Context - Revision history

Shohini at 15:21, 25 August 2022

2022-08-25T15:21:11Z

← Older revision		Revision as of 15:21, 25 August 2022
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	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]		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]



			Resources for computational cognitive neuroscience of language work can be found here:
			[[CogNeuro]]

Shohini at 15:19, 25 August 2022

2022-08-25T15:19:05Z

← Older revision		Revision as of 15:19, 25 August 2022
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	'''Investigating Context'''		'''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.		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.

	Recent Papers		'''Recent Papers'''

			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]

			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]

Shohini at 15:13, 25 August 2022

2022-08-25T15:13:57Z

← Older revision		Revision as of 15:13, 25 August 2022
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	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.		'''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.

			Recent Papers

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2022-08-25T15:11:07Z

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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.