Researchers link neural variability to short-term memory and decision making

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 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 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."

Doiron explains that brain cells increase activity during short-term . But this activity randomly drifts over time as a result of stochastic (or chance) forces in the brain. This drifting is what Doiron's team is trying to better understand.

"As mathematicians, what we're really trying to do is relate the structure and dynamics of this stochastic variability of to the variability in cognitive performance," said Doiron. "Linking the variability at these two levels will give important clues about the that support cognition."

Using a combination of and nonlinear system theory, the Pitt team examined the responses of a model of a simplified memory network proposed to be operative in the prefrontal cortex. When sources of neural variability were distributed over the entire network, as opposed to only over subsections, the performance of the memory network was enhanced. This helped the Pitt team make the prediction published in PNAS, that brain wiring affects how neural networks contend with—and ultimately express—variability in memory and decision making.

Recently, experimental neurosciencists are getting a better understanding of how the brain is wired, and theories like those published in PNAS by Doiron's group give a context for their findings within a cognitive framework. The Doiron group plans to apply the general principle of linking brain circuitry to neural variability in a variety of sensory, motor, and memory/decision-making frameworks.

More information: For more information on Doiron's lab, visit www.math.pitt.edu/~bdoiron/Welcome.html

Related Stories

Motor memory: The long and short of it

Sep 13, 2011

For the first time, scientists at USC have unlocked a mechanism behind the way short- and long-term motor memory work together and compete against one another.

Recommended for you

Turning off depression in the brain

3 hours ago

Scientists have traced vulnerability to depression-like behaviors in mice to out-of-balance electrical activity inside neurons of the brain's reward circuit and experimentally reversed it – but there's ...

Rapid whole-brain imaging with single cell resolution

4 hours ago

A major challenge of systems biology is understanding how phenomena at the cellular scale correlate with activity at the organism level. A concerted effort has been made especially in the brain, as scientists are aiming to ...

User comments