The study proposes a learning model of brain-like classical conditioned reflexes

The theory of conditional reflexes, discovered and established by Russian neuroscientist Ivan Petrovich Pavlov as a dog model animal, is one of the important foundations of biological system learning theory.
classical conditional reflexes play an important role in biological brain learning, and also provides a biologically feasible mechanism and basis for the study of artificial intelligence learning theory.
nearly 40 years, researchers in brain and neuroscience and artificial intelligence have tried to study and reveal the neuro-computer systems of classical conditional reflex experiments and apply them to artificial intelligence through a fusion of neuroscience experiments and computational modeling research.
, however, these models can only be re-presented and interpreted in a relatively limited number of classical conditional reflection experiments.
Zeng Yi, a researcher at the Brain Intelligence Research Center of the Institute of Automation of the Chinese Academy of Sciences, has made achievements in the field of conditional reflexes by integrating biology, neuroscience and other disciplines, and based on the neural basis of conditional reflexes, that is, the structure and computer system of the brain region, neural circuit, cognitive function, neuron scale, and puts forward a model of the pulsed neural network of brain classic conditional reflexes.
the model integrates the results of biological studies that have reached consensus in the field of conditional reflexes into a brain-like pulsed neural network.
compared with other computational models, the classical conditioned reflex model of brain-like brain can re-create 15 classical conditional reflex experiments proposed in neuroscience and give a reasonable explanation from the computational point of view, which can help to reveal the neural mechanism of the organism to establish conditional reflexes.
addition, the model can be deployed to robots, allowing them to exhibit brain-like classical conditional reflexes like organisms.
Experimentally verified, the model enables the robot to have the ability to generalize speed, that is, in navigation tasks, at lower speeds, the robot learns the trajectory of motion through conditional reflection, at higher speeds, no need to train again to complete navigation tasks.
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