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Updated: Mar 11, 2026

3D Modeling of Dendritic Spines with Synaptic Plasticity
Published on: May 18, 2020
A Cognitive Model Based on Neuromodulated Plasticity
Jing Huang1, Xiaogang Ruan2, Naigong Yu2
1Institute of Artificial Intelligence and Robotics, Beijing University of Technology, Beijing 100124, China; Pilot College, Beijing University of Technology, Beijing 101101, China.
Abstract:
Associative learning, including classical conditioning and operant conditioning, is regarded as the most fundamental type of learning for animals and human beings. Many models have been proposed surrounding classical conditioning or operant conditioning. However, a unified and integrated model to explain the two types of conditioning is much less studied. Here, a model based on neuromodulated synaptic plasticity is presented. The model is bioinspired including multistored memory module and simulated VTA dopaminergic neurons to produce reward signal. The synaptic weights are modified according to the reward signal, which simulates the change of associative strengths in associative learning. The experiment results in real robots prove the suitability and validity of the proposed model.
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