Warnings and Caveats in Brain Controllability

TL;DR

This paper critically re-evaluates previous claims about brain controllability, showing that the control of brain networks involves multiple nodes and that topology may not have specific roles, challenging prior interpretations.

Contribution

It demonstrates that the minimum control set in brain networks is larger than one and questions the specific roles of network topology in controllability.

Findings

Minimum control set is always larger than one.

Relationships between controllability and degree are also found in randomized data.

No specific roles for Resting State Networks in controlling the brain.

Abstract

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.