In the beginning, my plan seemed perfect. I would meditate for five minutes in the morning. Each evening before bed, I would do the same. And instead of having to rely on my own feelings, a biofeedback device would study my brainwaves to tell me whether I was actually focused, anxious, or asleep. By placing a few electrodes on my scalp to measure its electrical activity, I could use an electroencephalography (EEG) headset to monitor my mood and help me meditate. And unlike “quantified self” devices like the Fitbit or Apple Watch, which save your data for later, the headset would loop my brainwaves back to me in real time so that I could better control and regulate them. What could be more relaxing?
Inward bound, I sat at my desk and closed my eyes. Waves crashed loudly on the shore, which indicated that I was thinking too much
Basic EEG technology has been around since the early 20th century, but only recently has it become available in affordable, Bluetooth-ready packages. In the past five years, several startups — with hopeful names like Thync, Melon, Emotiv, and Muse — have tried to bring the devices from clinical and countercultural circles into mainstream consumer markets. Their sales pitch is undeniably attractive: In the comfort of our own homes, without psychotropic meds, psychoanalysis, or an invasive operation, we could bring to light what had previously been unconscious. That, in any case, is the dream.
When I first placed the Muse on my head one Sunday evening in late October, I felt as though I was greeting myself in the future. A thin black band, lightweight and plastic, stretched across my forehead. Its wing-like flanks fit snugly behind my ears. On the launch screen of its accompanying iPhone app, clouds floated by. The Muse wasn’t just a meditation device, the app explained, but a meditation assistant. For some minutes, my initial signal was poor, but eventually the Muse accurately “sensed” my brain. It would now be able to interpret my brainwaves and translate their frequencies into audio cues, which I would hear throughout my meditation session.
Inward bound, I sat at my desk and closed my eyes. Waves crashed loudly on the shore, which indicated that I was thinking too much. But from time to time, I could hear a few soft splashes of water and, farther in the distance, the soft chirping of birds. After what seemed like forever, the session was over. As with all self-tracking practices (and unlike conventional meditation), the post-game seemed to as important as the practice itself, so I made a good-faith effort to pore over my “results.”
They were, at first, second, and third glance, impenetrable. I had earned 602 “calm points,” which the app had mysteriously multiplied by a factor of three. My “neutral points,” by contrast, had been multiplied by a factor of only one. Birds, I was told, had “landed” 16 times.
Equally inscrutable were the two awards I had earned, after a total of seven minutes scanning my brain. One was for tranquility — “Being more than 50 percent calm in a single session must feel good,” the app told me. The other was a “Birds of Eden Award”: I earned this because at least two birds chirped per minute, “which must have felt a bit like being at Birds of Eden in South Africa — the largest aviary in the world.” Not really, I thought. But then again, I had never been to South Africa.
It felt great to meditate for the first time only to be told that I was already off to a good start. But I knew — or, at least, I thought I knew — that I had not felt calm during any part of the session. I had to either accept that I did not know myself, in spite of being myself, or insist on my own discomfort to prove the machine wrong. It seemed that what the brain tracker wanted was less for me to know myself better than for me to know myself the way that it knew me.
The second morning of my experiment, I went to see Dr. Kamran Fallahpour, the founder of the Brain Resource Center, which provides patients with maps and other measures of their cognitive activity so that they can, ideally, learn to alter it. Some of Fallahpour’s patients suffer from severe brain trauma, autism, PTSD, or cognitive decline, but many others — athletes, opera singers, attorneys, actors, students (some as young as five years old) — come to him to improve their concentration, reduce stress, and “achieve peak performance” in their respective fields.
It seemed the brain tracker wanted less for me to know myself than for me to know myself the way it knew me
Before turning to brain stimulation technologies, Fallahpour worked for many years as a psychotherapist, treating patients with traditional talk therapy. His supervisors thought he was doing a good job, and he saw many of his patients improve. But the results were slow-going. He often got the feeling that he was only “scratching the surface” of their problems. Medication worked more quickly, but it, too, was imprecise. Pills could mask the symptoms of those suffering from a brain injury, but they did little to improve the brain’s long-term health.
Fallahpour started to become interested in how to improve the brain through conditioning, electrical and magnetic stimulation, and visual feedback. He began to work with an international group of neuroscientists, clinicians, and researchers developing a database of the “typical” brain. They interviewed thousands of “normal” patients — what was regarded as normal was determined by tests showing the absence of known psychological disorders — and measured their brainwaves, among other physiological responses, to establish a gigantic repository of the normative brain’s function.
Neuroscience has always had a double aim: to know the brain and to be able to change it. Its method for doing so — “screen and intervene” — is part of the larger trend toward personalized medicine. Advance testing, like genomics, can target patients at risk for diabetes, cancer, and other diseases. With the rise of these increasingly sophisticated diagnostic technologies, individuals can not only be treated for current symptoms but prescribed a course of therapy to prevent future illnesses.
Under the 21st century paradigm of personalized medicine, everyone becomes a potential patient. This is why the Brain Resource Center sees just as many “normal” minds as symptomatic ones. And it’s why commercial EEG headsets are being sold to both epileptics trying to monitor their symptoms and employees hoping to work better, faster.
Brain training like this is seductive because its techniques coincide with the prevailing neoliberal approach to care: health is framed as a product of personal responsibility, while economic and environmental etiologies are ignored. Genetics may hardwire us in certain ways, the logic of neuro-liberalism goes, but hard work and data can make us healthy.
Consider Fallahpour’s boot camp for elementary-school kids. For a few hours each day during school vacations, the small rooms of his low-ceilinged offices are swarmed with well-behaved wealthy children playing games to “improve brain health,” “unlock better function,” and acquire a “competitive advantage.” “We tune their brain to become faster and more efficient,” he explained. “The analogy is they can have Windows 3.1 or upgrade it to 10.” Before I had time to contemplate the frightening implications of this vision, the phone began to ring. Fallahpour exchanged pleasantries for a few minutes, asking about the caller’s weekend. No, he told them, he did not take insurance.
The more I thought about the kind of cognitive enhancement Fallahpour promised, the more trouble I had remembering the last time I felt clear-eyed and focused. Had I ever been? Would I ever be? For a few days I was in a fog. I sensed a dull blankness behind my eyes. I wondered if it was a head cold, or sleep deprivation, or a newfound gluten allergy. On a good day, I convinced myself, there was no way I was operating above 60 percent, maybe 65. Sixty percent of what, I wasn’t sure. But I knew I could do better.
The more elusive peak performance seemed, the more I came to realize that it was an essentially nostalgic feeling
I started to resent those who had achieved mythical “peak performance,” and redoubled my commitment to self-improvement. The headset continued to flatter. “Whatever you’re experiencing right now is perfect,” my meditation assistant whispered in my ear, after another tedious sitting.
Still, I couldn’t help comparing each session’s score to the last’s. Was I hearing fewer birds? Was it easier to focus with or without caffeine? As suspicious as I was about the underlying accuracy of the headset’s metrics, I still wanted to beat my previous score. The more elusive peak performance seemed, the more I came to realize that it was an essentially nostalgic feeling. It preyed on the fear that the younger, sharper, more clear-eyed version of yourself once existed and had now disappeared. And it relied on the hope that someday, with practice, such peak selfhood could be rediscovered.
When I went to see Dr. Fallahpour for a follow-up visit, we decided I should try to take a snapshot of my brain. I tried a calm protocol first, to test my brain’s ability to relax, followed by a setting that rewarded my brain for its ability to focus. While he gelled the electrodes and placed them on my scalp, I asked him about some of the skepticism surrounding EEG headsets — namely, the fact that many people, myself included, found it difficult to tell what exactly was being measured.
“EEG is a crude tool and it isn’t the best we have, but it’s the most convenient in many ways,” he explained. “It’s prone to a lot of ‘garbage in and out.’” But when done correctly, he added, it could be “useful and quite powerful.” For one of the protocols we tried, I was asked to modulate my mind’s frequencies in order to trigger classical music to play, even if I did not quite know what those patterns meant or how to generate them.
It soon became clear that deciphering signals from the noise required the trained judgment of an expert like Fallahpour. In this sense, the EEG’s biofeedback wasn’t as seamless as, say, going to the gym with your Fitbit. You still needed someone to help you help yourself.
The next day at dinner, I mentioned these experiments to a friend, who recommended that I watch “Online Shopping Center.” In the performance, the conceptual programmer Sam Lavigne trains a homemade EEG device to identify whether his brain is thinking about online shopping or his own mortality. He sleeps at night with the headset on, hooked up to a computer that either fills carts on Amazon or provides the notification, “You are thinking about your own death.” Having a brain that was either “shopping-like” or “death-like” was not so different, it seemed, from the Muse telling me whether I was calm or active, focused or restless. In both cases, the binaries were reductive, the exercise absurd.
By the end of my week with the Muse, my results were as inscrutable as they had been at the start. Thousands of birds had chirped in my ear. An infinity of waves had crashed upon an endless shore. I had earned quite a few more badges, some by the sheer virtue of persisting: adjusting the signal, continuing the exercise day after day, not quitting in the face of a great and useless mystery.
The more I parsed my graphs and charts, though, the more obscure they seemed. As anyone who has taken more than a passing glance at the mind already knows, our tools aren’t good enough. At least not yet. And the inadequate and embarrassing analogies we use to describe our brains do little to help us see ourselves. In the course of the week, mine had been compared to a loom, a digital machine, an obsolete Windows operating system.
What had I been expecting? That a toy would illuminate the fog? Average EEG devices like the Muse have been shown to have trouble distinguishing between the signals of a relaxed brainwave, stray thought, skin pulse, and furrowed brow. And several studies have disproven the efficacy of related “brain training” games, which don’t augment intelligence so much as make people better at playing their specific games. The Muse helped me score calm points and charm songbirds, but how all this was connected to unlocking inner bliss remained unclear.
I had learned very little about myself. This in itself wasn’t surprising. But if my EEG adventure taught me anything, it was a contradictory lesson ripped straight out of Silicon Valley’s playbook: Know thyself, and know your data knows better.
This piece originally appeared in Logic, a new magazine about technology published in San Francisco. Read their manifesto, subscribe, and check out their new book, Tech Against Trump, at logicmag.io. Their upcoming issue is on Scale. Contact editors@logicmag.io with pitches.