https://wiki.umiacs.umd.edu/clip/api.php?action=feedcontributions&user=Shohini&feedformat=atomCLIP - User contributions [en]2024-03-28T21:58:54ZUser contributionsMediaWiki 1.39.6https://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1178CogNeuro2022-08-25T17:35:26Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: Naturalistic fMRI/EEG/MEG <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**[https://openneuro.org/datasets/ds003643/versions/2.0.1 Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.10.02.462875v1.abstract Preprint; Scientific Data paper in press]<br />
*Narratives fMRI corpus (English)<br />
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link]<br />
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper]<br />
*NBD fMRI corpus (Dutch)<br />
**[https://osf.io/utpdy/ Link]<br />
**[http://lrec-conf.org/workshops/lrec2018/W9/pdf/book_of_proceedings.pdf#page=17 Data paper]<br />
*Alice fMRI (English)<br />
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data]<br />
**[https://sites.lsa.umich.edu/cnllab/2016/06/11/data-sharing-fmri-timecourses-story-listening/ Link to ROIs]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Alice EEG (English)<br />
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Appleseed MEG (English)<br />
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link]<br />
**[https://elifesciences.org/articles/72056 Paper]<br />
*MASC-MEG (English)<br />
**[https://osf.io/ag3kj/ Link]<br />
**[https://arxiv.org/abs/2208.11488 Preprint]<br />
*10 hour within-participant MEG narrative (English)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011085.05_995?1 Link]<br />
**[https://www.nature.com/articles/s41597-022-01382-7 Data paper]<br />
*Mother of unification studies (MOUS) MEG/fMRI (Dutch)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011020.09_236?0 Link]<br />
**[https://www.nature.com/articles/s41597-019-0020-y Data paper]<br />
*LPP EEG (26 languages)<br />
**Data collection underway<br />
**[https://aclanthology.org/2020.lincr-1.6/ Data paper]<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG analysis (Python)<br />
**[https://eelbrain.readthedocs.io/en/stable/ Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.08.01.454687v1 Paper]<br />
**Tutorial TBD<br />
*SPM for fMRI analysis (Matlab)<br />
**[https://andysbrainbook.readthedocs.io/en/latest/SPM/SPM_Overview.html SPM Analysis]; read Poldrack first!<br />
**[https://andysbrainbook.readthedocs.io/en/latest/PM/PM_Overview.html SPM Parametric Modulation]<br />
**[https://andysbrainbook.readthedocs.io/en/latest/Stats/Stats_Overview.html Stats for fMRI]<br />
*fMRI image viewer (for figures)<br />
**[https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes FSLeyes]<br />
**[https://ric.uthscsa.edu/mango/ Mango]<br />
*Nilearn for fMRI (Python)<br />
**[https://nilearn.github.io/stable/glm/index.html#glm GLM analysis] <br />
**[https://nilearn.github.io/stable/auto_examples/00_tutorials/plot_decoding_tutorial.html Decoding]<br />
**[https://nilearn.github.io/stable/plotting/index.html#plotting Plotting Brain Images]<br />
*Neuroscount<br />
**[https://neuroscout.org/ Link]<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1177CogNeuro2022-08-25T17:34:37Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: Naturalistic fMRI/EEG/MEG <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**[https://openneuro.org/datasets/ds003643/versions/2.0.1 Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.10.02.462875v1.abstract Preprint; Scientific Data paper in press]<br />
*Narratives fMRI corpus (English)<br />
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link]<br />
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper]<br />
*NBD fMRI corpus (Dutch)<br />
**[https://osf.io/utpdy/ Link]<br />
**[http://lrec-conf.org/workshops/lrec2018/W9/pdf/book_of_proceedings.pdf#page=17 Data paper]<br />
*Alice fMRI (English)<br />
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data]<br />
**[https://sites.lsa.umich.edu/cnllab/2016/06/11/data-sharing-fmri-timecourses-story-listening/ Link to ROIs]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Alice EEG (English)<br />
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Appleseed MEG (English)<br />
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link]<br />
**[https://elifesciences.org/articles/72056 Paper]<br />
*MASC-MEG (English)<br />
**[https://osf.io/ag3kj/ Link]<br />
**[https://arxiv.org/abs/2208.11488 Preprint]<br />
*10 hour within-participant MEG narrative (English)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011085.05_995?1 Link]<br />
**[https://www.nature.com/articles/s41597-022-01382-7 Data paper]<br />
*Mother of unification studies (MOUS) MEG/fMRI (Dutch)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011020.09_236?0 Link]<br />
**[https://www.nature.com/articles/s41597-019-0020-y Data paper]<br />
*LPP EEG (26 languages)<br />
**Data collection underway<br />
**[https://aclanthology.org/2020.lincr-1.6/ Data paper]<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**[https://eelbrain.readthedocs.io/en/stable/ Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.08.01.454687v1 Paper]<br />
**Tutorial TBD<br />
*SPM for fMRI analysis<br />
**[https://andysbrainbook.readthedocs.io/en/latest/SPM/SPM_Overview.html SPM Analysis]; read Poldrack first!<br />
**[https://andysbrainbook.readthedocs.io/en/latest/PM/PM_Overview.html SPM Parametric Modulation]<br />
**[https://andysbrainbook.readthedocs.io/en/latest/Stats/Stats_Overview.html Stats for fMRI]<br />
*fMRI image viewer (for figures)<br />
**[https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes FSLeyes]<br />
**[https://ric.uthscsa.edu/mango/ Mango]<br />
*Nilearn for fMRI<br />
**[https://nilearn.github.io/stable/glm/index.html#glm GLM analysis] <br />
**[https://nilearn.github.io/stable/auto_examples/00_tutorials/plot_decoding_tutorial.html Decoding]<br />
**[https://nilearn.github.io/stable/plotting/index.html#plotting Plotting Brain Images]<br />
*Neuroscount<br />
**[https://neuroscout.org/ Link]<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1176CogNeuro2022-08-25T17:27:05Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**[https://openneuro.org/datasets/ds003643/versions/2.0.1 Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.10.02.462875v1.abstract Preprint; Scientific Data paper in press]<br />
*Narratives fMRI corpus (English)<br />
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link]<br />
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper]<br />
*NBD fMRI corpus (Dutch)<br />
**[https://osf.io/utpdy/ Link]<br />
**[http://lrec-conf.org/workshops/lrec2018/W9/pdf/book_of_proceedings.pdf#page=17 Data paper]<br />
*Alice fMRI (English)<br />
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data]<br />
**[https://sites.lsa.umich.edu/cnllab/2016/06/11/data-sharing-fmri-timecourses-story-listening/ Link to ROIs]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Alice EEG (English)<br />
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Appleseed MEG (English)<br />
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link]<br />
**[https://elifesciences.org/articles/72056 Paper]<br />
*MASC-MEG (English)<br />
**[https://osf.io/ag3kj/ Link]<br />
**[https://arxiv.org/abs/2208.11488 Preprint]<br />
*10 hour within-participant MEG narrative (English)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011085.05_995?1 Link]<br />
**[https://www.nature.com/articles/s41597-022-01382-7 Data paper]<br />
*Mother of unification studies (MOUS) MEG/fMRI (Dutch)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011020.09_236?0 Link]<br />
**[https://www.nature.com/articles/s41597-019-0020-y Data paper]<br />
*LPP EEG (26 languages)<br />
**Data collection underway<br />
**[https://aclanthology.org/2020.lincr-1.6/ Data paper]<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**[https://eelbrain.readthedocs.io/en/stable/ Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.08.01.454687v1 Paper]<br />
**Tutorial TBD<br />
*SPM for fMRI<br />
**[https://andysbrainbook.readthedocs.io/en/latest/SPM/SPM_Overview.html SPM Analysis]; read Poldrack first!<br />
**[https://andysbrainbook.readthedocs.io/en/latest/PM/PM_Overview.html SPM Parametric Modulation]<br />
**[https://andysbrainbook.readthedocs.io/en/latest/Stats/Stats_Overview.html Stats for fMRI]<br />
*Nilearn for fMRI<br />
**[https://nilearn.github.io/stable/glm/index.html#glm GLM analysis] <br />
**[https://nilearn.github.io/stable/auto_examples/00_tutorials/plot_decoding_tutorial.html Decoding]<br />
<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1175CogNeuro2022-08-25T17:17:43Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**[https://openneuro.org/datasets/ds003643/versions/2.0.1 Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.10.02.462875v1.abstract Preprint; Scientific Data paper in press]<br />
*Narratives fMRI corpus (English)<br />
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link]<br />
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper]<br />
*NBD fMRI corpus (Dutch)<br />
**[https://osf.io/utpdy/ Link]<br />
**[http://lrec-conf.org/workshops/lrec2018/W9/pdf/book_of_proceedings.pdf#page=17 Data paper]<br />
*Alice fMRI (English)<br />
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data]<br />
**[https://sites.lsa.umich.edu/cnllab/2016/06/11/data-sharing-fmri-timecourses-story-listening/ Link to ROIs]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Alice EEG (English)<br />
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Appleseed MEG (English)<br />
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link]<br />
**[https://elifesciences.org/articles/72056 Paper]<br />
*MASC-MEG (English)<br />
**[https://osf.io/ag3kj/ Link]<br />
**[https://arxiv.org/abs/2208.11488 Preprint]<br />
*10 hour within-participant MEG narrative (English)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011085.05_995?1 Link]<br />
**[https://www.nature.com/articles/s41597-022-01382-7 Data paper]<br />
*Mother of unification studies (MOUS) MEG/fMRI (Dutch)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011020.09_236?0 Link]<br />
**[https://www.nature.com/articles/s41597-019-0020-y Data paper]<br />
*LPP EEG (26 languages)<br />
**Data collection underway<br />
**[https://aclanthology.org/2020.lincr-1.6/ Data paper]<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**[https://eelbrain.readthedocs.io/en/stable/ Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.08.01.454687v1 Paper]<br />
**Tutorial TBD<br />
*Nilearn for fMRI<br />
**[https://nilearn.github.io/stable/glm/index.html#glm GLM analysis] <br />
**[https://nilearn.github.io/stable/auto_examples/00_tutorials/plot_decoding_tutorial.html Decoding]<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1174CogNeuro2022-08-25T17:16:42Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**[https://openneuro.org/datasets/ds003643/versions/2.0.1 Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.10.02.462875v1.abstract Preprint; Scientific Data paper in press]<br />
*Narratives fMRI corpus (English)<br />
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link]<br />
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper]<br />
*NBD fMRI corpus (Dutch)<br />
**[https://osf.io/utpdy/ Link]<br />
**[http://lrec-conf.org/workshops/lrec2018/W9/pdf/book_of_proceedings.pdf#page=17 Data paper]<br />
*Alice fMRI (English)<br />
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data]<br />
**[https://sites.lsa.umich.edu/cnllab/2016/06/11/data-sharing-fmri-timecourses-story-listening/ Link to ROIs]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Alice EEG (English)<br />
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Appleseed MEG (English)<br />
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link]<br />
**[https://elifesciences.org/articles/72056 Paper]<br />
*MASC-MEG (English)<br />
**[https://osf.io/ag3kj/ Link]<br />
**[https://arxiv.org/abs/2208.11488 Preprint]<br />
*10 hour within-participant MEG narrative (English)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011085.05_995?1 Link]<br />
**[https://www.nature.com/articles/s41597-022-01382-7 Data paper]<br />
*Mother of unification studies (MOUS) MEG/fMRI (Dutch)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011020.09_236?0 Link]<br />
**[https://www.nature.com/articles/s41597-019-0020-y Data paper]<br />
*LPP EEG (26 languages)<br />
**Data collection underway<br />
**[https://aclanthology.org/2020.lincr-1.6/ Data paper]<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**[https://eelbrain.readthedocs.io/en/stable/ Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.08.01.454687v1 Paper]<br />
**Tutorial TBD<br />
*Nilearn for fMRI<br />
**[https://nilearn.github.io/stable/glm/index.html#glm GLM analysis] <br />
**[https://nilearn.github.io/stable/auto_examples/00_tutorials/plot_decoding_tutorial.html Decoding]<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1173CogNeuro2022-08-25T17:16:21Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**[https://openneuro.org/datasets/ds003643/versions/2.0.1 Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.10.02.462875v1.abstract Preprint; Scientific Data paper in press]<br />
*Narratives fMRI corpus (English)<br />
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link]<br />
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper]<br />
*NBD fMRI corpus (Dutch)<br />
**[https://osf.io/utpdy/ Link]<br />
**[http://lrec-conf.org/workshops/lrec2018/W9/pdf/book_of_proceedings.pdf#page=17 Data paper]<br />
*Alice fMRI (English)<br />
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data]<br />
**[https://sites.lsa.umich.edu/cnllab/2016/06/11/data-sharing-fmri-timecourses-story-listening/ Link to ROIs]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Alice EEG (English)<br />
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Appleseed MEG (English)<br />
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link]<br />
**[https://elifesciences.org/articles/72056 Paper]<br />
*MASC-MEG (English)<br />
**[https://osf.io/ag3kj/ Link]<br />
**[https://arxiv.org/abs/2208.11488 Paper]<br />
*10 hour within-participant MEG narrative (English)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011085.05_995?1 Link]<br />
**[https://www.nature.com/articles/s41597-022-01382-7 Data paper]<br />
*Mother of unification studies (MOUS) MEG/fMRI (Dutch)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011020.09_236?0 Link]<br />
**[https://www.nature.com/articles/s41597-019-0020-y Data paper]<br />
*LPP EEG (26 languages)<br />
**Data collection underway<br />
**[https://aclanthology.org/2020.lincr-1.6/ Data paper]<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**[https://eelbrain.readthedocs.io/en/stable/ Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.08.01.454687v1 Paper]<br />
**Tutorial TBD<br />
*Nilearn for fMRI<br />
**[https://nilearn.github.io/stable/glm/index.html#glm GLM analysis] <br />
**[https://nilearn.github.io/stable/auto_examples/00_tutorials/plot_decoding_tutorial.html Decoding]<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1172CogNeuro2022-08-25T17:15:57Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**[https://openneuro.org/datasets/ds003643/versions/2.0.1 Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.10.02.462875v1.abstract Preprint; Scientific Data paper in press]<br />
*Narratives fMRI corpus (English)<br />
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link]<br />
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper]<br />
*NBD fMRI corpus (Dutch)<br />
**[https://osf.io/utpdy/ Link]<br />
**[http://lrec-conf.org/workshops/lrec2018/W9/pdf/book_of_proceedings.pdf#page=17 Data paper]<br />
*Alice fMRI (English)<br />
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data]<br />
**[https://sites.lsa.umich.edu/cnllab/2016/06/11/data-sharing-fmri-timecourses-story-listening/ Link to ROIs]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Alice EEG (English)<br />
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Appleseed MEG (English)<br />
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link]<br />
**[https://elifesciences.org/articles/72056 Paper]<br />
*MASC-MEG (English)<br />
**[https://osf.io/ag3kj/ Link]<br />
**[https://arxiv.org/abs/2208.11488 Paper]<br />
*10 hour within-participant MEG narrative (English)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011085.05_995?1 Link]<br />
**[https://www.nature.com/articles/s41597-022-01382-7 Data paper]<br />
*Mother of unification studies (MOUS) MEG/fMRI (Dutch)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011020.09_236?0 Link]<br />
**[https://www.nature.com/articles/s41597-019-0020-y]<br />
*LPP EEG (26 languages)<br />
**Data collection underway<br />
**[https://aclanthology.org/2020.lincr-1.6/ Data paper]<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**[https://eelbrain.readthedocs.io/en/stable/ Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.08.01.454687v1 Paper]<br />
**Tutorial TBD<br />
*Nilearn for fMRI<br />
**[https://nilearn.github.io/stable/glm/index.html#glm GLM analysis] <br />
**[https://nilearn.github.io/stable/auto_examples/00_tutorials/plot_decoding_tutorial.html Decoding]<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1171CogNeuro2022-08-25T17:13:42Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**[https://openneuro.org/datasets/ds003643/versions/2.0.1 Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.10.02.462875v1.abstract Preprint; Scientific Data paper in press]<br />
*Narratives fMRI corpus (English)<br />
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link]<br />
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper]<br />
*NBD fMRI corpus (Dutch)<br />
**[https://osf.io/utpdy/ Link]<br />
**[http://lrec-conf.org/workshops/lrec2018/W9/pdf/book_of_proceedings.pdf#page=17 Data paper]<br />
*Alice fMRI (English)<br />
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data]<br />
**[https://sites.lsa.umich.edu/cnllab/2016/06/11/data-sharing-fmri-timecourses-story-listening/ Link to ROIs]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Alice EEG (English)<br />
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Appleseed MEG (English)<br />
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link]<br />
**[https://elifesciences.org/articles/72056 Paper]<br />
*MASC-MEG (English)<br />
**[https://osf.io/ag3kj/ Link]<br />
**[https://arxiv.org/abs/2208.11488 Paper]<br />
*10 hour within-participant MEG narrative (English)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011085.05_995?1 Link]<br />
**[https://www.nature.com/articles/s41597-022-01382-7 Data paper]<br />
*Mother of unification studies (MOUS) MEG/fMRI (Dutch)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011020.09_236?0 Link]<br />
**[https://www.nature.com/articles/s41597-019-0020-y]<br />
*LPP EEG (26 languages)<br />
**Data collection underway<br />
**[https://aclanthology.org/2020.lincr-1.6/ Data paper]<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1170CogNeuro2022-08-25T17:12:16Z<p>Shohini: /* Datasets */</p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**[https://openneuro.org/datasets/ds003643/versions/2.0.1 Link]<br />
**[https://www.biorxiv.org/content/10.1101/2021.10.02.462875v1.abstract Preprint; Scientific Data paper in press]<br />
*Narratives fMRI corpus (English)<br />
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link]<br />
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper]<br />
*NBD fMRI corpus (Dutch)<br />
**[https://osf.io/utpdy/ Link]<br />
**[http://lrec-conf.org/workshops/lrec2018/W9/pdf/book_of_proceedings.pdf#page=17 Data paper]<br />
*Alice fMRI (English)<br />
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data]<br />
**[https://sites.lsa.umich.edu/cnllab/2016/06/11/data-sharing-fmri-timecourses-story-listening/ Link to ROIs]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Alice EEG (English)<br />
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Appleseed MEG (English)<br />
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link]<br />
**[https://elifesciences.org/articles/72056 Paper]<br />
*MASC-MEG (English)<br />
**[https://osf.io/ag3kj/ Link]<br />
**[https://arxiv.org/abs/2208.11488 Paper]<br />
*10 hour within-participant MEG narrative (English)<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011085.05_995?1 Link]<br />
**[https://www.nature.com/articles/s41597-022-01382-7 Data paper]<br />
*Mother of unification studies (MOUS) MEG/fMRI<br />
**[https://data.donders.ru.nl/collections/di/dccn/DSC_3011020.09_236?0 Link]<br />
**[https://www.nature.com/articles/s41597-019-0020-y]<br />
*LPP EEG<br />
**Data collection underway<br />
**[https://aclanthology.org/2020.lincr-1.6/ Data paper]<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1169CogNeuro2022-08-25T16:52:21Z<p>Shohini: /* Datasets */</p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**[https://openneuro.org/datasets/ds002345/versions/1.1.4 Link]<br />
**[https://www.nature.com/articles/s41597-021-01033-3? Data paper]<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**[https://openneuro.org/datasets/ds002322/versions/1.0.4 Link to whole brain data]<br />
**[https://sites.lsa.umich.edu/cnllab/2016/06/11/data-sharing-fmri-timecourses-story-listening/ Link to ROIs]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Alice EEG (English)<br />
**[https://deepblue.lib.umich.edu/data/concern/data_sets/bg257f92t Link]<br />
**[https://aclanthology.org/2020.lrec-1.15/ Data paper]<br />
*Appleseed MEG<br />
**[https://datadryad.org/stash/dataset/doi:10.5061/dryad.nvx0k6dv0 Link]<br />
**[https://elifesciences.org/articles/72056 Paper]<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1168CogNeuro2022-08-25T16:44:19Z<p>Shohini: /* Relevant Background */</p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**Link<br />
**Data paper<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**Link to whole brain<br />
**Link to ROIs<br />
**Data paper<br />
*Alice EEG (English)<br />
**Link<br />
**Data paper<br />
*Appleseed MEG<br />
**Link<br />
**Paper<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Brennan, J. (2016). Naturalistic sentence comprehension in the brain. Language and Linguistics Compass, 10(7), 299-313. [https://compass.onlinelibrary.wiley.com/doi/abs/10.1111/lnc3.12198?casa_token=I7XqafbB33gAAAAA%3AnjBW3gi-S8SrssJjV3DL4eakxrvrclLYk7nnPxWdZgxrd6JVOhFjFIkNWKXXig-T3-EpZgFDJWOlz_o Link]<br />
**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. [https://www.tandfonline.com/doi/pdf/10.1080/23273798.2018.1499946 Link]<br />
**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. [https://www.annualreviews.org/doi/abs/10.1146/annurev-linguistics-051421-020803?casa_token=JXxXJu6VZ-gAAAAA%3A3r_TXUVNJuMp0rEX9TuEBK-wV4CAwbwdQxFG-EKCm26MZXSw4VXEOinDH0-1m-WdqnqSZFJEnniD&journalCode=linguistics Link]<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1167CogNeuro2022-08-25T16:41:48Z<p>Shohini: /* Relevant Background */</p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**Link<br />
**Data paper<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**Link to whole brain<br />
**Link to ROIs<br />
**Data paper<br />
*Alice EEG (English)<br />
**Link<br />
**Data paper<br />
*Appleseed MEG<br />
**Link<br />
**Paper<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Naturalistic sentence comprehension<br />
**The revolution will not be controlled<br />
**Neurocomputational Models of Language Processing<br />
*Podcasts<br />
**[https://braininspired.co/podcast/47/ Brain Inspired 047: David Poeppel - Wrong in interesting ways]<br />
**[https://braininspired.co/podcast/53/ Brain Inspired 053: Jonathan Brennan - Linguistics in Minds and Machines]<br />
**[https://braininspired.co/podcast/144/ Brain Inspired 144: Emily Bender & Ev Federenko - Large Language Models]<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1166CogNeuro2022-08-25T16:38:20Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
==Datasets==<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**Link<br />
**Data paper<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**Link to whole brain<br />
**Link to ROIs<br />
**Data paper<br />
*Alice EEG (English)<br />
**Link<br />
**Data paper<br />
*Appleseed MEG<br />
**Link<br />
**Paper<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
<br />
==Toolkits==<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
==Relevant Background==<br />
*Papers:<br />
**Naturalistic sentence comprehension<br />
**The revolution will not be controlled<br />
**Neurocomputational Models of Language Processing<br />
*Podcasts<br />
**Brain Inspired podcast with Brennan<br />
**Brain Inspired podcast with Ev Federenko & Emily Bender<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1165CogNeuro2022-08-25T16:35:34Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
'''Datasets'''<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**Link<br />
**Data paper<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**Link to whole brain<br />
**Link to ROIs<br />
**Data paper<br />
*Alice EEG (English)<br />
**Link<br />
**Data paper<br />
*Appleseed MEG<br />
**Link<br />
**Paper<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
<br />
'''Toolkits'''<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
'''Relevant Background'''<br />
*Papers:<br />
**Naturalistic sentence comprehension<br />
**The revolution will not be controlled<br />
**Neurocomputational Models of Language Processing<br />
*Podcasts<br />
**Brain Inspired podcast with Brennan<br />
**Brain Inspired podcast with Ev Federenko & Emily Bender<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack: Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Steven Luck: An Introduction to the Event-Related Potential Technique]<br />
**[https://www.routledge.com/Cognitive-Neuroscience-of-Language/Kemmerer/p/book/9781848726215 David Kemmerer: Cognitive Neuroscience of Language]<br />
**[https://www.indiebound.org/book/9780198814764 Jonathan Brennan: Language and the Brain - A Slim Guide to Neurolinguistics]<br />
**[https://mitpress.mit.edu/9780262543262/neurolinguistics/ Giosuè Baggio: Neurolinguistics]<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1164CogNeuro2022-08-25T16:29:30Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
'''Datasets'''<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**Link<br />
**Data paper<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**Link to whole brain<br />
**Link to ROIs<br />
**Data paper<br />
*Alice EEG (English)<br />
**Link<br />
**Data paper<br />
*Appleseed MEG<br />
**Link<br />
**Paper<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
<br />
'''Toolkits'''<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
*SPM for fMRI<br />
**Link to tutorial<br />
*More: [https://www.nitrc.org/top/toplist.php?type=downloads NITRC]<br />
<br />
<br />
'''Relevant Background'''<br />
*Papers:<br />
**Naturalistic sentence comprehension<br />
**The revolution will not be controlled<br />
**Neurocomputational Models of Language Processing<br />
*Podcasts<br />
**Brain Inspired podcast with Brennan<br />
**Brain Inspired podcast with Ev Federenko & Emily Bender<br />
*Talks:<br />
**[http://nancysbraintalks.mit.edu/video/nancys-ted-talk-neural-portrait-human-mind Nancy's Kanwisher's TED talk: A Neural Portrait of the Human Mind]<br />
**[https://www.mpi.nl/events/neurobiology-language-key-issues-and-ways-forward/videos Jonathan Brennan: Building bridges between computation and implementation for natural language understanding]<br />
**[https://www.youtube.com/watch?v=YxAlcQKsgJc Laura Gwilliams: Towards a mechanistic account of speech comprehension]<br />
*Books:<br />
**[https://sites.google.com/site/fmridataanalysis/home Russel Poldrack's Handbook of Functional MRI Analysis]<br />
**[https://mitpress.mit.edu/9780262122771/ Luck's An Introduction to the Event-Related Potential Technique]<br />
**Cognitive Neuroscience of Language book<br />
**Brennan book<br />
**Baggio book<br />
*Course videos:<br />
**[https://www.youtube.com/playlist?list=PLwW-nea-Z6h-TiG0rBIviCQ5XaTyGq5WQ Neural Bases of Language through NYU]<br />
**[https://ocw.mit.edu/courses/9-13-the-human-brain-spring-2019/ The Human Brain course through MIT]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1163CogNeuro2022-08-25T16:02:12Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
'''Datasets'''<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**Link<br />
**Data paper<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**Link to whole brain<br />
**Link to ROIs<br />
**Data paper<br />
*Alice EEG (English)<br />
**Link<br />
**Data paper<br />
*Appleseed MEG<br />
**Link<br />
**Paper<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
<br />
'''Toolkits'''<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
<br />
<br />
'''Relevant Background'''<br />
*Papers:<br />
**Naturalistic sentence comprehension<br />
**The revolution will not be controlled<br />
**Neurocomputational Models of Language Processing<br />
*Podcasts<br />
**Brain Inspired podcast with Brennan<br />
**Brain Inspired podcast with Ev Federenko & Emily Bender<br />
*Talks:<br />
**Nancy TED talk<br />
**Brennan talk<br />
**Laura Gwilliams talk<br />
*Books:<br />
**Cognitive Neuroscience of Language book<br />
**Poldrack book for fMRI analysis<br />
**Brennan book<br />
**Baggio book<br />
*Course videos:<br />
**Neural Bases of Language course videos<br />
**Nancy Kanwisher The Human Brain course</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1162CogNeuro2022-08-25T15:59:35Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Background:Selected papers, podcasts, talks, course videos, books <br />
<br />
<br />
'''Datasets'''<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**Link<br />
**Data paper<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**Link to whole brain<br />
**Link to ROIs<br />
**Data paper<br />
*Alice EEG (English)<br />
**Link<br />
**Data paper<br />
*Appleseed MEG<br />
**Link<br />
**Paper<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
<br />
'''Toolkits'''<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
<br />
<br />
'''Relevant Papers/Podcast/Videos'''<br />
*Naturalistic sentence comprehension<br />
*The revolution will not be controlled<br />
*Neurocomputational Models of Language Processing<br />
*Cognitive Neuroscience of Language book<br />
*Poldrack book for fMRI analysis<br />
*Neural Bases of Language course videos<br />
*Nancy Kanwisher The Human Brain course<br />
*Brain Inspired podcast with Brennan<br />
*Brain Inspired podcast with Ev Federenko & Emily Bender<br />
*Nancy TED talk</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1161CogNeuro2022-08-25T15:43:41Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Papers & Podcasts :Selected for background knowledge <br />
<br />
<br />
'''Datasets'''<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**Link<br />
**Data paper<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**Link to whole brain<br />
**Link to ROIs<br />
**Data paper<br />
*Alice EEG (English)<br />
**Link<br />
**Data paper<br />
*Appleseed MEG<br />
**Link<br />
**Paper<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
<br />
'''Toolkits'''<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
<br />
<br />
'''Relevant Papers/Podcast/Videos'''<br />
*Naturalistic sentence comprehension<br />
*The revolution will not be controlled<br />
*Neurocomputational Models of Language Processing<br />
*Cognitive Neuroscience of Language book<br />
*Poldrack book for fMRI analysis<br />
*Neural Bases of Language course videos<br />
*Nancy Kanwisher The Human Brain course<br />
*Brain Inspired podcast with Brennan<br />
*Brain Inspired podcast with Ev Federenko & Emily Bender<br />
*Nancy TED talk</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1160CogNeuro2022-08-25T15:41:09Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Papers & Podcasts :Selected for background knowledge <br />
<br />
<br />
'''Datasets'''<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**Link<br />
**Data paper<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**Link to whole brain<br />
**Link to ROIs<br />
**Data paper<br />
*Alice EEG (English)<br />
**Link<br />
**Data paper<br />
*Appleseed MEG<br />
**Link<br />
**Paper<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
<br />
'''Toolkits'''<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
<br />
<br />
'''Relevant Papers/Podcast/Videos'''<br />
*Naturalistic sentence comprehension<br />
*The revolution will not be controlled<br />
*Neurocomputational Models of Language Processing<br />
*Cognitive Neuroscience of Language book<br />
*Poldrack book for fMRI analysis<br />
*Neural Bases of Language course videos<br />
*Nancy Kanwisher The Human Brain course<br />
*Brain Inspired podcast with Brennan<br />
*Brain Inspired podcast with Ev Federenko & Emily Bender</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1159CogNeuro2022-08-25T15:38:38Z<p>Shohini: </p>
<hr />
<div>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: <br />
;Datasets: EEG/MEG/fMRI <br />
;Toolkits & Tutorials :For neuroimaging data analysis <br />
;Relevant Papers & Podcasts :Selected for background knowledge <br />
<br />
<br />
'''Datasets'''<br />
*LPP-fMRI corpus (English, Chinese, French)<br />
**Link<br />
**Data paper<br />
*Narratives fMRI corpus<br />
**Link<br />
**Data paper<br />
*NBD fMRI corpus<br />
**Link<br />
**Data paper<br />
*Alice fMRI (English)<br />
**Link to whole brain<br />
**Link to ROIs<br />
**Data paper<br />
*Alice EEG (English)<br />
**Link<br />
**Data paper<br />
*Appleseed MEG<br />
**Link<br />
**Paper<br />
*MASC-MEG<br />
**Link<br />
**Paper<br />
*MUC MEG/fMRI<br />
**Link<br />
**Paper<br />
*LPP EEG<br />
**Paper<br />
<br />
<br />
'''Toolkits'''<br />
*Eelbrain for EEG/MEG<br />
**Link<br />
**Paper<br />
*Nilearn for fMRI<br />
**Link to GLM tutorial<br />
<br />
<br />
'''Relevant Papers/Podcast/Videos'''<br />
*Naturalistic sentence comprehension<br />
*The revolution will not be controlled<br />
*Neurocomputational Models of Language Processing<br />
*Cognitive Neuroscience of Language book<br />
*Poldrack book for fMRI analysis<br />
*Neural Bases of Language course videos<br />
*Brain Inspired podcast with Brennan<br />
*Brain Inspired podcast with Ev Federenko & Emily Bender</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=CogNeuro&diff=1158CogNeuro2022-08-25T15:26:19Z<p>Shohini: Created page with "This is a repository that is updated periodically with resources to analyze continuous, naturalistic neuroimaging data with computational tools. It is split into three section..."</p>
<hr />
<div>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 (for neuroimaging data analysis); Relevant Papers & Podcasts (selected for background knowledge); <br />
<br />
Datasets:<br />
<br />
<br />
Toolkits:<br />
<br />
<br />
Relevant Papers:</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=Context&diff=1157Context2022-08-25T15:21:11Z<p>Shohini: </p>
<hr />
<div>'''Investigating Context'''<br />
<br />
<br />
Through fMRI and MEG studies, the goal of this project is to investigate the role of context during naturalistic language comprehension. Utilizing language models and topic models, we are examining how they can represent different sources of contextual knowledge and embody cognitive hypotheses, both during speech perception and during sentence processing.<br />
<br />
'''Recent Papers'''<br />
<br />
Brodbeck, C., Bhattasali, S., Heredia, A. A. C., Resnik, P., Simon, J. Z., & Lau, E. (2022). Parallel processing in speech perception with local and global representations of linguistic context. elife, 11, e72056. [https://elifesciences.org/articles/72056.pdf Link]<br />
<br />
Bhattasali, S., & Resnik, P. (2021). Using surprisal and fMRI to map the neural bases of broad and local contextual prediction during natural language comprehension. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (pp. 3786-3798). [https://aclanthology.org/2021.findings-acl.332.pdf Link]<br />
<br />
<br />
<br />
Resources for computational cognitive neuroscience of language work can be found here:<br />
[[CogNeuro]]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=Context&diff=1156Context2022-08-25T15:19:05Z<p>Shohini: </p>
<hr />
<div>'''Investigating Context'''<br />
<br />
<br />
Through fMRI and MEG studies, the goal of this project is to investigate the role of context during naturalistic language comprehension. Utilizing language models and topic models, we are examining how they can represent different sources of contextual knowledge and embody cognitive hypotheses, both during speech perception and during sentence processing.<br />
<br />
'''Recent Papers'''<br />
<br />
Brodbeck, C., Bhattasali, S., Heredia, A. A. C., Resnik, P., Simon, J. Z., & Lau, E. (2022). Parallel processing in speech perception with local and global representations of linguistic context. elife, 11, e72056. [https://elifesciences.org/articles/72056.pdf Link]<br />
<br />
Bhattasali, S., & Resnik, P. (2021). Using surprisal and fMRI to map the neural bases of broad and local contextual prediction during natural language comprehension. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (pp. 3786-3798). [https://aclanthology.org/2021.findings-acl.332.pdf Link]</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=Context&diff=1155Context2022-08-25T15:13:57Z<p>Shohini: </p>
<hr />
<div>'''Investigating Context'''<br />
Through fMRI and MEG studies, the goal of this project is to investigate the role of context during naturalistic language comprehension. Utilizing language models and topic models, we are examining how they can represent different sources of contextual knowledge and embody cognitive hypotheses, both during speech perception and during sentence processing.<br />
<br />
Recent Papers</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=Projects&diff=1154Projects2022-08-25T15:11:59Z<p>Shohini: </p>
<hr />
<div><br />
* '''[http://www.umiacs.umd.edu/~jbg/projects/IIS-1652666 Human-Computer Cooperation for Word-by-Word Question Answering]''' (Boyd-Graber)<br />
* '''[http://users.umiacs.umd.edu/~jbg/projects/BETTER.html Better Extraction from Text Towards Enhanced Retrieval (BETTER)]''' (Boyd-Graber)<br />
* '''Assessment of Suicidality in Social Media Interaction''' PI: Philip Resnik and Hal Daumé III. ([[Suicide]])<br />
<br />
* '''Computational Models of Plasticity and Learning in Speech Perception''' PI: Naomi Feldman. ([https://www.nsf.gov/awardsearch/showAward?AWD_ID=2120834])<br />
<br />
* '''Computational Modeling to Identify Symptom Changes in Schizophrenia and Depression''' PI: Philip Resnik. ([[Schiz]])<br />
<br />
* '''Crowdsourcing Urban Bicycle Level of Service Measures''' PI: Frias-Martinez. ([[Cycling Safety]])<br />
<br />
* '''Expertsourcing''' PI: Philip Resnik. ([[Expert]])<br />
<br />
* '''Financial Open Knowledge Graphs''' PI: Louiqa Raschid. ([[DSfin OKN]] [http://ichs.ucsf.edu/open-knowledge-network/][https://docs.google.com/presentation/d/1CwoopZzCFnnoLVRUme2P3F7loShBfcmcl_WT172SZCU/edit?usp=sharing])<br />
<br />
* '''Improving Technical Paper Database Search Through Math-Aware Search Engines''' PI: Doug Oard. ([https://nsf.gov/awardsearch/showAward?AWD_ID=1717997&HistoricalAwards=false])<br />
<br />
* '''Investigating Context: A Computational Cognitive Neuroscience approach''' PI: Philip Resnik. ([[Context]] [https://csis.gmu.edu/pages/projects/ONR-MURI-Generating-Documents.html])<br />
<br />
* '''Semantics based community detection in biological datasets''' PI: Louiqa Raschid. ([[SemEP]][http://project-iasis.eu] [https://link.springer.com/chapter/10.1007%2F978-3-319-11964-9_9][http://ieeexplore.ieee.org/document/6817596/?reload=true])<br />
<br />
* '''Understanding Human Behavior and Resilience during Shocks in Smart and Connected Communities''' PI: Frias-Martinez. ([[Disaster Analytics]])</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=Context&diff=1153Context2022-08-25T15:11:07Z<p>Shohini: Created page with "Investigating Context: Through fMRI and MEG studies, the goal of this project is to investigate the role of context during naturalistic language comprehension. Utilizing langu..."</p>
<hr />
<div>Investigating Context: Through fMRI and MEG studies, the goal of this project is to investigate the role of context during naturalistic language comprehension. Utilizing language models and topic models, we are examining how they can represent different sources of contextual knowledge and embody cognitive hypotheses, both during speech perception and during sentence processing.</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=Projects&diff=1152Projects2022-08-25T15:09:59Z<p>Shohini: </p>
<hr />
<div><br />
* '''[http://www.umiacs.umd.edu/~jbg/projects/IIS-1652666 Human-Computer Cooperation for Word-by-Word Question Answering]''' (Boyd-Graber)<br />
* '''[http://users.umiacs.umd.edu/~jbg/projects/BETTER.html Better Extraction from Text Towards Enhanced Retrieval (BETTER)]''' (Boyd-Graber)<br />
* '''Assessment of Suicidality in Social Media Interaction''' PI: Philip Resnik and Hal Daumé III. ([[Suicide]])<br />
<br />
* '''Computational Models of Plasticity and Learning in Speech Perception''' PI: Naomi Feldman. ([https://www.nsf.gov/awardsearch/showAward?AWD_ID=2120834])<br />
<br />
* '''Computational Modeling to Identify Symptom Changes in Schizophrenia and Depression''' PI: Philip Resnik. ([[Schiz]])<br />
<br />
* '''Crowdsourcing Urban Bicycle Level of Service Measures''' PI: Frias-Martinez. ([[Cycling Safety]])<br />
<br />
* '''Expertsourcing''' PI: Philip Resnik. ([[Expert]])<br />
<br />
* '''Financial Open Knowledge Graphs''' PI: Louiqa Raschid. ([[DSfin OKN]] [http://ichs.ucsf.edu/open-knowledge-network/][https://docs.google.com/presentation/d/1CwoopZzCFnnoLVRUme2P3F7loShBfcmcl_WT172SZCU/edit?usp=sharing])<br />
<br />
* '''Improving Technical Paper Database Search Through Math-Aware Search Engines''' PI: Doug Oard. ([https://nsf.gov/awardsearch/showAward?AWD_ID=1717997&HistoricalAwards=false])<br />
<br />
* '''[https://conf.ling.cornell.edu/sbhattasali/ Investigating Context: A Computational Cognitive Neuroscience approach]''' PI: Philip Resnik. ([[Context]][https://csis.gmu.edu/pages/projects/ONR-MURI-Generating-Documents.html])<br />
<br />
* '''Semantics based community detection in biological datasets''' PI: Louiqa Raschid. ([[SemEP]][http://project-iasis.eu] [https://link.springer.com/chapter/10.1007%2F978-3-319-11964-9_9][http://ieeexplore.ieee.org/document/6817596/?reload=true])<br />
<br />
* '''Understanding Human Behavior and Resilience during Shocks in Smart and Connected Communities''' PI: Frias-Martinez. ([[Disaster Analytics]])</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=Projects&diff=1151Projects2022-08-25T15:09:40Z<p>Shohini: </p>
<hr />
<div><br />
* '''[http://www.umiacs.umd.edu/~jbg/projects/IIS-1652666 Human-Computer Cooperation for Word-by-Word Question Answering]''' (Boyd-Graber)<br />
* '''[http://users.umiacs.umd.edu/~jbg/projects/BETTER.html Better Extraction from Text Towards Enhanced Retrieval (BETTER)]''' (Boyd-Graber)<br />
* '''Assessment of Suicidality in Social Media Interaction''' PI: Philip Resnik and Hal Daumé III. ([[Suicide]])<br />
<br />
* '''Computational Models of Plasticity and Learning in Speech Perception''' PI: Naomi Feldman. ([https://www.nsf.gov/awardsearch/showAward?AWD_ID=2120834])<br />
<br />
* '''Computational Modeling to Identify Symptom Changes in Schizophrenia and Depression''' PI: Philip Resnik. ([[Schiz]])<br />
<br />
* '''Crowdsourcing Urban Bicycle Level of Service Measures''' PI: Frias-Martinez. ([[Cycling Safety]])<br />
<br />
* '''Expertsourcing''' PI: Philip Resnik. ([[Expert]])<br />
<br />
* '''Financial Open Knowledge Graphs''' PI: Louiqa Raschid. ([[DSfin OKN]] [http://ichs.ucsf.edu/open-knowledge-network/][https://docs.google.com/presentation/d/1CwoopZzCFnnoLVRUme2P3F7loShBfcmcl_WT172SZCU/edit?usp=sharing])<br />
<br />
* '''Improving Technical Paper Database Search Through Math-Aware Search Engines''' PI: Doug Oard. ([https://nsf.gov/awardsearch/showAward?AWD_ID=1717997&HistoricalAwards=false])<br />
<br />
* '''[https://conf.ling.cornell.edu/sbhattasali/ Investigating Context: A Computational Cognitive Neuroscience approach]''' PI: Philip Resnik. ([Context][https://csis.gmu.edu/pages/projects/ONR-MURI-Generating-Documents.html])<br />
<br />
* '''Semantics based community detection in biological datasets''' PI: Louiqa Raschid. ([[SemEP]][http://project-iasis.eu] [https://link.springer.com/chapter/10.1007%2F978-3-319-11964-9_9][http://ieeexplore.ieee.org/document/6817596/?reload=true])<br />
<br />
* '''Understanding Human Behavior and Resilience during Shocks in Smart and Connected Communities''' PI: Frias-Martinez. ([[Disaster Analytics]])</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=Projects&diff=1020Projects2020-08-27T18:07:22Z<p>Shohini: Adding Philip & Shohini's project</p>
<hr />
<div><br />
* '''Assessment of Suicidality in Social Media Interaction''' PI: Philip Resnik and Hal Daumé III. ([[Suicide]])<br />
<br />
* '''[http://www.umiacs.umd.edu/~jbg/projects/IIS-1409287.html Closing the User-Model Loop for Understanding Topics in Large Document Collections]''' (Boyd-Graber)<br />
<br />
* '''Cognitive Models of the Acquisition of Vowels in Context''' PI: Naomi Feldman, Micha Elsner. ([https://www.nsf.gov/awardsearch/showAward?AWD_ID=1421695])<br />
<br />
* '''Computational Modeling to Identify Symptom Changes in Schizophrenia and Depression''' PI: Philip Resnik. ([[Schiz]])<br />
<br />
* '''Crowdsourcing Urban Bicycle Level of Service Measures''' PI: Frias-Martinez. ([[Cycling Safety]])<br />
<br />
* '''Expertsourcing''' PI: Philip Resnik. ([[Expert]])<br />
<br />
* '''Financial Open Knowledge Graphs''' PI: Louiqa Raschid. ([[DSfin OKN]] [http://ichs.ucsf.edu/open-knowledge-network/][https://docs.google.com/presentation/d/1CwoopZzCFnnoLVRUme2P3F7loShBfcmcl_WT172SZCU/edit?usp=sharing])<br />
<br />
* '''[http://www.umiacs.umd.edu/~jbg/projects/IIS-1652666 Human-Computer Cooperation for Word-by-Word Question Answering]''' (Boyd-Graber)<br />
<br />
* '''Identifying Humanitarian Assistance Needs in Low Resource Languages''' PI: Philip Resnik and Jordan Boyd-Graber. ([[HumAssist]])<br />
<br />
* '''Improving Technical Paper Database Search Through Math-Aware Search Engines''' PI: Doug Oard. ([https://nsf.gov/awardsearch/showAward?AWD_ID=1717997&HistoricalAwards=false])<br />
<br />
* '''[https://conf.ling.cornell.edu/sbhattasali/ Investigating Context: A Computational Cognitive Neuroscience approach]''' PI: Philip Resnik. ([https://csis.gmu.edu/pages/projects/ONR-MURI-Generating-Documents.html])<br />
<br />
* '''Machine Translation for English Retrieval of Information in Any Language (MATERIAL)''' PI: Doug Oard, Co-PI: Marine Carpuat, Hal Daume, Philip Resnik. ([https://www.iarpa.gov/index.php/research-programs/material])<br />
<br />
* '''Modeling the Development of Phonetic Representations''' PI: Naomi Feldman, Sharon Goldwater. ([https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734245])<br />
<br />
* '''Search Among Sensitive Content''' PI: Doug Oard, Co-PI: Katie Shilton, Jimmy Lin ([https://www.umiacs.umd.edu/~oard/sasc/])<br />
<br />
* '''Semantics based community detection in biological datasets''' PI: Louiqa Raschid. ([[SemEP]][http://project-iasis.eu] [https://link.springer.com/chapter/10.1007%2F978-3-319-11964-9_9][http://ieeexplore.ieee.org/document/6817596/?reload=true])<br />
<br />
* '''Understanding Human Behavior and Resilience during Shocks in Smart and Connected Communities''' PI: Frias-Martinez. ([[Disaster Analytics]])</div>Shohinihttps://wiki.umiacs.umd.edu/clip/index.php?title=People&diff=1019People2020-08-27T17:59:18Z<p>Shohini: /* Researchers and Post-Docs */</p>
<hr />
<div>== Faculty ==<br />
<br />
* '''[https://aiwei.me/ Wei Ai]''': Assistant Professor, iSchool and UMIACS.<br />
<br />
* '''[http://boydgraber.org/ Jordan Boyd-Graber]''': Associate Professor, Computer Science, UMIACS, the iSchool, and the Language Science Center.<br />
<br />
* '''[http://www.cs.umd.edu/~marine/ Marine Carpuat]''': Assistant Professor, Computer Science and UMIACS.<br />
<br />
* '''[http://www.umiacs.umd.edu/~hal/ Hal Daum&eacute; III]''': Professor, Computer Science, Linguistics and UMIACS.<br />
<br />
* '''[http://www.ling.umd.edu/~nhf/ Naomi Feldman]''': Associate Professor, Linguistics and UMIACS; Affiliate Associate Professor, Computer Science and [https://nacs.umd.edu/ NACS].<br />
<br />
* '''[http://www.vanessafriasmartinez.org/ Vanessa Frias-Martinez]''': Assistant Professor, the iSchool and UMIACS; Affiliate Assistant Professor, Computer Science.<br />
<br />
* '''[http://www.glue.umd.edu/~oard/ Douglas W. Oard]''': Professor, the iSchool and UMIACS; Affiliate Professor, Computer Science and [https://amsc.umd.edu/academics/program-concentrations.html AMSC].<br />
<br />
* '''[http://www.umiacs.umd.edu/~louiqa/ Louiqa Raschid]''': Professor, Smith School of Business and UMIACS; Affiliate Professor, Computer Science.<br />
<br />
* '''[http://www.umiacs.umd.edu/~resnik/ Philip Resnik]''': Professor, Linguistics and UMIACS; Affiliate Professor, Computer Science.<br />
<br />
* '''[https://rudinger.github.io/ Rachel Rudinger]''': Assistant Professor, Computer Science and UMIACS.<br />
<br />
<center>[[Image:people_facpd.jpg|center|504px|x]]</center><br />
<br />
== Emeritus / Associated Faculty ==<br />
<br />
* '''[http://www.umiacs.umd.edu/~bonnie/ Bonnie J. Dorr]''': Professor Emerita, Computer Science and UMIACS<br />
<br />
* '''[http://www.umiacs.umd.edu/~mharper/ Mary Harper]''': Affiliate Research Professor, Computer Science, Electrical and Computer Engineering, and UMIACS<br />
<br />
* '''[http://www.umiacs.umd.edu/~jklavans/ Judith Klavans]''': Visiting Senior Research Scientist, UMIACS<br />
<br />
* '''[http://www.umiacs.umd.edu/~jimmylin/ Jimmy Lin]''': Associate Professor, the iSchool and UMIACS, now at University of Waterloo.<br />
<br />
* '''[http://www.umiacs.umd.edu/~weinberg/ Amy Weinberg]''': Professor, Department of Linguistics and UMIACS<br />
<br />
* '''[http://lampsrv02.umiacs.umd.edu/projdb/person.php?id=2 David Doermann]''': Senior Research Scientist, UMIACS. Now SUNY Empire Innovation Professor at Buffalo. [https://cse.buffalo.edu/~doermann/]<br />
<br />
==Researchers and Post-Docs==<br />
<br />
* '''[https://conf.ling.cornell.edu/sbhattasali/ Shohini Bhattasali]<br />
<br />
* '''[http://ufal.mff.cuni.cz/petra-galuscakova/ Petra Galuscakova]<br />
<br />
* '''Zara Harmon'''<br />
<br />
* '''[http://thomas.schatz.cogserver.net/ Thomas Schatz]'''<br />
<br />
==Graduate Students==<br />
<br />
<br />
* '''[https://jbarrow.ai Joe Barrow]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''Jake Bremerman''', Masters Student, Department of Computer Science<br />
<br />
* '''[http://cs.umd.edu/~elgohary Ahmed Elgohary]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[http://legacydirs.umiacs.umd.edu/~shifeng/ Shi Feng]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[http://www.linkedin.com/pub/milad-gholami/55/35a/33a Milad Gholami]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[https://csel.cs.colorado.edu/~fegu1724/ Fenfei Guo]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[http://www.cs.umd.edu/~huah/ Hua He]''': Ph.D. Student, Department of Computer Science<br />
<br />
* '''[http://cassidyhenry.com/ Cassidy Henry]''': Ph.D. student, Department of Linguistics<br />
<br />
* '''[https://terpconnect.umd.edu/~lzhong/ Lingzi Hong]''': Ph.D. student, iSchool<br />
<br />
* '''Nika Jurov''': Ph.D. student, Department of Linguistics<br />
<br />
* '''Marianna Martindale''': Ph.D. student, iSchool<br />
<br />
* '''Suraj Nair''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[http://www.umiacs.umd.edu/~daithang/ Thang Nguyen]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[http://ling.umd.edu/people/person/jackie-nelligan/ Jackie Nelligan]''': Ph.D. student, Department of Linguistics and M.S. student, Department of Computer Science<br />
<br />
* '''[http://xingniu.org/ Xing Niu]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[https://www.cs.umd.edu/people/dpeskov Denis Peskov]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[http://www.cs.umd.edu/~jinfeng/ Jinfeng Rao]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[http://raosudha.weebly.com/ Sudha Rao]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[https://pedrorodriguez.io/ Pedro Rodriguez]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''Kristine Rogers''': Ph.D. student, iSchool<br />
<br />
* '''Mahmoud Sayed''': Ph.D. student, Department of Computer Science<br />
<br />
* '''Amr Sharaf''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[https://www.linkedin.com/in/han-chin-shing/ Han-Chin Shing]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[http://alisonmsmith.github.io/ Alison Smith]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''Craig Thorburn''': Ph.D. student, Department of Linguistics<br />
<br />
* '''[http://cs.umd.edu/~yogarshi/ Yogarshi Vyas]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[http://www.cs.umd.edu/~ylwang/ Yulu Wang]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''[http://www.terpconnect.umd.edu/~jeffwu/ Jiahui Wu]''': Ph.D. student, iSchool<br />
<br />
<center>[[Image:people_students.jpg|center|504px|x]]</center><br />
<br />
== CLIP Alumni ==<br />
<br />
===Researchers and postdocs===<br />
<br />
* '''[http://www.umiacs.umd.edu/~hadi/ Hadi Amiri]''': Assistant Professor, University of Massachusetts, Lowell<br />
<br />
* '''[http://ssli.ee.washington.edu/people/amittai/index.html Amittai Axelrod]''': Research Scientist, Amazon<br />
<br />
* '''[http://boydgraber.org Jordan Boyd-Graber]''' (2010): Associate Professor, University of Maryland<br />
<br />
* '''[http://www.linkedin.com/in/maribromanolsen Mari Broman-Olsen]''': Senior progam manager, Natural Language Experiences, Microsoft<br />
<br />
* '''[http://www.isi.edu/~chiang/ David Chiang]''': Associate Professor, University of Notre Dame<br />
<br />
* '''[http://faculty.qu.edu.qa/telsayed/ Tamer Elsayed]''': Assistant Professor, Qatar University (Qatar)<br />
<br />
* '''[http://www.isical.ac.in/~utpal/ Utpal Garain]''': Associate Professor, Indian Statistical Institute (India)<br />
<br />
* '''[http://www.sis.pitt.edu/~daqing/ Daqing He]''': Professor, University of Pittsburgh<br />
<br />
* '''[http://www.umiacs.umd.edu/~hollingk Kristy Hollingshead]''' (2012): Research Scientist, Florida Institute for Human & Machine Cognition <br />
<br />
* '''[http://www.cs.pitt.edu/~hwa/ Rebecca Hwa]''': Associate Professor, University of Pittsburgh<br />
<br />
* '''[http://www.mit.edu/~dajones/ Doug Jones]''': Senior Member of the Technical Staff, Lincoln Labs<br />
<br />
* '''[http://web.donga.ac.kr/yjko/ Youngjoong Ko]''': Professor, Dong A University (Korea)<br />
<br />
* '''Rebecca LaPlante''': Independent Consultant on Information Access<br />
<br />
* '''[http://faculty.washington.edu/levow/ Gina Levow]''': Associate Professor, University of Washington<br />
<br />
* '''[http://www.umiacs.umd.edu/~lijunhui/ Junhui Li]''', Associate Professor, Soochow University<br />
<br />
* '''Saif Mohammad''': Research Officer, National Research Council (Canada)<br />
<br />
* '''[http://staff.science.uva.nl/~christof/ Christof Monz]''': Associate Professor, University of Amsterdam (The Netherlands)<br />
<br />
* '''[http://www.umiacs.umd.edu/~tsmoon/ Taesun Moon]''': Researcher, IBM TJ Watson Research Center<br />
<br />
* '''[http://comminfo.rutgers.edu/directory/smuresan/index.html Smaranda Muresan]''': Research Scientist, Center for Computational Learning Systems (CCLS), and Adjunct Associate Professor, Department of Computer Science, Columbia University. <br />
<br />
* '''[http://www.umiacs.umd.edu/~jiaul/ Jiaul Paik]''', Assistant Professor, IIT Kharagpur<br />
<br />
* '''[http://www.umiacs.umd.edu/~hendra/ Hendra Setiawan]''': Language Technology R&D Scientist and Engineer, Apple<br />
<br />
* '''Carolyn Sheffield''': Smithsonian Institute<br />
<br />
* '''[http://dbs.uni-leipzig.de/en/person/andreas_thor Andreas Thor]''': University of Leipzig (Germany)<br />
<br />
* '''[http://web.ntnu.edu.tw/~samtseng/ Yuen-Hsien Tseng]''': Professor, National Taiwan Normal University (Taiwan)<br />
<br />
* '''[http://www.ldc.usb.ve/~mvidal/ Maria Esther Vidal]''': Professor, Universidad Simon Bolivar (Venezuela)<br />
<br />
* '''[http://www.umiacs.umd.edu/~ewagner/ Earl J. Wagner]''': Google<br />
<br />
* '''[http://www.williamwebber.com/ William Webber]''': Consultant, Melbourne (Australia)<br />
<br />
* '''[http://research.microsoft.com/en-us/um/people/ryenw/ Ryen White]''': Research Manager, Microsoft Cortana<br />
<br />
* '''[http://mlg.eng.cam.ac.uk/sinead/ Sinead Williamson]''' (2011): Assistant Professor, University of Texas<br />
<br />
* '''Adnan Yahya''': Professor, Birzeit University (Palestine)<br />
<br />
* '''[http://www.sis.pitt.edu/~vladimir/ Vladimir Zadorozhny]''': Associate Professor, University of Pittsburgh<br />
<br />
* '''[http://ufal.mff.cuni.cz/~zeman/en/ Daniel Zeman]''': Researcher, Charles University (Czech Republic)<br />
<br />
===Ph.D. Students===<br />
<br />
* '''[http://www.cs.utah.edu/~arvind/ Arvind Agarwal]''': Researcher, Xerox Research<br />
<br />
*'''[http://www.cs.umd.edu/~nima/ Nima Asadi]'''<br />
<br />
* '''Necip Fazil Ayan''': SRI<br />
<br />
* '''[http://www.cs.umd.edu/~mossaab/ Mossaab Bagdouri]''' (2017): Walmart Labs<br />
<br />
* '''Laura Bright''' (2003): McAfee<br />
<br />
* '''[http://www.cs.ntou.edu.tw/CSWebPage/eng/teachers.php Ya-Hui Chang]''': Associate Professor, National Taiwan Ocean University, Keelung, Taiwan<br />
<br />
* '''[https://sites.google.com/site/snigdhac/ Snigdha Chaturvedi]''': Postdoc with Dan Roth, University of Illinois<br />
<br />
* '''Waiyian Chong''': Yuan<br />
<br />
* '''[https://www.linkedin.com/in/claudino Leonardo Claudino]''': NIH postdoc<br />
<br />
* '''[http://www.qcri.qa/kareem-darwish/ Kareem Darwish]''': Qatar Computing Research Institute (Qatar) <br />
<br />
* '''[https://lhncbc.nlm.nih.gov/personnel/dina-demner-fushman Dina Demner-Fushman]''': National Library of Medicine<br />
<br />
* '''[http://www.cs.gwu.edu/people/faculty/811 Mona Diab]''': Professor, George Washington University<br />
<br />
* '''[http://www.cs.cmu.edu/~cdyer/ Chris Dyer]''': Google DeepMind<br />
<br />
* '''[http://www.umiacs.umd.edu/~vlad/ Vladimir Eidelman]''': Vice President of Research, FiscalNote<br />
<br />
* '''[http://www.ieleta.com/en/ Irene Eleta]''': <br />
<br />
* '''[https://aetting.github.io/ Allyson Ettinger]''': Research Assistant Professor, Toyota Technological Institute<br />
<br />
* '''Denis Filimonov''': FactSet<br />
<br />
* '''Ning Gao''': Microsoft<br />
<br />
* '''Sergey Golitsynskiy''': Assistant Professor, University of Northern Iowa<br />
<br />
* '''[http://www.umiacs.umd.edu/~amit/ Amit Goyal]''': Yahoo! Research<br />
<br />
* '''Rebecca Green''': Library of Congress<br />
<br />
* '''Stephan Greene''': Lead Engineer for NLP, Data Science, Text Analytics at Sprinklr<br />
<br />
* '''[http://www.umiacs.umd.edu/~alvin/ Alvin Grissom II]''': Assistant Professor, Ursinus College<br />
<br />
* '''[http://www.cs.umd.edu/~rguerra/ Raul David Guerra]''': Ph.D. student, Department of Computer Science<br />
<br />
* '''Nizar Habash''': Associate Professor of Computer Science, New York University Abu Dhabi<br />
<br />
* '''[http://www.cs.umd.edu/~hardisty/ Eric Hardisty]''': DoD<br />
<br />
* '''[http://www.umiacs.umd.edu/~hhe/ He He]''': Postdoc with Percy Liang, Stanford University<br />
<br />
* '''[http://ling.umd.edu/people/person/kasia-hitczenko/ Kasia Hitczenko]''': Postdoc, Northwestern University<br />
<br />
* '''[http://www.cs.umd.edu/~zqhuang/ Zhongqiang Huang]''': BBN<br />
<br />
* '''[http://www.cs.umd.edu/~changhu/ Chang Hu]''': Research Software Development Engineer, Microsoft<br />
<br />
* '''[http://www.cs.umd.edu/~ynhu Yuening Hu]''': Research Scientist, Google<br />
<br />
* '''[http://www.cs.umd.edu/~miyyer Mohit Iyyer]''': Assistant Professor, University of Massachusetts <br />
<br />
* '''[http://www.umiacs.umd.edu/~jags/ Jagadeesh Jagarlamudi]''': Researcher, Google Research New York<br />
<br />
* '''[http://www.umiacs.umd.edu/~jiarong/ Jiarong Jiang]''': Research Scientist, Two-Sigma<br />
<br />
* '''Darsana P. Josyula'''<br />
<br />
* '''Maria Katsova''': Microsoft Research<br />
<br />
* '''Jinmook Kim''': Kangnam University (Korea)<br />
<br />
* '''Okan Kolak''': Google<br />
<br />
* '''[http://ling.umd.edu/~yakov/ Yakov Kronrod]''': Amazon<br />
<br />
* '''[http://www.umiacs.umd.edu/~abhishek/ Abhishek Kumar]''': Researcher, IBM TJ Watson Research Center<br />
<br />
* '''Grecia Lapizco'''<br />
<br />
* '''[http://www.ncbi.nlm.nih.gov/CBBresearch/Fellows/AdamLee/ Adam (Woei-Jyh) Lee]''': (2009) Postdoc Fellow, National Institutes of Health->Smith School of Business, University of Maryland<br />
<br />
* '''[https://alopez.github.io/ Adam Lopez]''': Reader, University of Edinburgh<br />
<br />
* '''Jun Luo'''<br />
<br />
* '''[http://www.desilinguist.org Nitin Madnani]''': Research Scientist, ETS<br />
<br />
* '''[http://www1.ccls.columbia.edu/~ymarton/ Yuval Marton]''': Senior Applied Scientist, Microsoft<br />
<br />
* '''Joseph Naft'''<br />
<br />
* '''[http://www.cs.umd.edu/~vietan/ Viet-An Nguyen]''': Facebook Research<br />
<br />
* '''Levon Mkrtchyan'''<br />
<br />
* '''[http://www.wyomingcatholiccollege.com/about-wcc/directory/profile/index.aspx?linkid=25&moduleid=19 J. Scott Olsson]''': Associate Professor, Wyoming Catholic College<br />
<br />
* '''[http://www.cl.ecei.tohoku.ac.jp/~naho/ Naho Orita]''': Research Assistant Professor, Tohoku University<br />
<br />
* '''[http://www.socsci.uci.edu/~lpearl/ Lisa Pearl]''': Associate Professor, UC Irvine<br />
<br />
* '''Stacy President Hobson''': IBM<br />
<br />
* '''Alejandro Rodriguez'''<br />
<br />
* '''Asad Sayeed''': Universitetslektor, University of Göteborg<br />
<br />
* '''[http://www.cs.umd.edu/~sayyadi/ Hassan Sayyadi]''': Comcast<br />
<br />
* '''Wade Shen''': DARPA<br />
<br />
* '''Matthew Snover''': Postdoc, CUNY<br />
<br />
* '''Calandra Tate''': West Point<br />
<br />
* '''Scott Thomas''': Navy Research Labs<br />
<br />
* '''[http://ling.umd.edu/~rachaelr/ Alayo Tripp]''': Postdoc, University of Minnesota<br />
<br />
* '''[http://www.cs.umd.edu/~fture/ Ferhan Ture]''': Comcast<br />
<br />
* '''Jyothi Vinjumur''': Walmart<br />
<br />
* '''Clare Voss''': Army Research Labs<br />
<br />
* '''Nate Waisbrot'''<br />
<br />
* '''[http://www.acsu.buffalo.edu/~jw254/ Jianqiang Wang]''': Associate Professor, University at Buffalo, State University of New York<br />
<br />
* '''[http://www.cs.umd.edu/~lidan/ Lidan Wang]''': IBM Research<br />
<br />
* '''[http://www.cs.umd.edu/~wsc/ Shanchan Wu]''' (2012): HP Labs<br />
<br />
* '''[http://www.csc.lsu.edu/~wuyj/ Yejun Wu]''': Associate Professor, Louisiana State University<br />
<br />
* '''Yao Wu''' (2009): Microsoft<br />
<br />
* '''[http://terpconnect.umd.edu/~tanx/ Tan Xu]''', AT&T Research<br />
<br />
* '''[https://ywwbill.github.io/ Weiwei Yang]''' (2019): Research Scientist, Facebook<br />
<br />
* '''David Zajic''': Univeristy of Maryland / CASL<br />
<br />
* '''Ke Zhai''': Researcher, Microsoft<br />
<br />
===MS Students===<br />
<br />
* '''David Alexander''': BBN<br />
<br />
* '''Aitziber Atutxa''': Univ of the Basque Country<br />
<br />
* '''Clara Cabezas'''<br />
<br />
* '''Jacob Devlin''': Principal A.I. Scientist, Google<br />
<br />
* '''Peter Enns''': Amazon<br />
<br />
* '''Ed Kenschaft''': Basis Technology<br />
<br />
* '''Govind Kothari''': eBay<br />
<br />
* '''John Morgan''': Army Research Lab<br />
<br />
* '''Grazia Russo-Lassner''': Senior software engineer, PTP<br />
<br />
* '''Gregory Sanders'''<br />
<br />
* '''[http://www.cs.umd.edu/~rashmi/ Rashmi Sankepally]'''<br />
<br />
* '''Aga Skotowski''': BBN<br />
<br />
* '''Ruth Sperer'''<br />
<br />
* '''Michael Subotin''': 3M Health Information Systems<br />
<br />
* '''Ke Wu''': Google<br />
<br />
===Undergraduate Students===<br />
<br />
* '''Olivia Buzek''': Watson Machine Learning Engineer, IBM Watson / Alchemy API<br />
<br />
* '''Aaron Elkiss''': Univ of Michigan Libraries<br />
<br />
* '''Andrew Fister'''<br />
<br />
* '''Meir Friedenberg''': PhD program in CS, Cornell<br />
<br />
* '''Ayelet Goldin''': Software Developer, PopCap Games <br />
<br />
* '''Gregory Marton''': Google Research<br />
<br />
* '''Ederlyn Lacson''': Microsoft<br />
<br />
* '''Jesse Metcalf-Burton''': PhD from University of Michigan<br />
<br />
* '''Eric Nichols''': MS student, Nara Institute of Science and Technology, Japan<br />
<br />
* '''Noah Smith''': Associate professor, University of Washington<br />
<br />
* '''Jessica Stevens''': BBN<br />
<br />
* '''[https://www.linkedin.com/in/bryan-toth-7b639765 Bryan Toth]''': Epic Systems<br />
<br />
* '''Michael Wasser'''</div>Shohini