Skip to content

Latest commit

 

History

History
20 lines (13 loc) · 1.02 KB

README.md

File metadata and controls

20 lines (13 loc) · 1.02 KB

A deep learning account of medial temporal lobe involvement in perception

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.