MEASURING NATURAL NEURAL PROCESSING WITH ARTIFICIAL NEURAL NETWORKS
John Hertz, Troels W. Kjær, Emad N. Eskandar, Barry J. Richmond · International Journal of Neural Systems · 1992
We show how to use artificial neural networks as a quantitative tool in studying real neuronal processing in the monkey visual system. Training a network to classify neuronal signals according to the stimulus that elicited them permits us to calculate the information transmitted by these signals. We illustrate this for neurons in the primary visual cortex with measurements of the information transmitted about visual stimuli and for cells in inferior temporal cortex with measurements of information about behavioral context. For the latter neurons we also illustrate how artificial neural networks can be used to model the computation they do.