  In this work we challenge the main conclusions of Gu et al work
(Controllability of structural brain networks. Nature communications 6, 8414,
doi:10.1038/ncomms9414, 2015) on brain controllability. Using the same methods
and analyses on four datasets we find that the minimum set of nodes to control
brain networks is always larger than one. We also find that the relationships
between the average/modal controllability and weighted degrees also hold for
randomized data and the there are not specific roles played by Resting State
Networks in controlling the brain. In conclusion, we show that there is no
evidence that topology plays specific and unique roles in the controllability
of brain networks. Accordingly, Gu et al. interpretation of their results, in
particular in terms of translational applications (e.g. using single node
controllability properties to define target region(s) for neurostimulation)
should be revisited. Though theoretically intriguing, our understanding of the
relationship between controllability and structural brain network remains
elusive.
