SC Connecticut News

Yale researchers have made a significant step forward in identifying potential biomarkers for psychiatric disorders by uncovering stable patterns of brain activity shared across more than 300 individuals. This new study, published on September 24 in the journal PLOS Biology, utilized functional magnetic resonance imaging (fMRI) data to reduce complexity and reveal recurring brain activity patterns.

"Because human brain activity is so complex, it can be unreliable, particularly when you’re aiming for reproducibility," said Kangjoo Lee, lead author of the study and an associate research scientist in the Department of Psychiatry at Yale School of Medicine. "In this study, we wanted to capture features of brain activity that were linked to features of human behavior and were also consistent across different people."

The research team used fMRI data from 337 healthy young adults who underwent four 15-minute scans each. These scans captured snapshots of brain activity during a resting state, allowing researchers to observe moment-to-moment changes.

To identify shared patterns in the data, the researchers applied a method called data dimension reduction. This technique simplifies high-dimensional data like brain activity into a lower dimensional space, similar to representing a complex dance sequence with basic movements.

After reducing the data's complexity, three shared patterns of brain activity emerged that were "highly recurring across participants and within participants," according to Lee. While these patterns were common among all participants, individual differences were also noted. These included variations in how much time individuals spent in specific states and their transitions between states.

The findings suggest these patterns could provide insights into both shared behaviors across different people and individual differences related to those behaviors or their changes over time.

The researchers are now exploring how this approach could be applied to psychiatric disorders. "Here we looked at healthy adults, but if we ran a similar analysis in a clinical population, we may find recurring brain patterns that are shared among that population but not among healthy individuals," said co-senior author John Murray, formerly a professor at Yale and now at Dartmouth College. "Therefore, these shared patterns could represent biomarkers of psychiatric illness that are useful in clinical settings."

Supporting this idea further, the study found associations between these recurring patterns and cognitive function, emotion regulation, as well as alcohol and substance use.

"Uncovering recurring brain patterns in clinical populations could tell us something about the neural activity associated with specific symptoms and how it differs between individuals," added Lee.