Hubness maps resulting from TED

The program vhubness produces a hubness map resulting from the output of vted. A voxel in the hubness map records the number of edges for which this voxel serves as an endpoint. Voxels in which many edges accumulate may be viewed as hubs in a task-specific network, and the number of edges meeting in a voxel is a measure of the voxel’s hubness.

The details of the algorithm are described in Lohmann et al (2016) (see reference below).

An example calling sequence is shown below:

Example:

vted -in1 A*.v -in2 B*.v -mask mask.v -perm   0 -q 0.99 -hist realhist.txt -out edgelist.v
vted -in1 A*.v -in2 B*.v -mask mask.v -perm 100 -q 0.99 -hist nullhist.txt
vtedfdr -real realhist.txt -null nullhist.txt -out fdr.txt -alpha 0.05
vhubness -in edgelist.v -out image.v -min 0.3

The first call produces a list of candidate voxel pairs and stores them in the file “edgelist.v”. It also produces a histogram file “realhist.txt” which is later used for statistical inference. The second call produces a null distribution which is obtained using 200 random permutations. It yields a histogram file “nullhist.txt”. The third call to ‘vtedfdr’ uses the two histogram files as input and produces the txt-file “fdr.txt” as output. The file “fdr.txt” can be used to determine a cutoff so that edges with edge densities that exceed this cutoff have a sufficiently low false discovery rate.

In our example, edge densities larger than 0.3 have a false discovery rate of less than 0.05. This cutoff is now used to produce a hubness map using the program ‘vhubness’. This voxel map highlights voxels that serve as an endpoint in at least one of the significant edges.

Reference: Lohmann G, Stelzer J, Zuber V, Buschmann T, Margulies D, et al. (2016): Task-Related Edge Density (TED) - A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain. PLoS ONE 11(6): e0158185. doi: 10.1371/journal.pone.0158185

Parameters of ‘vhubness’

-help

Prints usage information.

-in1

Input files 1.

-in2

Input files 2.

-out

Output file.

-mask

Region of interest mask.

-perm

Number of permutations. Default: 0

-qthreshold

Initial quantile threshold. Default: 0.99

-histogram

Output histogram filename.

-first

First timestep to use. Default: 0

-length

Length of time series to use, ‘0’ to use full length. Default: 0

-adj

Definition of adjacency [6 | 18 | 26]. Default: 26

-edgelength

Minimum edge length in voxels. Default: 5

-type

Type of metric [ SNR | median ]. Default: SNR

-metric

Correlation metric [ pearson | spearman ]. Default: pearson

-j

Number of processors to use, ‘0’ to use all. Default: 10