Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework
Fig 9
Estimated performance during training for networks in the Results.
(A)-(I) Percentage of correct responses. (J) Error in eye position. For each network the relevant figure in the main text and a brief description are given. Black lines are for the networks shown in the main text, while gray lines show the performance for 5 additional networks trained for the same tasks but using different initial weights. Red lines indicate the target performance; training terminated when the mean performance on several (usually 5) evaluations of the validation dataset exceeded the target performance. In I the target performance indicates the minimum, rather than mean, percentage of correct responses across conditions. The number of recurrent units (green) is indicated for each network. The number of minutes (in “real-time”) needed for training (blue) are estimates for a MacBook Pro running OS X Yosemite 10.10.4, with a 2.8 GHz Intel Core i7 CPU and 16 GB 1600 MHz DDR3 memory. GPUs were not used in the training of these networks.