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How the mouse brain learns from a single experience

Sometimes, even a single experience can be highly impactful, prompting humans and other animals to change their behavior or influencing their future choices. The formation of influential memories from a single, brief experience is also known as one-shot learning.

How the mouse brain learns from a single experience

Recent research conducted by scientists at Collège de France, Inria, Université Claude Bernard Lyon 1, and Brandeis University has shed light on the neural mechanisms behind one-shot learning in mice. The study, published in Nature Neuroscience, suggests that endocannabinoid-mediated long-term potentiation (eCB-LTP) plays a crucial role in enabling mice to learn from a single, brief experience.

Endocannabinoids are naturally occurring signaling molecules that bind to receptors in the brain and regulate communication between neurons.

The researchers designed a new task called the "sticky-tape test," where mice are placed in a naturalistic environment with a piece of sticky tape. After a single contact with the tape, the mice learned to avoid it in subsequent sessions, demonstrating spontaneous one-shot learning without any rewards or punishments. This type of learning was observed even when the experience was associated with a mildly uncomfortable stimulus, rather than a highly pleasant or unpleasant one.

To investigate the neural mechanisms underlying this learning, the team used a combination of optogenetics, local field potential monitoring, in vivo electrophysiology, and mathematical models. They found that the potentiation occurred in the dorsolateral striatum, but only in mice that experienced short contact with the tape, similar to findings in vitro with endocannabinoid plasticity.

The researchers further confirmed the involvement of endocannabinoids using fiber photometry experiments, knockout mice, and pharmacological approaches to target the endocannabinoid and dopaminergic systems.

Written by urgent.news from Medical Xpress's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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