Spike-based local synaptic plasticity: A survey of computational models and neuromorphic circuits

Understand

Understanding how biological neural networks carry out learning using spike-based local plasticity mechanisms can lead to the development of powerful, energy-efficient, and adaptive neuromorphic processing systems.

• A large number of spike-based learning models have recently been proposed following different approaches.
• However, it is difficult to assess if and how they could be mapped onto neuromorphic hardware, and to compare their features and ease of implementation.
• To this end, in this survey, we provide a comprehensive overview of representative brain-inspired synaptic plasticity models and mixed-signal CMOS neuromorphic circuits within a unified framework.