Inside your brain, there are 100 billion cells, called neurons. Each of them connects to at least 1,000 other neurons. Do the math, and you get at least 100 trillion connections. That’s far more connections than there are between all existing Internet devices in the world. That means that if you count up every iPhone, every laptop, every tablet computer everyone in the world uses on any given day to get online, you still wouldn’t get nearly as many connections as the ones happening between your ears right now.

Neuroscientists, and neurologists like myself, are convinced that the secret to solving the mystery of how the brain works can be answered by understanding how neurons communicate. We are able to think because neurons communicate with each other. We call all of these connections a connectome, and our big mission now—spearheaded by the NIH Human Connectome Project—is to map it all, just like scientists did a decade ago with the human genome.

We can do this because we have new technologies, including functional magnetic resonance imaging, or fMRI, which uses conventional MRI scanners to measure brain activity while individuals are at rest or perform cognitive tasks. fMRI reveals patterns of brain activity that underlie brain function. This type of scanning also helped confirm the idea that our brain’s neurons are distributed in a way that forms a complex network. Just like Facebook connects people, this enormous network in our heads connects neurons, and they, it turns out, communicate with each other in much the same way we do with our friends and family members.

But knowing that a network exists is one thing; understanding how it works is a challenge of a whole other magnitude. To tackle this problem, we rely on a fascinating field of mathematics called graph theory. It was invented in 1736 by a Prussian mathematician named Leonard Euler. Ambling through his city, Koenigsburg, Euler wondered whether it was possible to walk the entire length of the city while crossing each of its seven bridges once and once only. We still use Euler’s insights today:

We know, for example, that the brain is organized into separate and distinct communities, called modules. A brain module is a group of brain regions that are more connected with each other than with brain regions in other brain modules. Again, Facebook is a helpful metaphor: think of your closest friends on the social network as your module, the people closest to you and with whom you are most likely to communicate. It is presumed that each brain module performs a discrete function, such as producing language or seeing the world around us. However, brain modules must also communicate with each other to accomplish more complex behavior—such as multitasking or solving a mathematical problem.

One way that modules in the brain communicate with each other is through specialized regions called “connector hubs”. A connector hub is a brain region that has more connections with brain regions in other modules than connections within its own module. If these hubs are hurt, say by a stroke or a traumatic brain injury, patients tend not to recover well. But if provincial hubs, which have more connections just within their own module, are the ones hurt, patients are likely to recover to a fuller extent.

This insight isn’t just theoretical. For example, my colleagues and I found that when patients with traumatic brain injury participate in cognitive therapy, their brain connectivity changes in a way that allows them to function better. We also learned that if we scan their brain before starting cognitive therapy, our measurements of their brain connectivity predict who will respond to cognitive therapy and who will not. How did we achieve this scientific clairvoyance? We believe that there is an optimal state that our brains must be in to benefit from therapeutic interventions such as cognitive therapy. And with fMRI, we are able to identify those individuals with this optimal brain state by measuring their own brain connectivity pattern. We still have much to learn about optimal brain states, such as whether we can alter or optimize them or why brain states differ from one person to the next. But our findings nevertheless highlight the tremendous power of brain imaging and its potential impact on medical treatments.

Understanding brain connectivity in this way helps us develop rehabilitation therapies that stimulate the brain to reconfigure itself with new functional connections that bypass damaged connector hubs. In this way, we can attempt to “re-program the brain”. I like this term because it does not mean that we are trying to coax the brain to form new neurons or new neuron pathways—the brain can’t regenerate itself the way bones can. However, re-routing information through existing non-damaged brain regions and pathways for a new purpose may be possible.

To train a brain back to health, we’re currently studying a host of methods. All are promising, and our top priority now should be to determine which of these interventions, or combination of interventions, have the greatest impact on brain connectivity and function. But before we can provide informed recommendations about these interventions to our patients, there must be careful, well-designed clinical research trials, paired with brain imaging methods, to determine their effectiveness.

My take-home message is simple: a greater understanding of the function of the healthy brain will undoubtedly lead to a better understanding of the damaged brain. Recent scientific advances have given us basic knowledge of the functional architecture of the human brain. We are now in an excellent position to develop effective treatments for the millions of individuals who suffer from brain disorders. And that’s very good news.

This piece is part of a special brain health initiative curated by the Ohio State University Wexner Medical Center’s Stanley D. and Joan H. Ross Center for Brain Health and Performance