3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Conceptual Combination in the LATL With and Without Syntactic Composition

      research-article
      * , ,
      Neurobiology of Language
      MIT Press
      conceptual combination, syntax, semantics, magnetoencephalography

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The relationship among syntactic, semantic, and conceptual processes in language comprehension is a central question to the neurobiology of language. Several studies have suggested that conceptual combination in particular can be localized to the left anterior temporal lobe (LATL), while syntactic processes are more often associated with the posterior temporal lobe or inferior frontal gyrus. However, LATL activity can also correlate with syntactic computations, particularly in narrative comprehension. Here we investigated the degree to which LATL conceptual combination is dependent on syntax, specifically asking whether rapid (∼200 ms) magnetoencephalography effects of conceptual combination in the LATL can occur in the absence of licit syntactic phrase closure and in the absence of a semantically plausible output for the composition. We find that such effects do occur: LATL effects of conceptual combination were observed even when there was no syntactic phrase closure or plausible meaning. But syntactic closure did have an additive effect such that LATL signals were the highest for expressions that composed both conceptually and syntactically. Our findings conform to an account in which LATL conceptual composition is influenced by local syntactic composition but is also able to operate without it.

          Related collections

          Most cited references62

          • Record: found
          • Abstract: found
          • Article: not found

          An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

          In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Cortical surface-based analysis. I. Segmentation and surface reconstruction.

            Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging. Copyright 1999 Academic Press.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Nonparametric statistical testing of EEG- and MEG-data.

              In this paper, we show how ElectroEncephaloGraphic (EEG) and MagnetoEncephaloGraphic (MEG) data can be analyzed statistically using nonparametric techniques. Nonparametric statistical tests offer complete freedom to the user with respect to the test statistic by means of which the experimental conditions are compared. This freedom provides a straightforward way to solve the multiple comparisons problem (MCP) and it allows to incorporate biophysically motivated constraints in the test statistic, which may drastically increase the sensitivity of the statistical test. The paper is written for two audiences: (1) empirical neuroscientists looking for the most appropriate data analysis method, and (2) methodologists interested in the theoretical concepts behind nonparametric statistical tests. For the empirical neuroscientist, a large part of the paper is written in a tutorial-like fashion, enabling neuroscientists to construct their own statistical test, maximizing the sensitivity to the expected effect. And for the methodologist, it is explained why the nonparametric test is formally correct. This means that we formulate a null hypothesis (identical probability distribution in the different experimental conditions) and show that the nonparametric test controls the false alarm rate under this null hypothesis.
                Bookmark

                Author and article information

                Journal
                Neurobiol Lang (Camb)
                Neurobiol Lang (Camb)
                nol
                Neurobiology of Language
                MIT Press (One Broadway, 12th Floor, Cambridge, Massachusetts 02142, USA journals-info@mit.edu )
                2641-4368
                2022
                10 February 2022
                : 3
                : 1
                : 46-66
                Affiliations
                [1]Department of Linguistics, New York University, New York, USA
                [2]Department of Psychology, New York University, New York, USA
                [3]NYUAD Institute, New York University Abu Dhabi, Abu Dhabi, UAE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                * Corresponding Author: alicia.v.parrish@ 123456nyu.edu

                Handling Editor: Yanchao Bi

                Author information
                https://orcid.org/0000-0002-1054-0516
                https://orcid.org/0000-0002-6332-9378
                Article
                nol_a_00048
                10.1162/nol_a_00048
                10158584
                37215334
                9df749fb-91c8-4de3-9b8c-591e6253a286
                © 2021 Massachusetts Institute of Technology

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/.

                History
                : 16 March 2021
                : 15 June 2021
                Page count
                Pages: 21
                Funding
                Funded by: New York University Abu Dhabi, DOI 10.13039/100012025;
                Award ID: G10001
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                Parrish, A., & Pylkkänen, L. (2022). Conceptual combination in the LATL with and without syntactic composition. Neurobiology of Language, 3(1), 46–66. https://doi.org/10.1162/nol_a_00048

                conceptual combination,syntax,semantics,magnetoencephalography

                Comments

                Comment on this article