B. Rose Huber
A team of University of Pittsburgh mathematicians is using computational models to better understand how the structure of neural variability relates to such functions as short-term memory and decision making. In a paper published online April 2 in Proceedings of the National Academy of Sciences (PNAS), the Pitt team examines how fluctuations in brain activity can impact the dynamics of cognitive tasks.
Previous recordings of neural activity during simple cognitive tasks show a tremendous amount of trial-to-trial variability. For example, when a person was instructed to hold the same stimulus in working, or short-term, memory during two separate trials, the brain cells involved in the task showed very different activity during the two trials.
“A big challenge in neuroscience is translating variability expressed at the cellular and brain-circuit level with that in cognitive behaviors,” said Brent Doiron, assistant professor of mathematics in Pitt’s Kenneth P. Dietrich School of Arts and Sciences and the project’s principal investigator. “It’s a fact that short-term memory degrades over time. If you try to recall a stored memory, there likely will be errors, and these cognitive imperfections increase the longer that short-term memory is engaged.”