Our brains are wondrous, incredible machines. They're slower than the earliest personal computers in terms of raw processing power, yet capable of leaps of intuition and able to store a lifetime of memories that are cross-referenced and instantly-accessible at the slightest prompting. We know so very little about how they do these things, however. But imagine for a moment if we could build a complete wiring diagram of a human brain – to map in detail every one of the hundred trillion or so synapses and roughly hundred billion neurons together with all the tiniest supporting mechanisms. What might that mean, and would it even be possible?
Keep thinking about that. We'll come back to it in a bit. First let's cover some more background. The functioning of a healthy brain relies on its network of neuronal connections. Multiple layers of connections and pathways, like the wires of an old mainframe computer, all add up to a single entity.
This network of connections has been called the "connectome" by scientists. To map it is essentially to build the brain's wiring diagram. The human brain connectome has not yet been fully mapped at the cellular or the macro (high-level structural and functional) scale, though efforts to do the latter are much further along than the former – which has only just even become possible (more on that later).
Both avenues of connectome study promise all sorts of insights about how the brain works. The Human Connectome Project, which is an international effort to map the connectomes of 1,000 people on a macro scale – mostly just the white matter, or active myelinated (insulated) nerve cell bundles – using magnetic resonance imaging, this week announced its finding that brain wiring patterns correlate with behavioral and demographic traits.
The study found that in a sample of 460 people aged between 22 and 35, people with more education, better physical endurance, above-average memory, and other "positive" traits seem to have more strongly-connected brains than people with "negative" traits such as smoking, aggressive behavior, or a history of drug use. The results don't indicate whether one causes the other, but they do show that connectivity patterns could one day help predict traits or offer broad indicators of the effect of drugs on the brain.
It's all connected
Jeff Lichtman is a professor at Harvard University. He's one of the world's leading researchers in neurobiology, which looks at the brain and nervous system of animals and humans in terms of its anatomy and physiology (i.e., its cells and tissues, and the way they function and are organized). And he runs Harvard's Lichtman Lab. His journey in the field started when he was taking a course on histology – the study of tissues of the body – in medical school.
During the clinical component of the course – which delves into pathology, or the study of disorders/diseases in bodily tissues – he was struck by how there's no physical sign of what's wrong in autism, schizophrenia, bipolar disorder, and other maladies of the nervous system. "This was very different from all the other organ systems where when you look at the tissue there's something to see that is the physical equivalent or correlate of the disease," Lichtman tells us. There's always a physical abnormality like an inflammation or discoloration. But not so for most diseases and disorders that affect the brain.
"After a while I realized that the reason there aren't abnormalities is not that there really aren't any, but because no one's ever actually looked at the brain at the level of resolution they'd have to look to see these abnormalities," Lichtman continues.
The brain is vastly more complicated than any other organ, however, so it's not just a matter of zooming in further – although that's a big part of it. "People will take a single section through a piece of brain and show a synapse," Lichtman explains. "But the brain works by virtue of these connections that allow one nerve cell to talk to many other nerve cells, sort of like a Twitter account, and each nerve cell is also the recipient of a network of information from thousands of other nerve cells."
As a graduate student, Lichtman studied the peripheral nervous system of human babies and other mammalian babies. He noted dramatic rewiring of the nervous system as the babies developed, then developed a technique to map it out using colors. But there aren't enough colors to show all of the wires in the cerebral cortex. He needed another method.
Size matters
Only one animal's full connectome has been constructed thus far: the roundworm C. elegans, which has a mere 302 neurons and serves as the model for research and data sharing in the field. But researchers are also putting considerable effort into mapping the mouse connectome, since mice are easily accessible in the lab and they serve as animal models for many kinds of medical studies.
It's in the mouse connectome that Lichtman and 20 of his colleagues in a joint Harvard and Boston University-led study chose to show off the latest new imaging technology earlier this year. They essentially figured out a way to adapt electron microscopy, which goes down to nanoscale resolutions, for brain imaging. And they tested the technology on a tiny slice of an adult mouse's neocortex, gaining new insights into the complex relationship between axons (nerve fibers) and dendrites (branches on neurons that act kind of like electric input sockets).
Lichtman believes this technology may help with many clinical studies, such as one his lab is working on that explores the difference in brains of healthy mice and those that have an equivalent of a human autism gene for the rare neurodevelopmental disorder Rett syndrome.A key part of science is coming up not only with hypotheses to test but also with questions to ask. And nanoscale imaging of the brain promises to open up a brave new world of questions about brain function and structure on a cellular and subcellular level.
Principle to the quest to map the human connectome is the question of how memories are stored. "You have all these experiences of your life that are basically in there forever," Lichtman says. "You're never going to get rid of them. You may have trouble recalling things, but once you're reminded they just pop back into consciousness, which means that they're sitting in your brain in some form. Almost certainly in the form of which particular nerve cells are connected together in little networks. But no one knows how that information is encoded."
Mapping the wires of the brain might just provide the answer – which Lichtman expects will be some sort of learning algorithm that takes faces, shapes, objects, textures, sounds, names, or whatever else and converts them into wires and electrical signals.
Lichtman is also excited to see whether wiring diagrams might show why and how the brain changes as we get old. He suspects that old brains may have simpler wiring diagrams than younger ones, but connectome mapping – particularly at the finer resolutions – could hold the answer.
Big data
If nothing else, this wiring diagram of the brain will provide a lot of data. What you might call big data. You need to look at every cubic millimeter of brain to see every synapse, which is necessary to map the brain's connectome in full. "In a cubic millimeter of brain there is about two terabytes of image data," Lichtman says. "I think the original Google Maps was on the range of several terabytes – that was for the whole planet." As of August 2012, it was around 20 petabytes, or 20,500 terabytes, for satellite, aerial, and street imagery combined.
A human brain has something on the order of a million cubic millimeters, which means you'd need around two million terabytes to store a map of its wires. Two million terabytes is around two thousand petabytes, or two exabytes. "That's a big number," Lichtman notes. "Even today. Even for Google."
It's so big, even, that most people cannot fathom it. Even that 302-neuron C. elegans worm connectome is too much for most people, and it's more on the order of 12 terabytes. "You couldn't ask for a smaller [connectome] dataset than that, and it's impossibly complicated," Lichtman says. "You can't just look at it and say, 'Oh now I understand how the worm swims and why it makes a sinusoidal movement when the worm moves around in the soil or why it backs up when something noxious bumps into its nose.' It's in there, but you can't look at it and say, 'I see it.'"
If you grew up in a world where a megabyte is a big dataset, you probably have no hope of understanding the scale of a human connectome dataset. If you came of age this millennium, you'll likely have a somewhat easier time of it, because your brain is wired differently, but Lichtman cautions that we may be crossing an important threshold in human development – not just in neuroscience or science more broadly, but in everything from politics to economics to religion.
"The biggest casualty of big data is big ideas, in the sense that there are no big ideas that encompass the data any more," he says. "The data is more complicated than the thoughts of most people." There are too many variables and complex interactions for us to hold in our heads, basically.
With the death of big ideas could come a fundamental change in the human experience, wherein we don't understand and believe so much as steer the analyses and follow the data. What we're looking at with big data is a division between understanding and analysis. We can simulate, model, and analyze with computers, but we can no longer be confident about understanding the results in their entirety.
Man or machine?
That's not the only potential change Lichtman sees on the horizon. As the newly-discovered behavioral links allude to, mapping the brain could radically transform how we treat people. As we demystify the brain with these wiring diagrams, he warns, "virtually all behavior can begin to be judged on the machine that's causing that behavior. Criminality becomes just an expected behavior given the starting condition of that particular brain."
Conceptions of free will could evaporate, and deep-rooted philosophical and religious beliefs may be challenged to their core. That's no reason to abandon the research, because the payoffs – the secret workings of our minds – are so great, but it's cause for concern, and a possible challenge for what Lichtman concedes is a very expensive field of study that advances incredibly slowly.
What we know now about the brain is infinitesimally small relative to the full picture. Lichtman says that mouse neocortex test study for nanoscale brain imaging looked at a mere three billionths or so of the brain's volume.
That scale makes it a somewhat controversial point in science, because it seems like an impossible feat to map an entire human brain at the cellular level. But Lichtman says that this kind of work in general is controversial for a more fundamental reason.
Seeking description
Science is traditionally experimental, whereas connectome mapping is descriptive. Experiments test ideas and manipulate things. Descriptive projects like this one or the Hubble space telescope, or the whole field of archeology, on the other hand, merely look. They are tools of ponderance: what's out there?
To many people that sounds perfectly reasonable, but Lichtman says, "A lot of people in the biomedical sciences think that we are in some way beyond description." Instead, we should be manipulating things – knocking out genes, adding chemicals, activating nerve cells. Not wondering what uncharted, unheard of mysteries remain in the depths of the brain.
Lichtman likens neuroscience on the whole to a staircase with a million stairs. At the top is a complete one-to-one mapping of the human brain. "We maybe have gone one step," he says, "but that's the goal – to turn this field into something productive enough that it is able to generate enough data that one can begin to approach these deep mysteries about the brain."
In truth we probably know more about the universe beyond our Earth than about that which lies between our ears. And that is precisely why Lichtman and his connectome-mapping colleagues will persevere. "As long as we're seeing things we've never seen before, as long as we're discovering things that look different from what we expected, we should keep doing it," he says. "Obviously, because it's adding insight to things that were mysterious."
"Once you understand something well enough that there's nothing to learn and everything is the same, then yeah, maybe it's time to stop. But we're far, far from there."
