Benchmarking the Connectomes of Caenorhabditis elegans within the Reservoir Computing Framework
Read the original on arXiv Machine Learning →The paper investigates the connectomes of *Caenorhabditis elegans* by implementing them as echo state networks within a reservoir computing framework. Using connectomes derived at different ages and through three distinct measurement methods, the authors benchmark performance on neuro-inspired tasks, comparing biological wiring to randomized null models. Results indicate that biological wiring and bio-informed input/output configurations do not consistently outperform random models, and performance varies significantly with reservoir configuration and connectome derivation.
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