  Structural plasticity of the brain describes the creation of new and the
deletion of old synapses over time. Rinke et al. (JPDC 2018) introduced a
scalable algorithm that simulates structural plasticity for up to one billion
neurons on current hardware using a variant of the Barnes-Hut algorithm. They
demonstrate good scalability and prove a runtime complexity of $O(n \log^2 n)$.
In this comment paper, we show that with careful consideration of the algorithm
and a rigorous proof, the theoretical runtime can even be classified as $O(n
\log n)$.
