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    <titleInfo>
        <title>Temporal Lobes as Combinatory Engines for both Form and Meaning</title>
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    <name type="personal">
        <namePart type="given">Jixing</namePart>
        <namePart type="family">Li</namePart>
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    <name type="personal">
        <namePart type="given">Jonathan</namePart>
        <namePart type="family">Brennan</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Adam</namePart>
        <namePart type="family">Mahar</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">John</namePart>
        <namePart type="family">Hale</namePart>
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            <title>Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)</title>
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            <namePart type="given">Dominique</namePart>
            <namePart type="family">Brunato</namePart>
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        <name type="personal">
            <namePart type="given">Felice</namePart>
            <namePart type="family">Dell’Orletta</namePart>
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            <namePart type="given">Giulia</namePart>
            <namePart type="family">Venturi</namePart>
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        <name type="personal">
            <namePart type="given">Thomas</namePart>
            <namePart type="family">François</namePart>
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            <namePart type="given">Philippe</namePart>
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            <publisher>The COLING 2016 Organizing Committee</publisher>
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    <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.”</abstract>
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        <url>https://aclanthology.org/W16-4121</url>
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        <date>2016-12</date>
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            <start>186</start>
            <end>191</end>
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%0 Conference Proceedings
%T Temporal Lobes as Combinatory Engines for both Form and Meaning
%A Li, Jixing
%A Brennan, Jonathan
%A Mahar, Adam
%A Hale, John
%Y Brunato, Dominique
%Y Dell’Orletta, Felice
%Y Venturi, Giulia
%Y François, Thomas
%Y Blache, Philippe
%S Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F li-etal-2016-temporal
%X 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.”
%U https://aclanthology.org/W16-4121
%P 186-191

Markdown (Informal)

[Temporal Lobes as Combinatory Engines for both Form and Meaning](https://aclanthology.org/W16-4121) (Li et al., CL4LC 2016)

• Temporal Lobes as Combinatory Engines for both Form and Meaning (Li et al., CL4LC 2016)

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.