Temporal Lobes as Combinatory Engines for both Form and Meaning

Jixing Li, Jonathan Brennan, Adam Mahar, John Hale


Abstract
The relative contributions of meaning and form to sentence processing remains an outstanding issue across the language sciences. We examine this issue by formalizing four incremental complexity metrics and comparing them against freely-available ROI timecourses. Syntax-related metrics based on top-down parsing and structural dependency-distance turn out to significantly improve a regression model, compared to a simpler model that formalizes only conceptual combination using a distributional vector-space model. This confirms the view of the anterior temporal lobes as combinatory engines that deal in both form (see e.g. Brennan et al., 2012; Mazoyer, 1993) and meaning (see e.g., Patterson et al., 2007). This same characterization applies to a posterior temporal region in roughly “Wernicke’s Area.”
Anthology ID:
W16-4121
Volume:
Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)
Month:
December
Year:
2016
Address:
Osaka, Japan
Venues:
CL4LC | WS
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
186–191
Language:
URL:
https://aclanthology.org/W16-4121
DOI:
Bibkey:
Cite (ACL):
Jixing Li, Jonathan Brennan, Adam Mahar, and John Hale. 2016. Temporal Lobes as Combinatory Engines for both Form and Meaning. In Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC), pages 186–191, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Temporal Lobes as Combinatory Engines for both Form and Meaning (Li et al., 2016)
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PDF:
https://aclanthology.org/W16-4121.pdf