  In the applications of the graph theory it is unusual that one considers
numerous, pairwise different graphs on the very same set of vertices. In the
case of human braingraphs or connectomes, however, this is the standard
situation: the nodes correspond to anatomically identified cerebral regions,
and two vertices are connected by an edge if a diffusion MRI-based workflow
identifies a fiber of axons, running between the two regions, corresponding to
the two vertices. Therefore, if we examine the braingraphs of $n$ subjects,
then we have $n$ graphs on the very same, anatomically identified vertex set.
It is a natural idea to describe the $k$-frequently appearing edges in these
graphs: the edges that are present between the same two vertices in at least
$k$ out of the $n$ graphs. Based on the NIH-funded large Human Connectome
Project's public data release, we have reported the construction of the
Budapest Reference Connectome Server \url{http://connectome.pitgroup.org} that
generates and visualizes these $k$-frequently appearing edges. We call the
graphs of the $k$-frequently appearing edges "$k$-consensus connectomes" since
an edge could be included only if it is present in at least $k$ graphs out of
$n$. Considering the whole human brain, we have reported a surprising property
of these consensus connectomes earlier. In the present work we are focusing on
the frontal lobe of the brain, and we report here a similarly surprising
dynamical property of the consensus connectomes when $k$ is gradually changed
from $k=n$ to $k=1$: the connections between the nodes of the frontal lobe are
seemingly emanating from those nodes that were connected to sub-cortical
structures of the dorsal striatum: the caudate nucleus, and the putamen. We
hypothesize that this dynamic behavior copies the axonal fiber development of
the frontal lobe.
