How experts are different from the brains of nods

, Nov. 25 (Xinhua) -- What is the difference between the brains of experts and beginners who are proficient in a skill? Researchers have recently discovered the difference between animal experiments and machine learning algorithms, and developed new ways to predict animal behavior, demonstrating the potential of artificial intelligence to aid neuroscience research.
Researchers at Calders spring labs in the United States, Columbia University and University College London in the United Kingdom found that when mice went from "nobids" to "experts," their brain cell circuits and neuron activity changed and neural networks became more focused and focused. The findings were recently published in the American Journal of Neurons.
experiment, the researchers trained mice to perform sensory decision-making tasks. The mice first received multiple perceptual stimuli such as flashes and ticks, and then selectively licked one of the three outings to tell the researchers whether the stimuli were high-frequency or low-frequency. If selected correctly, the mice will be rewarded. During this process, neuron changes in mice were recorded by a double photon imaging microscope observation.
researchers found that when mice first started learning, the neurons involved only responded at the moment they made a choice, and when the mice fully mastered the skill, it was as if they were "in the chest" and their neurons began to respond long before time.
to "read" neuron activity, the researchers trained an artificial neural network using machine learning algorithms. The artificial neural network, called the Linear Support Vector Machine, collects several sets of experimental data and associates them with neuron activity. The researchers found that as mice became more skilled at completing tasks, their neural networks became more precise and focused, and when these changes were mapped into this artificial neural network, the mice's next behavior was predicted with up to 90 percent accuracy.