How Does Learning Something New Not Overwrite What We Know?

For more than a decade, a collaborative working group of neuroscience researchers from Carnegie Mellon University and University of Pittsburgh have explored unanswered questions about the learning process. Using brain-computer interface (BCI) technology, the group can define the relationship between recorded neurons and movement of a computer cursor in their subjects, using this causal system to ask questions about learning that wouldn’t otherwise be possible. Their latest paper examines what happens in the brain when it’s presented with learning a new task, but also asked to recall a familiar one.

“From a computation or theory perspective, it’s something of a mystery how the same neurons can be used for so many things,” said Jay Hennig, a former graduate student in neural computation and machine learning at Carnegie Mellon. “It’s not as though you have a separate neuron for each thing you must learn; you actually have to reuse the same brain for all these different things. What we found is one way that the brain can do that. It has the capacity to learn a new task in a way that’s cooperative with the other things it needs to do.”

In their analysis, the group used a BCI learning paradigm to monitor brain activity during a familiar cursor movement task and then instructed subjects to try out a new task, before returning to the familiar task. They found that learning something new altered the neural activity used to perform a familiar task, such that neural activity remained appropriate for the new task but did not impede performance on the familiar task.

“We found that learning leaves a ‘memory trace,’” explained Darby Losey, first author of the work published in Current Biology and Ph.D. graduate of the neural computation and machine learning training programs. “A memory trace is an alteration of neural activity, specific to the learning experience, that persists after learning is done. It acts to position neural activity to be good for both tasks.”

How learning leads to lasting changes in the brain has been pondered in previous studies, but in a correlative way, using arm movements, versus a BCI. Unique to this study, BCI data enables the team to know precisely how changes in neural activity relate to both the learned and familiar experiences because the exact relationship between neural activity and behavior is known and can be measured regardless of which task the subject performs.

To move this work forward, the researchers are conducting experiments to explain the related phenomenon of savings.

“If we use the analogy of learning a new racket sport, squash, when you already play tennis, savings can be used to define the stored proficiency you have for squash when you come back to it a second time,” expressed Emily Oby, research instructor, University of Pittsburgh. “You start at a place that is better than the initial learning experience. We believe this memory trace may be a neural explanation for savings.” Bearing this in mind, the group is conducting experiments to explore the neuronal correlation between memory trace and savings.

“For learning to be useful, it has to be remembered,” added Steve Chase, professor of biomedical engineering and the Neuroscience Institute at Carnegie Mellon and one of the three leads on the project, along with Byron Yu of Carnegie Mellon and Aaron Batista of the University of Pittsburgh. “The process of how you take a learned experience and lay it down in neural activity, so it can be recalled again when you need it, is a fascinating process. Our understanding of it is still in its infancy. The hope is that by looking at how these learned acts are laid down for motor tasks, it will help us know how they’re laid down for other tasks as well. And, ultimately, once we’re able to do all of this, we can try to understand what all the factors that help us remember are, to really track the memory process itself.” 

The group’s work is ongoing and done in collaboration with the Center for Neural Basis of Cognition, a cross-university research and educational program between Carnegie Mellon and the University of Pittsburgh that leverages each institution’s strengths to investigate the cognitive and neural mechanisms that give rise to biological intelligence and behavior.