This README.txt file was generated on <20211108> by <Elliot Collins>



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GENERAL INFORMATION

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1. Title of Software: Learning Experiment Files





2. Author Information

First Author Contact Information

    Name: Elliot Collins

    Institution: Carnegie Mellon University

    Email:collinse@uw.edu



Corresponding Author Contact Information

    Name: Marlene Behrmann	

    Institution: Carnegie Mellon University

    Email: behrmann@cmu.edu



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SOFTWARE LICENSE AGREEMENT

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Citations: If you use this data or software for any reason please cite: Collins, E, & Behrmann, M (2020) Exemplar learning reveals the representational origins of expert category perception. Proceeding of the National Academy of Sciences. 117(20), 11167-11177.



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SOFTWARE OVERVIEW

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Directory of Files:



   A. Filename:    NOLearning.zip    

      Short description: This zip file and the one below (B) are nearly identical directories containing the software to run either the novel object (A) or other race face (B) learning experiments from the paper cited above. Each zip file contains a python script which draws stimuli from and prints results to, trial by trial, appropriately named stimuli and results directories respectively. Each directory also contains a TrialLists/ directory which contains a text files naming the specific stimuli to be learned by each subject. 





   B. Filename:    ORFlearning.zip

      Short description:  As above

   

              



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METHODOLOGICAL INFORMATION

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1. Software-specific information:

<create a new entry for each qualifying software program>



Name: NOratings.py, NOtraining.py, ORFratings.py ORFtraining.py (all built and used in the same environment, at the same time with the same requirments)

Version:1

System Requirements: Psychopy environment

Open Source? (Y/N): Y



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2. Equipment-specific information: N/A

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Manufacturer:

Model:



(if applicable)

Embedded Software / Firmware Name:

Embedded Software / Firmware Version:

Additional Notes:



3. Software Execution Instructions



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Python scripts can be opened and run in the psychopy software environment. All of the dependencies are already written into the script and can be run locally. All necessary toolboxes are already included in the psychopy environment. This experiment was run on the most up to date software version available in 2018.



3. Date of software development: 2018