Temporal Brain Networks

Temporal Brain Networks This dataset contains a collection of temporal brain networks. The networks are obtained from resting-state fMRI data of 1047 subjects from the Human Connectome Project (HCP). Pipeline The pipeline takes the blood oxygen level dependent signals from the fMRI scan for each voxel of the brain and processes them. The output is a temporal network that represents the activity between brain regions during the ~12 minutes of the scan. The pipeline parameters are as follows Window size: 60 seconds Window overlap: 30 seconds Tukey window parameters: 0 (rectangular window) Correlation: Pearson Atlas: Schaefer Temporal Networks Networks are undirected and weighted. The values of the diagonal are 1, because they correspond to the correlation of a brain region with itself. The number of nodes doesn't change over time, instead edges appear and disappear. Dataset structure The dataset is organized as follows: The file id_subjects.txt contains the list of subject IDs, which are a selection of the HCP dataset. Each folder contains a network for each subject in a .txt file. The networks are compressed into several .zip files of 1 Gb each to facilitate downloading. The first line of each .txt file contains the number of nodes and the number of snapshots of the network divided by a space. The following lines contain the list of edges of the network in the form i,j,t,w meaning that the edge between node i and node j at time t has weight w. Folder names don't exactly correspond to the node number of the network collected in them (neuroscience convention). The real number of nodes (which is given in the header of the .txt files) is the folder name plus 2, e.g. folder 100 contains networks with 102 nodes. Acknowledgments Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. The authors are grateful to the OPAL infrastructure from Université Côte d'Azur for providing resources and support. This work has been supported by the French government, through the UCA DS4H Investments in the Future project managed by the National Research Agency (ANR) with the reference number ANR-17-EURE-0004. References Woolrich MW, Ripley BD, Brady JM, and Smith SM. (2001). Temporal autocorrelation in univariate linear modelling of FMRI data. NeuroImage 14(6):1370-1386. Matthew F. Glasser, Stamatios N. Sotiropoulos, J. Anthony Wilson, Timothy S. Coalson, Bruce Fischl, Jesper L. Andersson, Junqian Xu, Saad Jbabdi, Matthew Webster, Jonathan R. Polimeni, David C. Van Essen, and Mark Jenkinson (2013). The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage 80: 105-124.