Model performance and dimensionality varied as a function of the amount of data used for training the model. Models were trained in steps of 100,000 trials. Six models with random initialization and random subsets of data were trained per step and all models applied to the same test data as in the main text, making it a total of 78 trained models. For each step, computation of up to two models did not complete on the compute server for technical reasons, making the total between 4 and 6 models per step. Results for each individual model and the average for each step are shown in the Figure. a. Model performance was already high for 100,000 trials as training data but increased with more data, saturating around the final model performance. b. Dimensionality increased steadily with the amount of training data.