CogNeuro: Difference between revisions
Computational Linguistics and Information Processing
| Line 7: | Line 7: | ||
==Datasets== | ==Datasets== | ||
*LPP-fMRI corpus (English, Chinese, French) | *LPP-fMRI corpus (English, Chinese, French) | ||
**Link | **[https://openneuro.org/datasets/ds003643/versions/2.0.1 Link] | ||
**Data paper | **[https://www.biorxiv.org/content/10.1101/2021.10.02.462875v1.abstract Preprint; Scientific Data paper in press] | ||
*Narratives fMRI corpus | *Narratives fMRI corpus (English) | ||
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link] | **[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link] | ||
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper] | **[https://www.nature.com/articles/s41597-021-01033-3? Data paper] | ||
*NBD fMRI corpus | *NBD fMRI corpus (Dutch) | ||
**Link | **[https://osf.io/utpdy/ Link] | ||
**Data paper | **[http://lrec-conf.org/workshops/lrec2018/W9/pdf/book_of_proceedings.pdf#page=17 Data paper] | ||
*Alice fMRI (English) | *Alice fMRI (English) | ||
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data] | **[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data] | ||
| Line 22: | Line 22: | ||
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link] | **[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link] | ||
**[https://aclanthology.org/2020.lrec-1.15/ Data paper] | **[https://aclanthology.org/2020.lrec-1.15/ Data paper] | ||
*Appleseed MEG | *Appleseed MEG (English) | ||
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link] | **[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link] | ||
**[https://elifesciences.org/articles/72056 Paper] | **[https://elifesciences.org/articles/72056 Paper] | ||
*MASC-MEG | *MASC-MEG (English) | ||
**Link | **[https://osf.io/ag3kj/ Link] | ||
**Paper | **[https://arxiv.org/abs/2208.11488 Paper] | ||
* | *10 hour within-participant MEG narrative (English) | ||
**Link | **[https://data.donders.ru.nl/collections/di/dccn/DSC_3011085.05_995?1 Link] | ||
** | **[https://www.nature.com/articles/s41597-022-01382-7 Data paper] | ||
*Mother of unification studies (MOUS) MEG/fMRI | |||
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011020.09_236?0 Link] | |||
**[https://www.nature.com/articles/s41597-019-0020-y] | |||
*LPP EEG | *LPP EEG | ||
** | **Data collection underway | ||
**[https://aclanthology.org/2020.lincr-1.6/ Data paper] | |||
==Toolkits== | ==Toolkits== | ||
Revision as of 17:12, 25 August 2022
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)
- Narratives fMRI corpus (English)
- NBD fMRI corpus (Dutch)
- Alice fMRI (English)
- Alice EEG (English)
- Appleseed MEG (English)
- MASC-MEG (English)
- 10 hour within-participant MEG narrative (English)
- Mother of unification studies (MOUS) MEG/fMRI
- LPP EEG
- Data collection underway
- Data 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: