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The Neural Network for Sign Language Comprehension
Brennan Terhune-Cotter1, Karen Emmorey2
1Joint Doctoral Program in Language and Communicative Disorders, San Diego State University, University of California, San Diego, California, USA.
Sign language comprehension involves visual processing in the occipital lobe and temporal regions, activating language networks similar to spoken language processing. This highlights shared and modality-specific brain pathways for language.
Area of Science:
- Neuroscience
- Linguistics
- Cognitive Science
Background:
- Sign languages utilize visual-manual articulators, contrasting with spoken languages' vocal-auditory modality.
- This difference impacts neural processing, necessitating a review of sign language comprehension networks.
Purpose of the Study:
- To review the neural network underlying sign language comprehension.
- To delineate the processing stages from visual input to sentence parsing.
Main Methods:
- Review of existing literature on sign language neuroscience.
- Analysis of brain regions involved in visual processing, phonological representation, and semantic-syntactic construction.
Main Results:
- Visual sign decoding occurs in occipital and posterior temporal regions.
- Sign-based phonological and lexical-semantic representations are formed in temporal and parietal regions.
- Higher-level semantic-syntactic processing involves a frontotemporal network overlapping with spoken language networks.
Conclusions:
- Sign language comprehension recruits a network with both visual-specific and supramodal components.
- Further research should explore functional roles within specific brain regions for sign language processing.
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