The cerebellum continues to learn –

SEVILLE (EFE).— A research group from the Pablo de Olavide University (UPO) revealed the continuous learning process in the cerebellum, so that the acquisition, storage, timing and execution of motor learning continues throughout life.

The work, published in the journal “NPJ Science of Learning”, opens new perspectives for neuroscientific research and the development of therapies for neurological disorders of cerebellar origin, according to the Spanish university in a statement.

The cerebellum is crucial in the coordination and precision of motor acts, as it helps adjust and improve the execution of complex motor tasks, and, in fact, it has been classically considered a very important structure in the acquisition, storage, timing and execution of tasks. motor learning.

But this discovery redefines the understanding of learning as a dynamic and constant process in the brain, as demonstrated by the research team from the Division of Neurosciences of the UPO, which unraveled the functional secrets of the nucleus interpositus (IPn) – a cluster of neurons, or nerve cells, located in the central nervous system—of the cerebellum.

Contrary to the conventional wisdom of limiting the understanding of learning to its acquisition, storage, or retrieval, this study suggests that learning is a continuous functional state.

study rabbits

To carry out the research, rabbits were used, in which the activity of IPn neurons was recorded while these animals carried out associative learning tasks.

The researchers worked on two different stimuli: one of sound, which does not produce eye closure, and another of blowing, which does. When the animal heard the sound its tendency was to close its eyelids.

This suggests that the IPn neurons generate “predictions” that “optimize in time and form the conditioned blinking response,” that is, “blink before receiving the puff of air,” explains Rocío Leal, one of the researchers.

Scientists discovered that, contrary to what was believed, the cerebellum operates under Bayesian rules—we update our beliefs regarding a hypothesis as we obtain new evidence—an advance that would have significant implications in fields from clinical neurology to intelligence. artificial inspired by the brain.