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      Lists with and without Syntax: A New Approach to Measuring the Neural Processing of Syntax

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      1 , , 1 , 2 , 3
      The Journal of Neuroscience
      Society for Neuroscience
      magnetoencephalography, semantics, syntax, word lists

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          Abstract

          In the neurobiology of syntax, a methodological challenge is to vary syntax while holding semantics constant. Changes in syntactic structure usually correlate with changes in meaning. We approached this challenge from a new angle. We deployed word lists—typically, the unstructured control in studies of syntax—as both test and control stimuli. Three-noun lists (“lamps, dolls, guitars”) were embedded in sentences (“The eccentric man hoarded lamps, dolls, guitars…”) and in longer lists (“forks, pen, toilet, rodeo, lamps, dolls, guitars…”). This allowed us to minimize contributions from lexical semantics and local phrasal combinatorics: the same words occurred in both conditions, and in neither case did the list items locally compose into phrases (e.g., “lamps” and “dolls” do not form a phrase). Crucially, the list partakes in a syntactic tree in one case but not the other. Lists-in-sentences increased source-localized MEG activity at ∼250–300 ms from each of the list item onsets in the left inferior frontal cortex, at ∼300–350 ms in the left anterior temporal lobe and, most reliably, at ∼330–400 ms in left posterior temporal cortex. In contrast, the main effects of semantic association strength, which we also varied, localized in the left temporoparietal cortex, with high associations increasing activity at ∼400 ms. This dissociation offers a novel characterization of the structure versus word meaning contrast in the brain: the frontotemporal network that is familiar from studies of sentence processing can be driven by the sheer presence of global sentence structure, while associative semantics has a more posterior neural signature.

          SIGNIFICANCE STATEMENT Human languages all have a syntax, which both enables the infinitude of linguistic creativity and determines what is grammatical in a language. The neurobiology of syntactic processing has, however, been challenging to characterize despite decades of study. One reason is pure manipulations of syntax are difficult to design. The approach here offers a novel control of two variables that are notoriously hard to keep constant when syntax is manipulated: word meaning and phrasal combinatorics. The same noun lists occurred inside longer lists and sentences, while semantic associations also varied. Our MEG results show that classic frontotemporal language regions can be driven by sentence structure even when local semantic contributions are absent. In contrast, the left temporoparietal junction tracks associative relationships.

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          Most cited references64

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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              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.
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                Author and article information

                Journal
                J Neurosci
                J Neurosci
                jneuro
                jneurosci
                J. Neurosci
                The Journal of Neuroscience
                Society for Neuroscience
                0270-6474
                1529-2401
                10 March 2021
                10 March 2021
                : 41
                : 10
                : 2186-2196
                Affiliations
                [1] 1NYUAD Institute, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
                [2] 2Department of Psychology, New York University, New York, New York 10003
                [3] 3Department of Linguistics, New York University, New York, New York 10003
                Author notes
                Correspondence should be addressed to Ryan Law at ryan.law@ 123456nyu.edu

                Author contributions: R.L. and L.P. designed research; R.L. performed research; R.L. analyzed data; R.L. and L.P. wrote the paper.

                Author information
                https://orcid.org/0000-0002-1175-4604
                https://orcid.org/0000-0002-6332-9378
                Article
                JN-RM-1179-20
                10.1523/JNEUROSCI.1179-20.2021
                8018759
                33500276
                b8b865b0-076f-4d21-8393-cd2030e09bc8
                Copyright © 2021 Law and Pylkkänen

                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 that the original work is properly attributed.

                History
                : 5 May 2020
                : 11 January 2021
                : 13 January 2021
                Funding
                Funded by: New York University Abu Dhabi Institute
                Award ID: Grant G1001
                Categories
                Research Articles
                Behavioral/Cognitive

                magnetoencephalography,semantics,syntax,word lists
                magnetoencephalography, semantics, syntax, word lists

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