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Characterizing variation in the functional connectome: promise and pitfalls
Open accessAbstract
The functional MRI (fMRI) community has zealously embraced resting state or intrinsic functional connectivity approaches to mapping brain organization. Having demonstrated their utility for charting the large-scale functional architecture of the brain, the field is now leveraging task-independent methods for the investigation of phenotypic variation and the identification of biomarkers for clinical conditions. Enthusiasm aside, questions regarding the significance and validity of intrinsic brain phenomena remain. Here, we discuss these challenges and outline current developments that, in moving the field toward discovery science, permit a shift from cartography toward a mechanistic understanding of the neural bases of variation in cognition, emotion and behavior.
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Citations
Cites
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Cited by
Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity
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Self-citationYan, C.-G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R. C., Di Martino, A., Li, Q., Zuo, X.-N., Castellanos, F. X., & Milham, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.004 · Cited by 1,461
Self-citationOn the relationship between the “default mode network” and the “social brain
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Enhancing studies of the connectome in autism using the autism brain imaging data exchange II
Di Martino, A., O’Connor, D., Chen, B., Alaerts, K., Anderson, J. S., Assaf, M., Balsters, J. H., Baxter, L., Beggiato, A., Bernaerts, S., et al. (2017) · Scientific Data · doi:10.1038/sdata.2017.10 · Cited by 710
Self-citation
Metadata
- Authors
- Kelly, C., Biswal, B. B., Craddock, R. C., Castellanos, F. X., & Milham, M. P.
- Venue
- Trends in Cognitive Sciences
- Publisher
- Elsevier BV
- Published
- 2012-03
- Volume
- 16
- Issue
- 3
- Pages
- 181-188
- ISSN
- 1364-6613 (ISSN-L)
- OpenAlex
- W2044186073
- Cited by
- 257
- References
- 23
- FWCI
- 1.88
- Type
- journal article
- Language
- en
- Open access
- green
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