A single-spike model of predictive coding

Abstract The standard cortical model assumes that the meaning of a neuron's signal is contained in its firing rate. While that model has been used to interpret a voluminous amount of experimental data, it does not address the question of timing, or how recipient neurons can decode this signal in time to predict behavioral results. We propose a model based on coincident firing of large groups of neurons. We show using an example of predictive coding, how the cortex can support vast amounts of non-interfering parallel computation.

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