UMich.data: fMRI brain networks of the UMich dataset

In jesusdaniel/graphclass: Network classification

fMRI brain networks of the UMich dataset

Description

This dataset contains functional connectivity brain networks of 79 subjects and corresponding class labels indicating schizophrenia status (40 healthy controls and 39 schizophrenic subjects). The fMRI data used to obtain these networks were collected by Professor Stephen F. Taylor's lab at the University of Michigan.

Usage

data(UMich.data)

Format

UMich.data is a list with two elements

X.cobre

A matrix containing the upper triangular part of the networks in column major order and without the diagonal entries. The networks are composed of 264 nodes obtained from the Power parcellation \insertCitepower2011functionalgraphclass and 34716 different edges. Each row corresponds to a subject in the data, and the columns correspond to edges in the networks. The edge weights are the Fisher-transformed correlations between the fMRI time series of the nodes. Nuisance covariates like age, gender, motion (meanFD and meanFDquad) and handedness have been regressed out. For a description of the preprocessing steps to obtain the network edge weights, see \insertCiterelion2017network;textualgraphclass.

Y.cobre

Class labels of the subjects in the dataset. Y = 1 represents schizophrenia status.

References

\insertRef

relion2017networkgraphclass

\insertRef

power2011functionalgraphclass

Examples

data(UMich.data)
plot_adjmatrix(UMich.data$X.umich[1,])

jesusdaniel/graphclass documentation built on Aug. 10, 2022, 3:10 p.m.