@InProceedings{li-EtAl:2016:CL4LC,
  author    = {Li, Jixing  and  Brennan, Jonathan  and  Mahar, Adam  and  Hale, John},
  title     = {Temporal Lobes as Combinatory Engines for both Form and Meaning},
  booktitle = {Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {186--191},
  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.''},
  url       = {http://aclweb.org/anthology/W16-4121}
}