Figure 4.
Recurrent neural network used to model call recognition in túngara frogs. The network has a recurrent loop between the feature detector and context layers that allows the detection of time-varying stimuli. The stimulus is a matrix of Fourier transform coefficients from a túngara call presented to the input layer one time interval per step. From Phelps & Ryan (1998).