[R] A brain-inspired algorithm that mitigates catastrophic forgetting of artificial and spiking neural networks with low computational cost - Chinese Academy of Sciences 2023

Paper: [https://www.science.org/doi/10.1126/sciadv.adi2947#abstract](https://www.science.org/doi/10.1126/sciadv.adi2947#abstract)

Code: [https://zenodo.org/record/8037309](https://zenodo.org/record/8037309)

Abstract:

>Neuromodulators in the brain act globally at many forms of synaptic plasticity, represented as metaplasticity, which is rarely considered by existing spiking (SNNs) and nonspiking artificial neural networks (ANNs). Here, we report an efficient brain-inspired computing algorithm for SNNs and ANNs, referred to here as neuromodulation-assisted credit assignment (NACA), which uses expectation signals to induce defined levels of neuromodulators to selective synapses, whereby the long-term synaptic potentiation and depression are modified in a nonlinear manner …

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