Computation with neuronal cultures: Effects of connectivity modularity on response separation and generalisation in simulations and experiments
Akke Mats Houben, Anna-Christina Haeb, Jordi Garcia-Ojalvo, Jordi Soriano · FENS Forum 2024
Interest in using biological neuronal networks as artificial learning systems has surged [e.g. 1,2,3]. However, networks of biological neurons differ from artificial neural networks: they are intrinsically noisy and have non-trivial physical embeddings. The question thus arises whether biological neurons are usable for artificial intelligence. A basic requirement for a system to be a good learning machine is the capacity to respond distinctly to different inputs, yet reproduce similar activity to similar stimuli. Liquid state [4] and reservoir [5] computing make direct and explicit use of this
ePoster · Neuroscience