Our recent findings are reflected in the structure of this repository:
electrophysiological/: model fits to electrophysiological recordings from IT and V4 cortexretrospective/: generate model performance on all experiments in the retrospective datasethigh-throughput/: collect human behavior on novel dataset and preprocess the resultsin_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.