Neural networks capable of making decisions or storing memories have intrigued scientists for years. A defining feature of these networks is the presence of stereotyped activity sequences, similar to one-way paths. John Hopfield, a key figure in this area, was recently co-awarded the 2024 Nobel Prize in Physics alongside Geoffrey E. Hinton, a former faculty member at Carnegie Mellon University. However, the use of these one-way paths in the brain remained unproven until now.
A team of researchers from Carnegie Mellon and the University of Pittsburgh devised an innovative experiment using a brain-computer interface (BCI) to test this concept causally. The results supported the existence of one-way activity paths in the brain, aligning with long-standing hypotheses from neural network models.
Neural dynamics, or stereotyped sequences of neural population activity, are believed to support various brain functions, including motor control, sensory perception, decision-making, timing, and memory. The team concentrated on the brain’s motor system, as described in their recent publication in Nature Neuroscience, where neural population activity can be harnessed to control a BCI.
“The brain is composed of networks of neurons that have connections between them,” explained Alan Degenhart, a former postdoctoral researcher at Pitt and CMU. “Previous studies have shown and theorized that the way these networks of neurons are connected can influence how their activity evolves over time. We hypothesized that if this was true, then it would be difficult for subjects to modify the sequences of their neural activity, if we challenged them to do so.”
In the study, a BCI challenged nonhuman subjects to deviate from the natural sequences of neural activity in the motor cortex. This involved attempting to traverse natural neural activity sequences in reverse. Despite being given visual feedback and a reward incentive, subjects could not alter these neural activity sequences, supporting the idea that stereotyped sequences result from constraints in the neural circuitry.
Emily Oby, a former research professor at Pitt, notes that neural dynamics computation is experiencing a renaissance. “There is a lot of synergy between neural network modeling and how we can use those models to better understand the brain. Our findings have relevance for the field of computational neuroscience, as well as BCIs, stroke recovery and how the brain learns.”
Understanding how the brain uses these stereotyped activity sequences can also aid individuals with injuries or disorders affecting the cerebral cortex. “If we have an understanding of how constrained this activity is, we may be able to positively impact patient care and recovery,” elaborated Erinn Grigsby, a former Ph.D. student at Pitt. “The idea is that we can maybe help them regain some motor control by using optimized learning that takes into account the constraints of neural activity sequences.”
The researchers are expanding this work with a BCI-driven project to further connect stereotyped activity sequences to physical movements, aiming to better comprehend how planning influences movement.
“Our study validates principles that researchers have brought out in neural network models for decades,” added Byron Yu, professor of biomedical engineering and electrical and computer engineering at CMU. “If the stereotyped activity sequences could change, that would presumably mean a new skill has been learned or a new computation is being performed. However, we found that the sequences of neural activity are obligatory on a one-to-two-hour timescale.”
Aaron Batista, professor of bioengineering at Pitt, emphasized the unique collaboration enabling this research. “We have computational neuroscientists helping out with experiments, and experimental neuroscientists designing and implementing algorithms,” highlighted Batista. “A team like ours that can bring together the state-of-the-art of two disciplines, that are usually separate, really makes it possible to do transformative work.”
The work continues in collaboration with the Center for Neural Basis of Cognition, a joint research and educational program between Carnegie Mellon and the University of Pittsburgh. The Nature Neuroscience paper was co-authored by postdoctoral fellow Asma Motiwala and former Ph.D. students Nicole McClain and Patrick Marino. Emily Oby is now an assistant professor at Queen’s University, and Alan Degenhart is a senior research scientist at Starfish Neuroscience.
Read More Here
Be First to Comment