eLife assessment
This work presents a valuable data-driven method to extract the "true" synaptic plasticity rule (or learning rule) operating in a neural circuit from empirical measurements of neural activity. The approach aims to train a generative adversarial network (GAN) to match neural activity measurements in terms of statistics, learning them from the data, rather than being pre-determined by the experimenter. The main conclusion is that the extracted learning rules are not unique, but rather degenerate, meaning that multiple plasticity rules can produce the same neural activity. Although the paper presents a thorough investigation using one learning rule as a case study (the Oja rule), the evidence that the results can be inferred beyond the specific numerical experiments presented in the paper is incomplete.