Abstract Number:
3555
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
Bonnie Smith (1), Brian Caffo (2), Yi Zhao (3), Martin Lindquist (2)
Institutions:
(1) Johns Hopkins University, School of Public Health, N/A, (2) Johns Hopkins University, N/A, (3) Indiana University, N/A
Co-Author(s):
First Author:
Bonnie Smith
Johns Hopkins University, School of Public Health
Presenting Author:
Bonnie Smith
Johns Hopkins University, School of Public Health
Abstract Text:
We propose analyses of resting-state fMRI data that use partial location information of regions of interest (ROIs). In particular we consider subject-level regression models to explain intra-subject variability in brain functional connectivity and summarize connectivity parsimoniously, and we investigate approaches based on distributions of connectivity values. We apply our approach to Human Connectome Project data.
Keywords:
fMRI|connectivity|connectomics| | |
Sponsors:
Section on Statistics in Imaging
Tracks:
fMRI
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