Strengths of the afferent synapses from the input population to a typical output neuron during testing.

Results are shown for the model with peaked eye-position gain modulation before training (A) and after training (B), and for the model with sigmoidal eye-position modulation before training (C) and after training (D). The output neurons correspond to those plotted in Fig 3. In each plot, the afferent synapses have been arranged topographically by the preference of the input neuron for retinal location αi and eye-position βj. For the model with sigmoidal gain modulation, there are two input neurons for every combination of retinal preference and eye-position preference, but with opposite eye-position gain. Consequently, the input population has been separated by gain direction. The portion of each plot to the left of the white dashed line corresponds to input neurons with positive gain κj > 0, while the portion of each plot to the right of the white dashed line corresponds to those input neurons with negative gain κj (B) that the output neuron in the trained network with peaked gain modulation has developed a diagonal weight structure, which is consistent with a learned response to a particular location within the head-centred frame of reference. In contrast, subplot (D) shows that the output neuron in the trained network with sigmoidal (monotonic) gain modulation has developed a more horizontal weight structure, which is consistent with a learned response to a specific location within the eye-centred reference frame.