The DOI matches its Crossref record; 89 of the 89 references it cites were found in a registry or an index.
Idiosynchrony: From shared responses to individual differences during naturalistic neuroimaging
Open accessAbstract
Two ongoing movements in human cognitive neuroscience have researchers shifting focus from group-level inferences to characterizing single subjects, and complementing tightly controlled tasks with rich, dynamic paradigms such as movies and stories. Yet relatively little work combines these two, perhaps because traditional analysis approaches for naturalistic imaging data are geared toward detecting shared responses rather than between-subject variability. Here, we review recent work using naturalistic stimuli to study individual differences, and advance a framework for detecting structure in idiosyncratic patterns of brain activity, or "idiosynchrony". Specifically, we outline the emerging technique of inter-subject representational similarity analysis (IS-RSA), including its theoretical motivation and an empirical demonstration of how it recovers brain-behavior relationships during movie watching using data from the Human Connectome Project. We also consider how stimulus choice may affect the individual signal and discuss areas for future research. We argue that naturalistic neuroimaging paradigms have the potential to reveal meaningful individual differences above and beyond those observed during traditional tasks or at rest.
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The WU-Minn Human Connectome Project: An overview
Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E. J., Yacoub, E., & Ugurbil, K. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.041 · Cited by 5,651
The minimal preprocessing pipelines for the Human Connectome Project
Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J. R., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.127 · Cited by 5,253
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Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity
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Self-citationThe Human Connectome Project: A data acquisition perspective
Van Essen, D. C., Ugurbil, K., Auerbach, E., Barch, D., Behrens, T. E. J., Bucholz, R., Chang, A., Chen, L., Corbetta, M., Curtiss, S. W., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.018 · Cited by 2,680
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The default mode network: where the idiosyncratic self meets the shared social world
Yeshurun, Y., Nguyen, M., & Hasson, U. (2021) · Nature Reviews Neuroscience · doi:10.1038/s41583-020-00420-w · Cited by 682
Multimodal EEG-fMRI: advancing insight into large-scale human brain dynamics
Chang, C., & Chen, J. E. (2021) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2021.100279 · Cited by 45
Leveraging shared connectivity to aggregate heterogeneous datasets into a common response space
Nastase, S. A., Liu, Y.-F., Hillman, H., Norman, K. A., & Hasson, U. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116865 · Cited by 42
van Baar, J. M., & FeldmanHall, O. (2022) · American Psychologist · doi:10.1037/amp0000814 · Cited by 38
Kim, J.-H., De Asis-Cruz, J., Cook, K. M., & Limperopoulos, C. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhac209 · Cited by 19
Metadata
- Authors
- Finn, E. S., Glerean, E., Khojandi, A. Y., Nielson, D., Molfese, P. J., Handwerker, D. A., & Bandettini, P. A.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 215
- Pages
- 116828
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W3015354840
- Cited by
- 269
- References
- 89
- FWCI
- 18.15
- Type
- journal article
- Language
- en
- Open access
- gold
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