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E., Yacoub, E., Ugurbil, K., WU-Minn HCP Consortium. (2013). The WU-Minn human connectome project: an overview. NeuroImage, 80, 62–79. https://doi.org/10.1016/j.neuroimage.2013.05.041

Article  PubMed  Google Scholar 

Vanderwal, T., Eilbott, J., & Castellanos, F. X. (2019). Movies in the magnet: naturalistic paradigms in developmental functional neuroimaging. Developmental Cognitive Neuroscience, 36, 100600. https://doi.org/10.1016/j.dcn.2018.10.004

Article  PubMed  Google Scholar 

Wang, J., Ren, Y., Hu, X., Nguyen, V. T., Guo, L., Han, J., & Guo, C. C. (2017). Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms. Human Brain Mapping, 38, 2226–2241. https://doi.org/10.1002/hbm.23517

Article  PubMed  PubMed Central  Google Scholar 

Wang, J. H., Zuo, X. N., Gohel, S., Milham, M. P., Biswal, B. B., & He, Y. (2011). Graph theoretical analysis of functional brain networks: test-retest evaluation on short- and long-term resting-state functional MRI data. PLoS One, 6, e21976. https://doi.org/10.1371/journal.pone.0021976

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang, C., Dougherty, C. C., Baum, S. A., White, T., & Michael, A. M. (2018). Functional connectivity predicts gender: evidence for gender differences in resting brain connectivity. Human Brain Mapping, 39, 1765–1776. https://doi.org/10.1002/hbm.23950

Article  PubMed  PubMed Central  Google Scholar