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Partially Localized FMRI Connectivity Analyses

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):

Brian Caffo  
Johns Hopkins University
Yi Zhao  
Indiana University
Martin Lindquist  
Johns Hopkins University

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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I have read and understand that JSM participants must abide by the Participant Guidelines.

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