Natural neural networks for quantitative sensing of neurochemicals: an artificial neural network analysis

In cell culture, mammalian neurons form fault tolerant, spontaneously active systems with great sensitivity to their chemical environment and generate response profiles that are often concentration and substance specific. In the experiments to be discussed, the response of spontaneously active murine spinal cord cultures coupled to an array of 64 transparent microelectrodes to the glycine receptor blocker strychnine was evaluated. Strychnine reliably generated increased multichannel bursting at 5–20 nM and regular, coordinated bursting above 5 μM. In comparison bicuculline was applied which shows a similar network response but at higher concentrations. By principal component analysis a good discrimination of signals produced by strychnine and by bicuculline was possible. By artificial neural network analysis a quantitative interpretation of the strychnine data was shown for the first time. In particular it could be demonstrated that for subsequent strychnine expositions a quantitative analysis of an unknown strychnine concentration is possible. These results indicate that cultured neuronal networks are practical systems that can be used as a biosensor system for the characterization of a great variety of neuroactive substances.