Fig 7. Data-driven convolutional network model.

We trained a convolutional neural network to produce a feature space fed to a GLM-like model. In contrast to the VGG-based model, both feature space and readout weights are trained only on the neural data. A. Three-layer architecture with a factorized readout [40] used for comparison with other models. B. Performance of the data driven approach as a function of the number of convolutional layers on held-out data. Three convolutional layers provided the best performance on the validation set. See Methods for details.