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Can I read Functional Connectivity and Structural Covariance Between Regions of Interest Can Be Measured More Accurately Using Multivariate Distance Correlation on EtoBox?
Functional Connectivity and Structural Covariance Between Regions of Interest Can Be Measured More Accurately Using Multivariate Distance Correlation by Linda Geerligs; Richard N. Henson is a Neuroscience article available to read on EtoBox.
What is Functional Connectivity and Structural Covariance Between Regions of Interest Can Be Measured More Accurately Using Multivariate Distance Correlation about?
Studies of brain-wide functional connectivity or structural covariance typically use measures like the Pearson correlation coefficient, applied to data that have been averaged across voxels within regions of interest (ROIs). However, averaging across voxels may result in biased connectivity estimates when there is inhomogeneity within those ROIs, e.g., sub-regions that exhibit different patterns of functional connectivity or structural covariance. Here, we propose a new measure based on "distance correlation"; a test of multivariate dependence of high dimensional vectors, which allows for both linear and non-linear dependencies. We used simulations to show how distance correlation out-performs Pearson correlation in the face of inhomogeneous ROIs. To evaluate this new measure on real data, we use resting-state fMRI scans and T1 structural scans from 2 sessions on each of 214 participants from the Cambridge Centre for Ageing & Neuroscience (Cam-CAN) project. Pearson correlation and distance correlation showed similar average connectivity patterns, for both functional connectivity and structural covariance. Nevertheless, distance correlation was shown to be 1) more reliable across se
Who reads Functional Connectivity and Structural Covariance Between Regions of Interest Can Be Measured More Accurately Using Multivariate Distance Correlation?
It is typically read by researchers, students, and practitioners in Neuroscience.
- Author
- Linda Geerligs; Richard N. Henson
- Published
- 2016
- Language
- EN
- Field
- Neuroscience (Life Sciences)