The chronnectome: Evaluating replicability of dynamic connectivity patterns in 7500 resting fMRI datasets

Anees Abrol, Charlotte Chaze, Eswar Damaraju, Vince Daniel Calhoun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Functional fMRI data are typically analyzed under the assumption that participants experience one long, continuous connectivity state throughout rest scan sessions. The chronnectome is a model that takes into account the temporal variance in connectivity throughout a scan session. In this work, we evaluate the repeatability of properties of functional network connectivity (FNC) dynamics assessed using sliding-windowed correlations in 28 independent age-matched large samples of 250 subjects. This approach revealed that multiple discrete, reoccurring connectivity states arise during rest, and that subjects tend to remain in one connectivity state for long periods of time before transitioning to another. Occurrence time spent in certain states tends to increase as participants spend more time resting, while less time is spent in other states as time goes on. Overall, results show distinct connectivity states that are similar across groups during rest.

Original languageEnglish (US)
Title of host publication2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5571-5574
Number of pages4
Volume2016-October
ISBN (Electronic)9781457702204
DOIs
StatePublished - Oct 13 2016
Externally publishedYes
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States
Duration: Aug 16 2016Aug 20 2016

Other

Other38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
CountryUnited States
CityOrlando
Period8/16/168/20/16

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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  • Cite this

    Abrol, A., Chaze, C., Damaraju, E., & Calhoun, V. D. (2016). The chronnectome: Evaluating replicability of dynamic connectivity patterns in 7500 resting fMRI datasets. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 (Vol. 2016-October, pp. 5571-5574). [7591989] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2016.7591989