Our recent findings are reflected in the structure of this repository:

• electrophysiological/: model fits to electrophysiological recordings from IT and V4 cortex
• retrospective/: generate model performance on all experiments in the retrospective dataset
• high-throughput/: collect human behavior on novel dataset and preprocess the results
• in_silico/: examine effects of changing model architecture and trained data on PRC-relevant behavior

Results across each of these studies are synthesized in

• summary/: reporting statistical effects, generating figures, and final manuscript

To generate our main findings and figures, install conda (v4.8.5, tested on an osx-64 platform), import our python environment with

$ conda env create -f conda_environment.yml

and open the jupyter notebook summary/reporting_statistics.ipynb using the mtl_perception kernel.