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Activity Number: 285 - Statistical Inference for Probabilistic Graphical Models with Applications
Type: Invited
Date/Time: Wednesday, August 5, 2020 : 10:00 AM to 11:50 AM
Sponsor: ENAR
Abstract #309345
Title: Detecting Differences in Brain-Region Correlations Between Two Groups
Author(s): Yuval Benjamini* and Itamar Faran and Michael Peer and Shahar Arzy
Companies: Hebrew University of Jerusalem and Hebrew University of Jerusalem and Hebrew University of Jerusalem and Hebrew University of Jerusalem
Keywords: Resting-state fMRI; correlation matrix; functional-connectivity; Wishart

Resting state fMRI consists of continuous neural-activity recordings over a period of several minutes without structured experimental manipulation. These measurements are typically summarized into a correlation matrix between activity in p predetermined brain-regions (p between 90 and 500). Neurologists are interested in identifying localized differences in correlation across patient populations, e.g. disease versus control. However, running a univariate test for each region-pair separately requires strong multiplicity corrections, making it hard to detect differences. In this work, we reparametrize the matrix of differences between populations as p main effects representing change for each region and ~p^2/2 “interactions”. We propose a likelihood based method that accounts for the dependence between the parameters, between correlation coefficients, and within the time-series. Adjusted intervals are derived for the main effects and for the second-order effects that are selected. In simulations we show that our method increases power to detect changes. In examples, we detect regions of difference in Amnesia patients compared to healthy controls.

Authors who are presenting talks have a * after their name.

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