The Brain
The human brain, in all its complexity, is nearly impossible to model. One neuroscientist is trying anyway
In the ’90s, when he was a doctoral student at the University of Lausanne, in Switzerland, neuroscientist Sean Hill spent five years studying how cat brains respond to noise. At the time, researchers knew that two regions—the cerebral cortex, which is the outer layer of the brain, and the thalamus, a nut-like structure near the centre—did most of the work. But, when an auditory signal entered the brain through the ear, what happened, specifically? Which parts of the cortex and thalamus did the signal travel to? And in what order? The answers to such questions could help doctors treat hearing loss in humans. So, to learn more, Hill, along with his supervisor and a group of lab techs, anaesthetized cats and inserted electrodes into their brains to monitor what happened when the animals were exposed to sounds, which were piped into their ears via miniature headphones. Hill’s probe then captured the brain signals the noises generated.
The last step was to euthanize the cats and dissect their brains, which was the only way for Hill to verify where he’d put his probes. It was not a part of the study he enjoyed. He’d grown up on a family farm in Maine and had developed a reverence for all sentient life. As an undergraduate student in New Hampshire, he’d experimented on pond snails, but only after ensuring that each was properly anaesthetized. “I particularly loved cats,” he says, “but I also deeply believed in the need for animal data.” (For obvious reasons, neuroscientists cannot euthanize and dissect human subjects.)
Over time, Hill came to wonder if his data was being put to the best possible use. In his cat experiments, he generated reels of magnetic tape—printouts that resembled player piano scrolls. Once he had finished analyzing the tapes, he would pack them up and store them in a basement. “It was just so tangible,” he says. “You’d see all these data coming from the animals, but then what would happen with it? There were boxes and boxes that, in all likelihood, would never be looked at again.” Most researchers wouldn’t even know where to find them.
Hill was coming up against two interrelated problems in neuroscience: data scarcity and data wastage. Over the past five decades, brain research has advanced rapidly—we’ve developed treatments for Parkinson’s and epilepsy and have figured out, if only in the roughest terms, which parts of the brain produce arousal, anger, sadness, and pain—but we’re still at the beginning of the journey. Scientists are still some way, for instance, from knowing the size and shape of each type of neuron (i.e., brain cell), the RNA sequences that govern their behaviour, or the strength and frequency of the electrical signals that pass between them. The human brain has 86 billion neurons. That’s a lot of data to collect and record.
But, while brain data is a precious resource, scientists tend to lock it away, like secretive art collectors. Labs the world over are conducting brain experiments using increasingly sophisticated technology, from hulking magnetic-imaging devices to microscopic probes. These experiments generate results, which then get published in journals. Once each new data set has served this limited purpose, it goes . . . somewhere, typically onto a secure hard drive only a few people can access.
Hill’s graduate work in Lausanne was at times demoralizing. He reasoned that, for his research to be worth the costs to both the lab that conducted it and the cats who were its subjects, the resulting data—perhaps even all brain data—should live in the public domain. But scientists generally prefer not to share. Data, after all, is a kind of currency: it helps generate findings, which lead to jobs, money, and professional recognition. Researchers are loath to simply give away a commodity they worked hard to acquire. “There’s an old joke,” says Hill, “that neuroscientists would rather share toothbrushes than data.”
He believes that, if they don’t get over this aversion—and if they continue to stash data in basements and on encrypted hard drives—many profound questions about the brain will remain unanswered. This is not just a matter of academic curiosity: if we improve our understanding of the brain, we could develop treatments that have long eluded us for major mental illnesses.
In 2019, Hill became director of Toronto’s Krembil Centre for Neuroinformatics (KCNI), an organization working at the intersection of neuroscience, information management, brain modelling, and psychiatry. The basic premise of neuroinformatics is this: the brain is big, and if humans are going to have a shot at understanding it, brain science must become big too. The KCNI’s goal is to aggregate brain data and use it to build computerized models that, over time, become ever more complex—all to aid them in understanding the intricacy of a real brain. There are about thirty labs worldwide explicitly dedicated to such work, and they’re governed by a central regulatory body, the International Neuroinformatics Coordinating Facility, in Sweden. But the KCNI stands out because it’s embedded in a medical institution: the Centre for Addiction and Mental Health (CAMH), Canada’s largest psychiatric hospital. While many other neuroinformatics labs study genetics or cognitive processing, the KCNI seeks to demystify conditions like schizophrenia, anxiety, and dementia. Its first area of focus is depression.
Fundamentally, we don’t have a biological understanding of depression.
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