Attention: A Muscle to Strengthen
Neurofeedback training could work the brain almost as muscles are worked in physical therapy, as Shibata and his Kyoto colleagues published in a 2011 Science study. The process, which the authors called “inception” in homage to the 2010 film about dreams implanted in people’s brains, made a big splash when it came out. The only instruction inside the fMRI? “Somehow regulate activity in the posterior part of your brain to make the solid green disc… as large as possible.” Without conscious knowledge of what they were learning, subjects managed to make the green disc grow. Shibata trained a decoder to work like the “faces” versus “landscapes” experiment, only he used three different orientations of line gratings for images. Then, while people were watching the green disc, he “rewarded” them by making the disc grow when their brains responded to one of the three patterns of lines. In turn, they became better at seeing the patterns that they associated with the green disc growing.
As Turk-Browne points out, this sort of learning is often unconscious. Which is why some scientists believe tools like the attention machine at Princeton may soon help not only to better understand when the brain goes wrong, but even to treat mental illness.
If you’ve ever known someone with ADHD or depression, you know how these disorders affect attention, holding hostage the senses, focusing them relentlessly on gloomy perspectives. Depression is especially pernicious: My boss frowned at me; my girlfriend dissed my cooking; nobody is talking to me at this party, I’m so boring. The Princeton group, in collaboration with the University of Texas, Austin, hopes to leverage its mental prosthetic to curb this negative attention bias. Instead of noticing the (perhaps imagined) frown on someone’s face, the tool might train depressed brains to focus on the information they are being told.
“Why do some people recover from sad mood, while others stay stuck for months or years?” asks Chris Beevers, a professor of psychology at the University of Texas, Austin, and one of the co-authors of this pilot work. What interests him and his colleagues about the attention tool is its potential to “target mechanisms that maintain sad mood, and reverse them,” a trend he calls precision medicine. “From the clinician’s perspective, we’d like to tailor treatment to an individual’s neural function: not treating every depressed patient the same.”
Today, mental illness is usually treated in two ways: drugs and behavioral therapy. Only around 50 percent of depression patients respond to any drug,according to the National Institutes of Mental Health. The nearly 20 percent of Americans with mental disorders, and the roughly half who will experience one in their lifetimes, are stuck with checklists—How anxious are you, on a scale of 1 to 10? Are you hearing voices? How’s your sleep?—when what they need, some scientists believe, is direct access to the brain. Psychologists like Beevers envision a future in which patients would be evaluated through quantitative tests of traits like memory and attention bias, to determine symptoms to target, and tailor treatment for each patient’s needs. Those who have “difficulty disengaging from emotional content,” as Beevers puts it, may be good candidates for neurofeedback training.
“We still haven’t plumbed the depths of what information can be mined from fMRI… but we’re finding ways to squeeze more information out.”
This sort of training has its roots in today’s talk therapy. People with anxiety are taught to identify feelings that may spiral out of control. But as much as cognitive-behavioral therapy trains the conscious mind to catch rumination, compulsion or panic, and nip them in the bud, other emotional tendencies are completely outside of deliberate control—habits of the brain. So the Princeton-Austin team is using real-time fMRI to rein in the brain’s biases. Depressed subjects are shown a collection of faces, some sad, overlaid on scenes they are told to judge: outdoors or inside? When the machine detects that the viewer is focusing more on faces than scenes, the sad face grows clearer, the scene harder to see. This prompts self-correction by focusing on the scene instead. Over time, the theory goes, subjects get better at not being drawn in by sad faces, at focusing on the task at hand. The hope is that whatever in a depressed person’s brain draws her toward sad things may gradually learn to regulate itself, the researchers say. That’s the hope, anyway. There’s still the question of whether such therapies could treat depression broadly—or, like brain games, just teach people how to excel at the treatment exercise.
The depression research is still ongoing—the authors stress the need for many more subjects and controls—but data reported at November’s Society For Neuroscience conference offered a promising proof of concept. The future of this work, in any case, is provocative to imagine.
“We still haven’t plumbed the depths of what information can be mined from fMRI,” the memory researcher Norman says. “We’re over the honeymoon period, but we’re still finding ways to squeeze more information out of the signal. Now we can pick up on not just ‘How awake are you?’ but ‘What plans are in your head?,’ ‘What are you attending to?’ There’s never been a technology that allows us to get such rich information about mental states from the brain.”