https://github.com/alfa-group/neural-program-comprehension
[eLife 2020] "Comprehension of computer code relies primarily on domain-general executive brain regions" by Anna A. Ivanova, Shashank Srikant, Yotaro Sueoka, Hope H. Kean, Riva Dhamala, Una-May O'Reilly, Marina U. Bers, Evelina Fedorenko
Science Score: 23.0%
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Low similarity (10.2%) to scientific vocabulary
Keywords
cognitive-neuroscience
fmri
language-comprehension
language-understanding
programming-languages
python
scratchjr
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[eLife 2020] "Comprehension of computer code relies primarily on domain-general executive brain regions" by Anna A. Ivanova, Shashank Srikant, Yotaro Sueoka, Hope H. Kean, Riva Dhamala, Una-May O'Reilly, Marina U. Bers, Evelina Fedorenko
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Topics
cognitive-neuroscience
fmri
language-comprehension
language-understanding
programming-languages
python
scratchjr
Created almost 6 years ago
· Last pushed about 5 years ago
https://github.com/ALFA-group/neural-program-comprehension/blob/master/
# The Neuroscience of Program Comprehension Resources for the paper **Comprehension of computer code relies primarily on domain-general executive brain regions** by *Anna A. Ivanova, Shashank Srikant, Yotaro Sueoka, Hope H. Kean, Riva Dhamala, Una-May O'Reilly, Marina U. Bers, Evelina Fedorenko* **Paper preprint:** https://www.biorxiv.org/content/10.1101/2020.04.16.045732v1 **Published in eLife, December 2020:** https://elifesciences.org/articles/58906 The labs involved: https://evlab.mit.edu/ https://sites.tufts.edu/devtech/ https://alfagroup.csail.mit.edu/ For additional information, contact annaiv@mit.edu, shash@mit.edu, or evelina9@mit.edu. ## Stimuli ### Python (Experiment 1) All stimuli related to our Python experiments (Experiment 1) are available in `./stimuli/python/`. We have made available stimuli pertaining to the three conditions we test in our work - - `EN`: Codes with variable names in English. - `SENT`: English descriptions of these codes. - `JAP`: Codes with obfuscated variable names. We have shared three files corresponding to these conditions, each containing all 108 stimuli, as well as three folders each containing individual files for the 108 stimuli across the three conditions. The stimuli vary by problem content (math vs. string manipulation) and problem structure (sequential/for loop/if statement), yielding 6 problem types in total. Note that only 72 stimuli (the first 12 for each of the 6 problem types) were used in the study. ### ScratchJr (Experiment 2) The stimuli used in the ScratchJr experiment (Experiment 2) are available in `./stimuli/scratchjr/`. Each folder item contains the `.png` image of the code snippet, two videos (match and mismatch; only one of the videos was shown to each participant), and the audio of the sentence describing the video (the audio was not used for the current experiment). ## Data We make available the data we used for statistical analyses and plotting: - behavioral responses - responses to conditions of interest within MD and language fROIs (`data_fROI*`) - responses to conditions of interest within parcels defined using the code problems > sentence problems contrast (`data_GSS`) - voxelwise spatial correlation between responses in language fROIs (`data_spcorr`) Original `.nii` files are available upon request. ## Analyses We provide the R code that was used for statistical analyses and plot generation. ## Parcels We make available the brain parcels used to define functional systems of interest (MD and language). The parcels were defined using the [GcSS method](https://www.ncbi.nlm.nih.gov/pubmed/20410363) using previously collected data from 197 (MD) and 220 (language) participants. ## Python proficiency test For Experiment 1, we developed a custom Python proficiency test (22 short response questions and 1 long response question, intended to be completed within 1 hour). There was no overlap between the proficiency test questions and the questions presented to participants in the scanner. ## Programming background survey Subjects also responded to a survey at the end of their scans. They reported their proficiency and familiarity with a number of programming related topics. `./survey/` has a PDF of these questions.
Owner
- Name: Anyscale Learning For All (ALFA)
- Login: ALFA-group
- Kind: organization
- Email: alfa-apply@csail.mit.edu
- Location: Cambridge, MA, USA
- Website: https://alfagroup.csail.mit.edu/
- Repositories: 19
- Profile: https://github.com/ALFA-group
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