ABSTRACT
The gap procedure represents one of the most popular paradigms for exploring the connection between learning and timing. Scaling in the general timing model is accomplished by adjusting the weights between the input layer and the middle layer. The portion of the model best suited to the timescale becomes the primary clock, without any explicit change of scale. A trace model could be envisioned with an additional learning process that acts as the equivalent of a thumb over the hole in the bucket, but that thumb would then need to solve the assignment-of-credit problem in order to be able to perform its task. Trace models are particularly suited to neural network modeling and thus can be considered to be the most biologically plausible of the various breeds of timing models. The general timing model consists of three layers: an input layer, a hidden layer, and an output layer.
