Connectivity normalization

With significant variability between methods of obtaining structural connectivity, it is often useful to normalize, in one sense or another, the connectivity when comparing, for example, across subjects, or standardizing parameter ranges.

In [1]:
%matplotlib widget
from tvb.simulator.lab import connectivity , plot_connectivity
In [2]:
conn = connectivity.Connectivity.from_file()
conn.configure()

def plot_with_weights(weights):
    conn = connectivity.Connectivity.from_file()
    conn.configure()
    conn.weights = weights
    plot_connectivity(conn, num="tract_mode", plot_tracts=False)

plot_with_weights(conn.scaled_weights(mode='tract'))

WARNING  File 'hemispheres' not found in ZIP.
WARNING  File 'hemispheres' not found in ZIP.
In [3]:
plot_with_weights(conn.scaled_weights(mode='region'))
plot_with_weights(conn.scaled_weights(mode='none'))
plot_with_weights(conn.transform_binarize_matrix())
plot_with_weights(conn.transform_remove_self_connections())

WARNING  File 'hemispheres' not found in ZIP.
WARNING  File 'hemispheres' not found in ZIP.
WARNING  File 'hemispheres' not found in ZIP.
WARNING  File 'hemispheres' not found in ZIP.