Brain networks

Human brain datasets

(A) Human dual task datasets

Human dual task datasets (networks data, ATTENTION! Large file: 2.2 Gb)

Complete human dual task datasets (7 Gb) including all experiments with activity (phase and amplitude, see Sigman paper below for details) of each voxel, code to read the data, spatial coordinates of the nodes, and activity mask used to filter the data.

The compressed file contains 64 directories. The naming conventions are as follows: Each of the 64 directories is named phaseXXsY , where XX is a number from 01 to 16 and Y is a number between 1 and 4. XX corresponds to each one of the 16 individuals that participated in the study. Each participant went through 4 different experimental conditions (SOA), which are given by the number Y. Within each directory there are roughly 40 files, named phaseXXsY.t00TT.ascii. Each file corresponds to one full brain scan, XX and Y are the same as above, and TT represents the corresponding trial for each subject. Every file has 216,464 numbers. The numbers range from 0 to 2*\pi and correspond to the phase of each voxel. The phase is a measure of the activity in each voxel. For a detailed description of the procedure please see:

Brain Mechanisms of Serial and Parallel Processing during Dual-Task Performance, by Mariano Sigman and Stanislas Dehaene.

Parsing a sequence of brain activations at psychological times using fMRI, by M. Sigman, A. Jobert, D. LeBihan, and S. Dehaene.

Analysis of the dataset using complex networks tools and a simplified, although complete, explanation of the dataset, see the Methods section in:

A conundrum in the structure of brain networks: “small-world” integration of “large-world” functional modularity, by Gallos, Makse and Sigman.

Avoiding catastrophic failure in correlated networks of networks, S. D. S. Reis, Y. Hu, A. Babino, J. S. Andrade Jr., S. Canals, M. Sigman, and H. A. Makse.

(B) Human resting state datasets

Human resting state datasets (network datasets, ATTENTION! Large file: 1.4 Gb)

A total of 12 right-handed participants were included (8 women and 4 men, mean age 27, ranging from 21 to 49). During the scan, participants were instructed to rest with their eyes open while the word Relax was centrally projected in white, against a black background. A total of 197 brain volumes were acquired. For fMRI a gradient echo (GE) EPI was used with the following parameters: repetition time (TR) = 2.0 s; echo time (TE) = 25 ms; angle = 90; field of view (FOV) = 192 X 192 mm; matrix = 64 X 64; 39 slices 3 mm thick. For spatial normalization and localization, a high-resolution T1-weighted anatomical image was also acquired using a magnetization prepared gradient echo sequence (MP-RAGE, TR = 2500 ms; TE = 4.35 ms; inversion time (TI) = 900 ms; flip angle = 8; FOV = 256 mm; 176 slices). Data were processed using both AFNI (version AFNI 2011 12 21 1014, and FSL (version 5.0, and the help of the batch scripts for preprocessing. The preprocessing consisted on: motion correcting (AFNI) using Fourier interpolation, spatial smoothing (fsl) with gaussian kernel (FWHM=6mm), mean intensity normalization (fsl), FFT band-pass filtering (AFNI) with 0.08 Hz and 0.01Hz bounds, linear and quadratic trends removing, transformation into MIN152 space (fsl) with a 12 degrees of freedom affin transformation, (AFNI) and extraction of global, white matter and cerebrospinal fluid nuisance signals.

For a detailed description of the datasets please see:

Avoiding catastrophic failure in correlated networks of networks, S. D. S. Reis, Y. Hu, A. Babino, J. S. Andrade Jr., S. Canals, M. Sigman, and H. A. Makse.

(C) Network datasets from human dual task and resting state

Network data extracted from fMRI data above.

For further information or help with the files, please contact Hernan Makse.

(D) Task-based fMRI of 20 healthy individual performing a language task used for clinical studies.

Healthy 20 subject – language task (ATTENTION! Large file, 2.47 Gb)

A total of 20 right-handed healthy subjects were included in the study. The .zip files contains, for each individual, fMRI and MRI files and the language model used during the task. In addition, we include the weighted adjacency matrix and further information about the functional network that we build from this data set. Please see the readme file for each individual.

(E) Case report study on the functional translocation of the Broca’s area. 

Case report – translocation of Broca’s area

A righ-handed patient who shows functional translocation of the Broca’s area from the left to the right hemisphere, due to brain tumor, is studied. Data include three different fMRI language task and MRI. Additionally we provide the data about the functional network structure that we constructed from the fMRI.