In the quiet of sleep, the small movements of the pupils reveal an extraordinary secret: the delicate act of the brain to preserve the memories while forging new ones.
The eyes never lie (not even when you sleep) and memory is a fragile and fleeting thing. It allows us to retain the faces of our loved ones, to travel family roads and to master new skills. But how does the brain keep the old memories intact and make room for new ones? Scientists wondered about this for decades, in particular about the phenomenon known as “catastrophic oblivion“, In which the new information overwrite the old acquaintance.
The researchers have discovery an surprising bond between the Pupilla size during sleep and the way in which memories are developed. Their discoveries could offer clues to improve memory in humans and even inspire progress in artificial intelligence.
The study
Sleep is divided into two main phases: Rem (rapid eye movement) and. Non REM sleep is the body repair workshop, where breathing slows down, the muscles relax and memories are consolidated silently in the deepest phases. It is a moment of recovery, both physical and mental. Then comes REM sleep, a more mysterious phase characterized by flickering eyes under closed eyelids, intensified brain activities and vivid dreams.
Scholars monitored the brain and pupils while the subjects slept. They noticed a scheme: During a non -REM sleeping specification, the pupils contracted, reporting the consolidation of the tasks just learned. Subsequently, as the pupils dilated, the oldest memories were revisited and strengthened.
The research revealed a previously unknown microstructure of non-rehem sleep, in which the brain alternates the elaboration of new and old memories. By interrupting sleep in critical moments, the researchers found that it was difficult to remember recent or older tasksdepending on the moment of interruption.
This study is promising for artificial intelligence. Neural networks, the backbone of artificial intelligence systems, often face challenges similar to catastrophic oblivion. Insights on how the brain protects and consolidates memories could inspire more robust automatic learning algorithms.
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