Skip to Content

The Quantified Brain of a Self-Tracking Neuroscientist

A neuroscientist is getting a brain scan twice every week for a year to try to see how neural networks behave over time.

Russell Poldrack, a neuroscientist at the University of Texas at Austin, is undertaking some intense introspection. Every day, he tracks his mood and mental state, what he ate, and how much time he spent outdoors. Twice a week, he gets his brain scanned in an MRI machine. And once a week, he has his blood drawn so that it can be analyzed for hormones and gene activity levels. Poldrack plans to gather a year’s worth of brain and body data to answer an unexplored question in the neuroscience community: how do brain networks behave and change over a year?

Quantified brain: Russell Poldrack, a neuroscientist at the University of Texas at Austin, is tracking his daily mood and weekly brain activity.

While different investigators have examined a particular person’s brain activity at different times, no study has examined the patterns of a brain at a twice weekly frequency for a year. Poldrack’s self-tracking study could help fill a gap in the neuroscience community’s understanding of how brain networks act. “We know absolutely nothing about how a healthy brain changes its function and fluctuates over the course of days and weeks and months, and that’s important to know because there are a lot of disorders, including depression, bipolar disorder, and schizophrenia that show really big fluctuations over the course of weeks and months,” says Poldrack. “This kind of data set—I image myself two to three times a week over a year, that’s 100 to 150 imaging sets of one person—just doesn’t exist,” he says.

MRI scans can reveal when different regions of the brain have similar patterns of activity—in other words, when they function as a network. Different brain networks are associated with different cognitive functions and are a hot area of research for investigators trying to treat disorders such as depression and epilepsy (see “Brain Implants Can Reset Misfiring Circuits”).  Recently, the U.S. government announced $100 million in funding for a large initiative to determine the activity patterns of all individual neurons in the brain (see “Why Obama’s Brain-Mapping Project Matters”). The goal is to understand how brain network patterns change in disease states, but that will require a greater understanding of how healthy neural networks behave.

Mind reader: Russell Poldrack lies in an MRI machine in the Imaging Research Center at the University of Texas at Austin.

“In any disease you care to name, people are ascribing meaning to changes observed in these networks, but we really don’t understand how these networks can fluctuate on a daily, weekly, or monthly basis,” says Ravi Menon, a neuroscientist and MRI specialist at Robarts Research Institute in London, Ontario. “If we don’t know the variation, then one has to be really careful in ascribing differences in disease states,” he says.

Poldrack’s self-study could be most interesting if he can identify connections between fluctuations in his brain networks and the rest of the data he collects, says Michael Fox, a neurologist at Massachusetts General Hospital in Boston. Every day, Poldrack plans to survey his mood, rate the quality of his sleep the night before, and log his heart rate during exercise. Each week, technicians on the UT Austin campus will take a blood sample, which will later be analyzed for hormone levels and gene expression levels. “The degree to which he will be able to correlate changes in own brain with changes in mental state and hormone levels will be interesting,” says Fox.

For example, on days when his mood is low or bad, it would be interesting to see if Poldrack’s network connectivity looks more like that of a person with depression. Having the MRI machine in the same building as his office makes the task a bit easier for Poldrack, but not even the director of the imaging center gets a free ride. “I have to pay for the scan time just like everybody else,” he says.

It takes more than a convenient MRI machine, however, to get a research-worthy data set, and Poldrack draws upon the tools and ideas of the Quantified Self movement (see “The Measured Life”) to enhance his project. “I am somebody who is attuned to my own body, I think a lot about diet and nutrition, so it wasn’t a big stretch for me to start thinking about tracking these data on myself,” he says. He says he spends a few hours each week just doing the data collection. “You have to be a little bit obsessive to want to do that,” says Poldrack. “If you don’t do it regularly, the data aren’t very useful.”

Poldrack also has a personal medical question in mind—is there a relationship between the psoriasis flare-ups he gets and other factors such as mood, stress, and gene activity changes?

For the most part, it’s too early to draw any conclusions from the data set, but Poldrack says he can already see a pattern emerging in his brain’s activity patterns. On Tuesdays, he gets an early morning scan on an empty stomach and without a cup of morning coffee. On Thursdays, he can eat and caffeinate. “The networks look more stable on days I’ve had caffeine and eaten,” he says.

Menon says there is no known risk to being exposed to a strong magnetic field twice a week (Menon himself gets scanned on a near-weekly basis to help train students or to develop experimental protocols). During the pilot phase of the project, Poldrack did notice an increase in his tinnitus and accordingly began testing for hearing damage. A small loss in hearing caused him to put the project on hold for several weeks, but when that loss was not detected in future tests, he began again, albeit with noise-canceling headphones.

Poldrack estimates that by early 2014, he should be able to report his overall findings.

Keep Reading

Most Popular

10 Breakthrough Technologies 2024

Every year, we look for promising technologies poised to have a real impact on the world. Here are the advances that we think matter most right now.

Scientists are finding signals of long covid in blood. They could lead to new treatments.

Faults in a certain part of the immune system might be at the root of some long covid cases, new research suggests.

AI for everything: 10 Breakthrough Technologies 2024

Generative AI tools like ChatGPT reached mass adoption in record time, and reset the course of an entire industry.

What’s next for AI in 2024

Our writers look at the four hot trends to watch out for this year

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at with a list of newsletters you’d like to receive.