| Paper: | PS-1B.60 | ||
| Session: | Poster Session 1B | ||
| Location: | H Fläche 1.OG | ||
| Session Time: | Saturday, September 14, 16:30 - 19:30 | ||
| Presentation Time: | Saturday, September 14, 16:30 - 19:30 | ||
| Presentation: | Poster | ||
| Publication: | 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany | ||
| Paper Title: | Temporal Dynamics of Meaning | ||
| Manuscript: | Click here to view manuscript | ||
| License: |  This work is licensed under a Creative Commons Attribution 3.0 Unported License. |
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| DOI: | https://doi.org/10.32470/CCN.2019.1301-0 | ||
| Authors: | Ariel Goldstein, Princeton University and Google Research, United States; Aren Jansen, Malcom Slaney, Google Research, United States; Amy Price, Zaid Kokaja Zada, Princeton University, United States; Gina Ghoe, Bobbi Aubrey, Aditi Rao, Lora Fanda, Princeton University and NYU School of Medicine, United States; Kenneth Norman, Princeton University, United States; Adeen Flinker, Orrin Devinsky, NYU School of Medicine, United States; Michael Brenner, Google Research, United States; Uri Hasson, Princeton University and Google Research, United States | ||
| Abstract: | Language is a hallmark of human cognition. It allows for efficient communication between humans and is a building block for high-level cognition. The question of how lingual semantic meaning is represented in and produced by the brain is one of the great mysteries of cognitive neuroscience. In this work we compare the processes of semantic comprehension and production, focusing on neural processes that take place in the speaker’s and listener’s brains before the word was articulated. To that end, we are building a big dataset of high-quality brain data as patients speak and comprehend language in real-life conversations using intracranial EEG recordings. Using linear and deep models, we were able to track the triggered temporal dynamic for semantic comprehension and semantic production before and after word onset. In particular, we were able to read semantic information from the speaker’s brain and utilize it to identify the spoken words, hundreds of milliseconds before the moment of articulation, with some hints of pre-verbalization predictive coding in the listener’s brain much closer to word onset. These results demonstrate the difference between semantic comprehension and production, and shed light on the underlying processes allowing for the verbalization of inner neural states. | ||