Neural Mechanisms Underlying Working Memory Identified

Researchers from The Rockefeller University and UCLA have identified neural mechanisms that help memories crystallize over time." Their study, published in Nature, employed light-beads microscopy (LBM) to simultaneously observe 73,000 cortical neurons in mice as they learned and repeated a task over two weeks.

The findings revealed a remarkable transformation in the brain's working memory circuits as the mice mastered the task through repetitive practice. Initially, these circuits were unstable, but as the animals continued practicing, the neural representations solidified, leading to more accurate and automatic performance.

"This is what we refer to as 'crystallization,'" explained Alipasha Vaziri, head of Rockefeller's Laboratory of Neurology and Biophysics. "The findings essentially illustrate that repetitive training not only enhances skill proficiency but also leads to profound changes in the brain's memory circuits, making performance more accurate and automatic."

Peyman Golshani, a neurologist at UCLA Health and corresponding author, further elaborated, "If one imagines that each neuron in the brain is sounding a different note, the melody that the brain is generating when it is doing the task was changing from day to day, but then became more and more refined and similar as animals kept practicing the task."

LBM technology enabled the team to capture the activity of up to 1 million neurons simultaneously, a 100-fold increase compared to traditional methods. This large-scale and deep tissue imaging capability was crucial in observing the crystallization of working memory representations that accompanied the mice's increasing mastery of the task.

"In the future, we may tackle the role of different neuronal cell types involved in mediating this mechanism, and in particular the interaction of different types of interneurons with excitatory cells," Vaziri said. "We're also interested in understanding how learning is implemented and could be transferred into a new context—that is, how the brain could generalize from a learned task to some new unknown problems."