Data for "Convergent temperature representations in artificial and biological neural networks"

Data for "Convergent Temperature Representations in Artificial and Biological neural networks" by Haesemeyer M, Schier AF and Engert F, 2019 The corresponding python code is available at: https://github.com/haesemeyer/GradientPrediction All zip files should be extracted in the same folder as the python files. This will create a sub-folder structure for the model data. ZIP File Contents (Note: These are used by the code and not necessarily useful by themselves): model_data.zip Contains tensorflow checkpoints on all naive and fully trained models, test errors during training as well as evolution weights where applicable. model_cluster_assignments.zip For the trained models in model_data.zip the response cluster assignment for each individual unit. zebrafish_data.zip The zebrafish brain and behavior data used in the paper comparisons. This archive also contains the temperature stimulus file stimFile.hdf5 training_data.zip The generated training data used during predictive network training test_data.zip The generated test data used to evaluate predictive network trainingResearch was funded through NIH 1U19NS104653, 5R24NS086601 and 1DP1HD094764 as well as a Simons Collaboration on the Global Brain Research Award (542973