The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Can brain state be manipulated to emphasize individual differences in functional connectivity?
Open accessAbstract
While neuroimaging studies typically collapse data from many subjects, brain functional organization varies between individuals, and characterizing this variability is crucial for relating brain activity to behavioral phenotypes. Rest has become the default state for probing individual differences, chiefly because it is easy to acquire and a supposed neutral backdrop. However, the assumption that rest is the optimal condition for individual differences research is largely untested. In fact, other brain states may afford a better ratio of within- to between-subject variability, facilitating biomarker discovery. Depending on the trait or behavior under study, certain tasks may bring out meaningful idiosyncrasies across subjects, essentially enhancing the individual signal in networks of interest beyond what can be measured at rest. Here, we review theoretical considerations and existing work on how brain state influences individual differences in functional connectivity, present some preliminary analyses of within- and between-subject variability across conditions using data from the Human Connectome Project, and outline questions for future study.
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Cites
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Self-citationIntersubject synchronization of cortical activity during natural vision
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Cited by
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Ten simple rules for predictive modeling of individual differences in neuroimaging
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Connectome-based prediction of cocaine abstinence
Yip, S. W., Scheinost, D., Potenza, M. N., & Carroll, K. M. (2019) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2018.17101147 · Cited by 196
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Metadata
- Authors
- Finn, E. S., Scheinost, D., Finn, D. M., Shen, X., Papademetris, X., & Constable, R. T.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2017-10
- Volume
- 160
- Pages
- 140-151
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2603091313
- Cited by
- 359
- References
- 21
- FWCI
- 17.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
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