Abstract
There are many attempts to analyze the relationship between functional magnetic resonance imaging (fMRI) data and text stimuli representation in cognitive neuroscience research. Because programming codes are exemplary text stimuli, appropriate code representation for neuroscience research has been actively studied. In this paper, we focus on representing python code for fMRI research through natural language processing (NLP) techniques. We collect 7, 893 python codes of 23 question types from a code competition website and build three different models based on sequence-to-sequence, bag-of-words, and bigram representation. The model is evaluated to classify the types of questions. Finally, the model is applied to classify 108 python codes which were used for a cognitive neuroscience study of fMRI. We are looking forward to analyzing fMRI data with the proposed code representation for understanding how the human brain is active.
Original language | English |
---|---|
Title of host publication | 4th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2022 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 184-187 |
Number of pages | 4 |
ISBN (Electronic) | 9781665458184 |
DOIs | |
Publication status | Published - 2022 |
Event | 4th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2022 - Jeju lsland, Korea, Republic of Duration: 2022 Feb 21 → 2022 Feb 24 |
Publication series
Name | 4th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2022 - Proceedings |
---|
Conference
Conference | 4th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2022 |
---|---|
Country/Territory | Korea, Republic of |
City | Jeju lsland |
Period | 22/2/21 → 22/2/24 |
Bibliographical note
Funding Information:ACKNOWLEDGEMENT This research was supported by the MOTIE (Ministry of Trade, Industry, and Energy) in Korea, under the Fostering Global Talents for Innovative Growth Program (P0008749) supervised by the Korea Institute for Advancement of Technology (KIAT) and National Research Foundation of Korea (NRF-2019R1A2C1084778).
Publisher Copyright:
© 2022 IEEE.
Keywords
- bag-of-words
- bigram
- cognitive neuroscience
- computer code representation
- Functional magnetic resonance imaging
- natural language processing
- sequence-to-sequence
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Electrical and Electronic Engineering