  Over the past years, network science has proven invaluable as a means to
better understand many of the processes taking place in the brain. Recently,
interareal connectivity data of the macaque cortex was made available with
great richness of detail. We explore new aspects of this dataset, such as a
correlation between connection weights and cortical hierarchy. We also look at
the link-community structure that emerges from the data to uncover the major
communication pathways in the network, and moreover investigate its reciprocal
connections, showing that they share similar properties.
