SCIENTIFICAMERICAN.COM | 13in certain limits. In our lab, we found that in the brains of peo-
ple with schizophrenia and their first-degree relatives, there is
an overabundance of flexibility in how networks reconfigure
themselves. Auditory hallucinations might result when nodes
unexpectedly switch links between speech and auditory mod-
ules. The uninvited mix can result in what seem to be the utter-
ings of voices in one’s head.
Like schizophrenia, major depressive disorder is not caused
by a single abnormal brain region. Three specific modules ap-
pear to be affected in depression: the frontoparietal control, sa-
lience and default mode modules. In fact, the symptoms of de-
pression—emotional disinhibition, altered sensitivity to emo-
tional events and rumination—map to these modules.
As a result, normal communication among the three modules
becomes destabilized. Activities from module to module typical-
ly tug back and forth to balance the cognitive processing of sen-
sory inputs with more introspective thoughts. In depression,
though, the default mode dominates, and the afflicted person
lapses into ruminative thought. The music of the brain thus be-
comes in creasingly unbalanced, with one family of instruments
governing the symphony. These observations have broadened
our understanding of the network properties of depression to
the extent that a connectivity pattern in a brain can allow us to
diagnose certain subtypes of the disorder and determine which
areas should be treated with electrical-stimulation technology.NETWORKS EVOLVE
besides studying development, network neuroscientists
have begun to ask why brain networks have taken their present
form over tens of thousands of years. The areas identified as
hubs are also the locations in the human brain that have expand-
ed the most during evolution, making them up to 30 times the
size they are in macaques. Larger brain hubs most likely permit
greater integration of processing across modules and so support
more complex computations. It is as if evolution increased the
number of musicians in a section of the orchestra, fostering more
intricate melodies.
Another way neuroscientists have explored these questions
is by creating computer-generated networks and subjecting them
to evolutionary pressures. In our lab, we have probed the evolu-
tionary origins of hubs. This exercise started with a network in
which all edges were placed uniformly at random. Next, the net-
work was rewired, mimicking natural selection to form segre-
gated modules and display a property known in network science
as small-worldness, in which paths form to let distant network
nodes communicate with surprising ease. Thousands of such
networks then evolved, each of which ultimately contained hubs
strongly connected to multiple modules but also tightly inter-
connected to one another, forming what is called a club. Noth-
ing in the selection process explicitly selected for a club of hubs—
they simply emerged from this iterative process.
This simulation demonstrates that one potential solution to
evolving a brain capable of exchanging information among mod-
ules requires hubs with strong connections. Notably, real net-
works—brains, airports, power grids—also have durable, tight-
ly interconnected hubs, exactly as predicted by evolutionary ex-
periments. That observation does not mean evolution necessarily
occurred in the same way as the simulation, but it shows a pos-
sible means by which one of nature’s tricks might operate.
STATES OF MIND
when nobel prize–winning physicist Richard Feynman died
in 1988, his blackboard read, “What I cannot create, I do not un-
derstand.” He created a beautiful aphorism, yet it misses a pivotal
idea: it should be revised to “What I cannot create and control, I
do not understand.” Absent such control, we still know enough to
enjoy a symphony, even if we do not qualify to be the conductor.
When it comes to the brain, we have a basic understanding of
its form and the importance of its network architecture. We know
that our brain determines who we are, but we are just beginning
to understand how it all happens. To rephrase mathematician
Pierre-Simon Laplace’s explanation of determinism and mechan-
ics and apply it to the brain, one’s present brain, and so one’s men-
tal state, can be thought of as a compilation of past states that
can be used to predict the future. A neuroscientist who knew all
the principles of brain function and everything about someone’s
brain could predict that person’s mental conditions—the future,
as well as the past, would be present inside the person’s mind.
This knowledge could be used to prevent pain and suffering,
given that many mental illnesses are associated with network
abnormalities. With enough engineering ingenuity, we may de-
velop implanted devices that alter or even generate new brain
networks or edit genomes to prevent the disorganized networks
associated with mental disorders from occurring in the first
place. Such an achievement would enable us to treat diseases
and to restore brain function after stroke or injury and enhance
it in healthy individuals.
Before those futuristic scenarios materialize, two major gaps
must be filled: we need to know more about how personal ge-
netics, early-life development and environment determine one’s
brain’s structure and how that structure leads to functional ca-
pacities. Neuroscientists have some knowledge from the human
genome about the structure that gives rise to functional net-
works but still need to learn precisely how this process occurs.
We are starting to grasp the way brain networks develop and are
shaped by the environment but are not close to explaining the
entire complexity of this process. The brain’s wiring, its struc-
tural connectivity, constrains how various modules interact with
one another, but our knowledge remains limited. As we fill in
these gaps, chances improve for interventions to guide brain
functioning into healthy trajectories.
What holds us back, for the moment, is our still blurry vision
of the brain—it is as if we are outside the concert hall and have
seen only sketches of the instruments. Inside each brain region
that neuroscientists study are millions of neurons firing every
millisecond, and we are able just to indirectly measure their av-
erage activity levels every second or so. Thus far we can rough-
ly identify the human brain’s structural connections. Luckily, sci-
entists and engineers have taken steps to deliver ever clearer
data that will enable a deeper look into perhaps the most com-
plex network in the known universe: your brain.Max Bertolero is a research scientist at the University of Pennsylvania. He received
a doctorate in systems neuroscience from the University of California, Berkeley, and
undergraduate degrees in philosophy and psychology from Columbia University.Danielle S. Bassett is an associate professor in the department of bioengineering at the
University of Pennsylvania, where she studies networks in physical and biological systems.
In 2014 she became a MacArthur Fellow.