Using Statistical Models to Solve Environmental Problems
4 min read
How many times a day do you lose focus? You’re zeroed in on a task when you’re interrupted by say a friend showing you a cute cat video, or your phone dinging with a text message. After the brief distraction, have you lost your train of thought or are you able to pick up exactly where you left off, unperturbed? Attention spans vary across the population. Some people have laser focus; others are easily distracted. Monica Rosenberg, a Postdoctoral Associate at Yale University, can figure out which group you fall into from a simple brain scan.
“Attention is crucial for navigating everyday life,” says Monica. She researches attention, investigating how we pay attention, why we lose focus, and why are some people—like those with ADHD—have a harder time paying attention than others. Monica hopes that the insights from her research can be used to improve our ability to focus and suggest new treatment targets for people with ADHD and other attention disorders. Her research recently caught the attention (pardon the pun) of Forbes Magazine, who selected her from over 15,000 nominees for their 2017 “30 under 30: Science” list.
What makes Monica stand out from thousands of other young scientists is that she has developed models to predict a person’s attention span based on patterns in their brain activity. Using the method Monica and her colleagues developed, it’s possible to estimate someone’s attention span while they’re not even focusing on a task. It turns out that a person’s unique pattern of brain connectivity—the regions of the brain that are active at the same time—predicts how well they will pay attention in different contexts. Everyone's pattern of brain connectivity is unique and can be measured from data gathered while doing a task or just resting in an MRI scanner.
To quantify attention span, Monica and her colleagues showed participants a series of images during an MRI scan and asked them to press a button when they saw cities, but not when they saw mountains. It’s an easy assignment, but it gets pretty boring after 30 minutes. As you might expect, the results of the experiment were varied: some people performed well and others made several mistakes.
When the researchers analysed the data, they discovered a correlation between how accurately the participants identified the images and patterns in their brain connectivity during the test. Monica and her coworkers created connectivity profiles for each of the participants by looking at how connected the different regions of their brains were with other regions during the image identification task. The researchers realised that certain connections were stronger in people who performed the task more accurately, while others were stronger in people who performed less accurately. With a little statistical analysis, the researchers were able to predict how well each subject performed during the task based purely on their brain connectivity during the task. Using the same statistical analysis, they were even able to predict how each of the participants performed on the task based solely on profiles of their brain connectivity while they were just at rest in the scanner.
Attention varies widely in the population and is sometimes impaired in clinical disorders such as ADHD. To test if their brain connectivity models for attention were specific to a healthy population, Monica and her colleagues applied the same brain connectivity analysis to a data set of over a hundred children and adolescents with varying degrees of ADHD symptoms in China. They built brain connectivity profiles of the children based on resting-state MRI scans and found that the same connection that predicted performance on the cities/mountains task also predicted the ADHD scores of the children. By looking solely at scans of the children’s resting brains, Monica and her coworkers were able to predict their ADHD symptoms. This kind of research has great clinical potential to improve the daily lives of people with attention disorders. A better understanding of how brain circuitry supports attention can suggest new treatment target areas for attention disorders.
Monica finished her PhD in 2017 and is continuing both her attention research and her career in academia. “I’ve always been endlessly fascinated with how the brain gives rise to the mind,” she says. She’s now a Postdoctoral Associate at Yale building models to predict differences in attention and cognition. She hopes to one day lead her own lab as an independent investigator.
Her research has taken her all over the world and given her the opportunity to work with some incredibly smart and creative people. She even gave a talk at the Young European Scientists Meeting in Porto, Portugal alongside two Nobel Laureates. “It was surreal,” she exclaimed. Monica’s dream is that her work will address big questions about attention and provide insights that can improve the daily lives of millions. It seems to us like she’s on the right track.
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