3 ms·

Yes, I'm not concerned with the computational cost. Reading the paper more carefully, I can't see any obvious weaknesses. The main idea is based on [1]: a brai

• orbifold 6y ago
  They don't address the fundamental issue of BPTT in an RNN model. To my mind this is a much larger block to biological plausibility than how to track the error locally. Besides this has been addressed in various forms in earlier work: - Hochreiter and Schmidhuber present a truncated version of BPTT in the original LSTM paper that tracks part of the error locally and forward in time (https://www.bioinf.jku.at/publications/older/2604.pdf https://www.bioinf.jku.at/publications/older/2604.pdf) - Bellec et al. https://www.nature.com/articles/s41467-020-17236-y https://www.nature.com/articles/s41467-020-17236-y present a similar algorithm that tracks the error with something they call eligibility traces. Despite the title of the paper the method is also applicable to non-spiking RNNs. - Bohnstigl et al. present another solution: https://arxiv.org/pdf/2007.12723.pdf https://arxiv.org/pdf/2007.12723.pdf