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Journal Club: Neurons fire in sync, helping elucidate the biological basis of learning

Researchers found that when rats learned to navigate a maze and find a reward, they displayed distinct patterns of neuronal activity. Image credit: Science Source/Will & Deni McIntyre

Researchers found that when rats learned to navigate a maze and find a reward, they displayed distinct patterns of neuronal activity. Image credit: Science Source/Will & Deni McIntyre

Our brains change as we learn. But how exactly does a cluster of neurons change their activity or connections? It seems the phenomenon is due, at least in part, to neurons starting to fire in sync, according to a recent study in the Journal of Neuroscience.

The research team analyzed data from rats running a maze while implanted electrodes recorded the activity of 15–55 neurons in the prefrontal cortex (PFC). The PFC has a variety of functions, including both short-term memory and learning the connections between actions and consequences, and has been linked to personality, decision-making, and disorders such as schizophrenia. “Think of it as this machine that learns about the probabilities in the world, about the links between the things that are happening in the world, and our effects on them,” says study coauthor Mark Humphries, a neuroscientist at the University of Nottingham in the United Kingdom.

Humphries and his colleagues analyzed data previously collected by coauthor Adrien Peyrache, a neuroscientist at McGill University in Montreal, Canada. Four male rats ran a Y maze, in which they can choose one of two arms to traverse. At the end of one of those arms was a flavored milk reward.

There were four different rules by which an arm would result in a treat: treats were always on the left arm, always on the right, always on the illuminated arm, or always on the dark one. Once rats learned the right strategy by trial and error—which took days or weeks—Peyrache would change the rule.

Before and after the daily maze sessions, the rats rested in a padded flowerpot; usually they napped. By monitoring neurons during these rest and maze sessions, again with electrodes, Peyrache could collect data from before, during, and after the rat figured out the current rule.

Humphries and colleagues analyzed 27 maze sessions, 10 of which involved learning. They saw two patterns of neural activity, one affected by learning and one that happened regardless of learning. Individual neurons fired at different rates from one nap to the next; neuroscientists call these changes plasticity. But when the rat figured out the right strategy, certain neurons would fire in sync. These synchronizations continued as the rats snoozed after they’d learned the rule and reaped the rewards. “Population activity in prefrontal cortex is constantly plastic, but learning gives it direction,” Humphries concludes.

The paper provides clear evidence that learning causes changes to brain states, says David Euston, a neuroscientist at the University of Lethbridge in Canada. “That is one of the things that has been predicted by theories for a long time, but hasn’t really been shown by many papers,” says Euston, who wasn’t involved in the work. The paper also supports the long-held theory that the brain replays recently learned tasks or concepts during sleep to help solidify the memory.

The method that Humphries used to analyze neurons as a population was itself innovative. He and his team called it a “dictionary.” They divided the recording time into small chunks of two to five milliseconds. Then, for each chunk, they noted whether each neuron they recorded had fired or not. They built “words” out of those recordings, noting a 1 for a neuron that fired and a 0 for ones that didn’t. For example, a word 0010010 would indicate the two neurons assigned positions three and six both fired during a given time. By comparing how often certain words appeared in the dictionary, the team could discern which neurons fired together. This is the first time this kind of analysis has been applied to the prefrontal cortex during learning in living animals, according to Peyrache.

“The dictionary approach is a really compelling way to break apart the data,” says Samuel McClure, a neuroscientist at Arizona State University in Tempe who wasn’t involved in the study. At this point, however, it’s a dictionary without definitions. What neuroscientists ultimately want, he notes, is to break the code to understand what the cofiring of certain groups of neurons means.

Nonetheless, McClure says, the paper provides welcome insight into the puzzle that is the prefrontal cortex. “Any progress we make in understanding what is going on in the PFC, how it is structured, how information is represented there,” he says, “is really important.”

Categories: Cell Biology | Journal Club | Neuroscience and tagged | | | | | |
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