Literature DB >> 29478856

Electrophysiological Correlates of Semantic Dissimilarity Reflect the Comprehension of Natural, Narrative Speech.

Michael P Broderick1, Andrew J Anderson2, Giovanni M Di Liberto3, Michael J Crosse4, Edmund C Lalor5.   

Abstract

People routinely hear and understand speech at rates of 120-200 words per minute [1, 2]. Thus, speech comprehension must involve rapid, online neural mechanisms that process words' meanings in an approximately time-locked fashion. However, electrophysiological evidence for such time-locked processing has been lacking for continuous speech. Although valuable insights into semantic processing have been provided by the "N400 component" of the event-related potential [3-6], this literature has been dominated by paradigms using incongruous words within specially constructed sentences, with less emphasis on natural, narrative speech comprehension. Building on the discovery that cortical activity "tracks" the dynamics of running speech [7-9] and psycholinguistic work demonstrating [10-12] and modeling [13-15] how context impacts on word processing, we describe a new approach for deriving an electrophysiological correlate of natural speech comprehension. We used a computational model [16] to quantify the meaning carried by words based on how semantically dissimilar they were to their preceding context and then regressed this measure against electroencephalographic (EEG) data recorded from subjects as they listened to narrative speech. This produced a prominent negativity at a time lag of 200-600 ms on centro-parietal EEG channels, characteristics common to the N400. Applying this approach to EEG datasets involving time-reversed speech, cocktail party attention, and audiovisual speech-in-noise demonstrated that this response was very sensitive to whether or not subjects understood the speech they heard. These findings demonstrate that, when successfully comprehending natural speech, the human brain responds to the contextual semantic content of each word in a relatively time-locked fashion.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  EEG; cocktail party; computational linguistics; cortical entrainment; multisensory integration; selective attention; semantic processing

Mesh:

Year:  2018        PMID: 29478856     DOI: 10.1016/j.cub.2018.01.080

Source DB:  PubMed          Journal:  Curr Biol        ISSN: 0960-9822            Impact factor:   10.834


  61 in total

1.  Rapid Transformation from Auditory to Linguistic Representations of Continuous Speech.

Authors:  Christian Brodbeck; L Elliot Hong; Jonathan Z Simon
Journal:  Curr Biol       Date:  2018-11-29       Impact factor: 10.834

Review 2.  Machine Learning Approaches to Analyze Speech-Evoked Neurophysiological Responses.

Authors:  Zilong Xie; Rachel Reetzke; Bharath Chandrasekaran
Journal:  J Speech Lang Hear Res       Date:  2019-03-25       Impact factor: 2.297

3.  Cortical encoding of acoustic and linguistic rhythms in spoken narratives.

Authors:  Cheng Luo; Nai Ding
Journal:  Elife       Date:  2020-12-21       Impact factor: 8.140

4.  Dynamic EEG analysis during language comprehension reveals interactive cascades between perceptual processing and sentential expectations.

Authors:  McCall E Sarrett; Bob McMurray; Efthymia C Kapnoula
Journal:  Brain Lang       Date:  2020-10-18       Impact factor: 2.381

5.  Hierarchical Encoding of Attended Auditory Objects in Multi-talker Speech Perception.

Authors:  James O'Sullivan; Jose Herrero; Elliot Smith; Catherine Schevon; Guy M McKhann; Sameer A Sheth; Ashesh D Mehta; Nima Mesgarani
Journal:  Neuron       Date:  2019-10-21       Impact factor: 17.173

6.  Dissociable effects of prediction and integration during language comprehension: evidence from a large-scale study using brain potentials.

Authors:  Mante S Nieuwland; Dale J Barr; Federica Bartolozzi; Simon Busch-Moreno; Emily Darley; David I Donaldson; Heather J Ferguson; Xiao Fu; Evelien Heyselaar; Falk Huettig; E Matthew Husband; Aine Ito; Nina Kazanina; Vita Kogan; Zdenko Kohút; Eugenia Kulakova; Diane Mézière; Stephen Politzer-Ahles; Guillaume Rousselet; Shirley-Ann Rueschemeyer; Katrien Segaert; Jyrki Tuomainen; Sarah Von Grebmer Zu Wolfsthurn
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-12-16       Impact factor: 6.237

7.  Two Distinct Neural Timescales for Predictive Speech Processing.

Authors:  Peter W Donhauser; Sylvain Baillet
Journal:  Neuron       Date:  2019-12-02       Impact factor: 17.173

Review 8.  Grounding the neurobiology of language in first principles: The necessity of non-language-centric explanations for language comprehension.

Authors:  Uri Hasson; Giovanna Egidi; Marco Marelli; Roel M Willems
Journal:  Cognition       Date:  2018-07-24

9.  (Early) context effects on event-related potentials over natural inputs.

Authors:  Shaorong Yan; T Florian Jaeger
Journal:  Lang Cogn Neurosci       Date:  2019-03-30       Impact factor: 2.331

10.  Semantic Context Enhances the Early Auditory Encoding of Natural Speech.

Authors:  Michael P Broderick; Andrew J Anderson; Edmund C Lalor
Journal:  J Neurosci       Date:  2019-08-01       Impact factor: 6.167

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