IN THE ’90S, when he was a doc toral student at the University of Lausanne, in Switzerland, neuro scientist 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 nutlike 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 doc tors treat hearing loss in humans. So, to learn more, Hill, along with his super visor 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 under graduate 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 rea sons, 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 inter related 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 jour ney. Scientists are still some way, for in stance, from knowing the size and shape of each type of neuron (i.e., brain cell), therna 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 re source, scientists tend to lock it away, like secretive art collectors. Labs the world over are conducting brain experiments using increasingly sophisticated tech nology, from hulking magneticimaging 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 Toron to’s Krembil Centre for Neuroinformatics (kcni), an organization working at the intersection of neuroscience, information management, brain modelling, and psychiatry. The basic premise of neuro informatics 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 be cause it’s embedded in a medical institution: the Centre for Addiction and Mental Health (CAMH ), Canada’s lar gest 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.
The disease affects more than 260 million people around the world, but we barely understand it. We know that the balance between the prefront al cortex (at the front of the brain) and the anterior cingulate cortex (tucked just behind it) plays some role in regulating mood, as does the chemical serotonin. But what actually causes depression? Is there a tiny but important area of the brain that researchers should focus on? And does there even exist a singular dis order called depression, or is the label a catchall denoting a bunch of distinct dis orders with similar symptoms but differ ent brain mechanisms? “ Fundamentally,” says Hill, “we don’t have a biological understanding of depression or any other mental illness.”
The problem, for Hill, requires an ambitious, participatory approach. If neuroscientists are to someday under stand the biological mechanisms behind mental illness — that is, if they are to figure out what literally happens in the brain when a person is depressed, manic, or delusional — they will need to pool their resources. “There’s not going to be a single person who figures it all out,” he says. “There’s never going to be an Ein stein who solves a set of equations and shouts, ‘I’ve got it!’ The brain is not that kind of beast.”
THE KCNI LAB has the feeling of a tech firm. It’s an openconcept space with temporary workstations in lieu of offices, and its glassedin meet ing rooms have inspirational names, like “Tranquility” and “Perception.” The kcni is a “dry centre”: it works with information and software rather than with bio logical tissue. To obtain data, researchers forge relationships with other scientists and try to convince them to share what they’ve got. The interior design choices are a tactical part of this effort. “The space has to look nice,” says Dan Felsky, a researcher at the centre. “Colleagues from elsewhere must want to come in and collaborate with us.”
Yet it’s hard to forget about the larger surroundings. During one interview in the “Clarity” room, Hill and I heard a codeblue alarm, broadcast across CAMH, to indicate a medical emergency elsewhere in the hospital. Hill’s job doesn’t involve front-line care, so he doesn’t personally work with patients, but these disruptions reinforce his sense of urgency. “I come from a discipline where scientists focus on theoretical subjects,” he says. “It’s important to be reminded that people are suffering and we have a responsibility to help them.”
Today, the science of mental illness is based primarily on the study of symp toms. Patients receive a diagnosis when they report or exhibit maladaptive behaviours — despair, anxiety, disordered thinking — associated with a given condition. If a significant number of patients respond positively to a treatment, that treatment is deemed effective. But such data reveals nothing about what physically goes on within the brain. “When it comes to the various diseases of the brain,” says Helena Ledmyr, co director of the International Neuroinformatics Coordinating Facility, “we know aston is highly little.” Shreejoy Tripathy, a kcni researcher, gives modern civilization a bit more credit: “The ancient Egyp tians would remove the brain when em balming people because they thought it was useless. In theory, we’ve learned a few things since then. In relation to how much we have left to learn, though, we’re not that much further along.”
Joe Herbert, a Cambridge University neuroscientist, offers a revealing com parison between the way mental versus physical maladies are diagnosed. If, in the nineteenth century, you walked into a doctor’s office complaining of short ness of breath, the doctor would likely diagnose you with dyspnea, a word that basically means . . . shortness of breath. Today, of course, the doctor wouldn’t stop there: they would take a blood sample to see if you were anemic, do an Xray to search for a collapsed lung, or subject you to an echocardiogram to spot signs of heart disease. Instead of applying a Greek label to your symptoms, they’d run tests to figure out what was causing them.
Herbert argues that the way we currently diagnose depression is similar to how we once diagnosed shortness of breath. The term depression is likely as useful now as dyspnea was 150 years ago: it probably denotes a range of wildly different maladies that just happen to have similar effects. “Psychiatrists recognize two types of depression — or three if you count bipolar — but that’s simply on the basis of symptoms,” says Herbert. “Our history of medi cine tells us that defining a disease by its symptoms is highly simplistic and inaccurate.”
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