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      Multimodal characterization of the semantic N400 response within a rapid evaluation brain vital sign framework

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          Abstract

          Background

          For nearly four decades, the N400 has been an important brainwave marker of semantic processing. It can be recorded non-invasively from the scalp using electrical and/or magnetic sensors, but largely within the restricted domain of research laboratories specialized to run specific N400 experiments. However, there is increasing evidence of significant clinical utility for the N400 in neurological evaluation, particularly at the individual level. To enable clinical applications, we recently reported a rapid evaluation framework known as “brain vital signs” that successfully incorporated the N400 response as one of the core components for cognitive function evaluation. The current study characterized the rapidly evoked N400 response to demonstrate that it shares consistent features with traditional N400 responses acquired in research laboratory settings—thereby enabling its translation into brain vital signs applications.

          Methods

          Data were collected from 17 healthy individuals using magnetoencephalography (MEG) and electroencephalography (EEG), with analysis of sensor-level effects as well as evaluation of brain sources. Individual-level N400 responses were classified using machine learning to determine the percentage of participants in whom the response was successfully detected.

          Results

          The N400 response was observed in both M/EEG modalities showing significant differences to incongruent versus congruent condition in the expected time range (p < 0.05). Also as expected, N400-related brain activity was observed in the temporal and inferior frontal cortical regions, with typical left-hemispheric asymmetry. Classification robustly confirmed the N400 effect at the individual level with high accuracy (89%), sensitivity (0.88) and specificity (0.90).

          Conclusion

          The brain vital sign N400 characteristics were highly consistent with features of the previously reported N400 responses acquired using traditional laboratory-based experiments. These results provide important evidence supporting clinical translation of the rapidly acquired N400 response as a potential tool for assessments of higher cognitive functions.

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          Most cited references44

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          Towards a neural basis of auditory sentence processing.

          Functional dissociations within the neural basis of auditory sentence processing are difficult to specify because phonological, syntactic and semantic information are all involved when sentences are perceived. In this review I argue that sentence processing is supported by a temporo-frontal network. Within this network, temporal regions subserve aspects of identification and frontal regions the building of syntactic and semantic relations. Temporal analyses of brain activation within this network support syntax-first models because they reveal that building of syntactic structure precedes semantic processes and that these interact only during a later stage.
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            Reading senseless sentences: brain potentials reflect semantic incongruity.

            In a sentence reading task, words that occurred out of context were associated with specific types of event-related brain potentials. Words that were physically aberrant (larger than normal) elecited a late positive series of potentials, whereas semantically inappropriate words elicited a late negative wave (N400). The N400 wave may be an electrophysiological sign of the "reprocessing" of semantically anomalous information.
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              Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400.

              This paper describes recommended methods for the use of event-related brain potentials (ERPs) in clinical research and reviews applications to a variety of psychiatric and neurological disorders. Techniques are presented for eliciting, recording, and quantifying three major cognitive components with confirmed clinical utility: mismatch negativity (MMN), P300, and N400. Also highlighted are applications of each of the components as methods of investigating central nervous system pathology. The guidelines are intended to assist investigators who use ERPs in clinical research, in an effort to provide clear and concise recommendations and thereby to standardize methodology and facilitate comparability of data across laboratories.
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                Author and article information

                Contributors
                ssujoy@sfu.ca
                careesa.liu@sfu.ca
                xiaowei.song@fraserhealth.ca
                sficklin@sfu.ca
                tpc5@sfu.ca
                604-580-4926 , rdarcy@sfu.ca
                Journal
                J Transl Med
                J Transl Med
                Journal of Translational Medicine
                BioMed Central (London )
                1479-5876
                4 June 2018
                4 June 2018
                2018
                : 16
                : 151
                Affiliations
                [1 ]ISNI 0000 0004 1936 7494, GRID grid.61971.38, Faculty of Applied Science, , Simon Fraser University, ; Burnaby, BC Canada
                [2 ]Health Science and Innovation, Surrey Memorial Hospital, Fraser Health Authority, Surrey, BC Canada
                [3 ]HealthTech Connex Inc, Surrey, BC Canada
                [4 ]ISNI 0000 0004 0629 4716, GRID grid.460764.7, Surrey NeuroTech Lab, , Surrey Memorial Hospital, ; 13750 96 Avenue, Surrey, BC V3V 1Z2 Canada
                [5 ]ISNI 0000 0004 0629 4716, GRID grid.460764.7, ImageTech Lab, , Surrey Memorial Hospital, ; 13750 96 Av, Surrey, BC V3V 1Z2 Canada
                Article
                1527
                10.1186/s12967-018-1527-2
                5987605
                29866112
                d6e7d9d9-00c7-4e88-8ebd-8eea96573327
                © The Author(s) 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 3 March 2018
                : 26 May 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100004489, Mitacs;
                Award ID: IT03240
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;
                Award ID: GSD-140381
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100004326, Simon Fraser University;
                Award ID: Multi-Year Funding Award
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000038, Natural Sciences and Engineering Research Council of Canada;
                Award ID: RGPIN-2015-04018
                Award Recipient :
                Funded by: Surrey Memorial Hospital Foundation
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                Medicine
                n400,erp,meg,semantic language,clinical application
                Medicine
                n400, erp, meg, semantic language, clinical application

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