CogNeuro
Computational Linguistics and Information Processing
This is a repository that is updated periodically with resources to analyze continuous, naturalistic neuroimaging data with computational tools. It is split into three sections:
- Datasets
- EEG/MEG/fMRI
- Toolkits & Tutorials
- For neuroimaging data analysis
- Relevant Background
- Selected papers, podcasts, talks, course videos, books
Datasets
- LPP-fMRI corpus (English, Chinese, French)
- Link
- Data paper
- Narratives fMRI corpus
- Link
- Data paper
- NBD fMRI corpus
- Link
- Data paper
- Alice fMRI (English)
- Link to whole brain
- Link to ROIs
- Data paper
- Alice EEG (English)
- Link
- Data paper
- Appleseed MEG
- Link
- Paper
- MASC-MEG
- Link
- Paper
- MUC MEG/fMRI
- Link
- Paper
- LPP EEG
- Paper
Toolkits
- Eelbrain for EEG/MEG
- Link
- Paper
- Nilearn for fMRI
- Link to GLM tutorial
- SPM for fMRI
- Link to tutorial
- More: NITRC
Relevant Background
- Papers:
- Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. Link
- Hamilton, L. S., & Huth, A. G. (2020). The revolution will not be controlled: natural stimuli in speech neuroscience. Language, cognition and neuroscience, 35(5), 573-582. Link
- Hale, J. T., Campanelli, L., Li, J., Bhattasali, S., Pallier, C., & Brennan, J. R. (2022). Neurocomputational models of language processing. Annual Review of Linguistics, 8, 427-446. Link
- Podcasts
- Talks:
- Books:
- Course videos: