Instructions:

1. please download this file containing a dataset and the code used in this paper (thanks to Dante Chialvo for the permission to use this data/code in this assignment)
2. unzip and compile the code as instructed in reader.f
3. run the program as instructed, and it will produce the full correlation matrix for all voxel pairs in the brain (see the paper)
4. form networks from this correlation matrix: let voxels v₁ and v₂ be connected if the correlation coefficient between them exceeds threshold r_c, r(v₁,v₂) > r_c > 0
5. find an approximate percolation transition value of r_c, i.e., its value r'_c corresponding to the onset of the giant connected component in the resulting networks
6. compute basic network properties (see below) for the network with this r'_c

Completed assignment:
is a zipped file which includes:

• the estimated percolation transition value of the correlation coefficient threshold r'_c
• a short description of how this value was estimated
• the size, average degree, and average clustering in the network with this r'_c
• the raw data for the degree distribution P(k), average degree of neighbors of nodes of degree k (ANND), and average clustering of nodes of degree k in this network
• the properly logbinned plots of the last three statistics

Assignment questions:
can be directed to jobs+net.qs@caida.org