5 research outputs found
Dynamic EEG analysis during language comprehension reveals interactive cascades between perceptual processing and sentential expectations
Available online 18 October 2020.Understanding spoken language requires analysis of the rapidly unfolding speech signal at multiple levels: acoustic, phonological, and semantic. However, there is not yet a comprehensive picture of how these levels relate. We recorded electroencephalography (EEG) while listeners (N = 31) heard sentences in which we manipulated acoustic ambiguity (e.g., a bees/peas continuum) and sentential expectations (e.g., Honey is made by bees). EEG was analyzed with a mixed effects model over time to quantify how language processing cascades proceed on a millisecond-by-millisecond basis. Our results indicate: (1) perceptual processing and memory for fine-grained acoustics is preserved in brain activity for up to 900 msec; (2) contextual analysis begins early and is graded with respect to the acoustic signal; and (3) top-down predictions influence perceptual processing in some cases, however, these predictions are available simultaneously with the veridical signal. These mechanistic insights provide a basis for a better understanding of the cortical language network.This work was supported by NIH grant DC008089 awarded to BM.
This work was partially supported by the Basque Government through
the BERC 2018–2021 program and by the Spanish State Research
Agency through BCBL Severo Ochoa excellence accreditation SEV-2015-
0490, as well as by a postdoctoral grant from the Spanish Ministry of
Economy and Competitiveness (MINECO; reference FJCI-2016-28019),
awarded to EK
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Author Correction: Immediate neural impact and incomplete compensation after semantic hub disconnection
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Immediate neural impact and incomplete compensation after semantic hub disconnection
The human brain extracts meaning using an extensive neural system for semantic knowledge. Whether broadly distributed systems depend on or can compensate after losing a highly interconnected hub is controversial. We report intracranial recordings from two patients during a speech prediction task, obtained minutes before and after neurosurgical treatment requiring disconnection of the left anterior temporal lobe (ATL), a candidate semantic knowledge hub. Informed by modern diaschisis and predictive coding frameworks, we tested hypotheses ranging from solely neural network disruption to complete compensation by the indirectly affected language-related and speech-processing sites. Immediately after ATL disconnection, we observed neurophysiological alterations in the recorded frontal and auditory sites, providing direct evidence for the importance of the ATL as a semantic hub. We also obtained evidence for rapid, albeit incomplete, attempts at neural network compensation, with neural impact largely in the forms stipulated by the predictive coding framework, in specificity, and the modern diaschisis framework, more generally. The overall results validate these frameworks and reveal an immediate impact and capability of the human brain to adjust after losing a brain hub
Recommended from our members
Immediate neural impact and incomplete compensation after semantic hub disconnection
The human brain extracts meaning using an extensive neural system for semantic knowledge. Whether broadly distributed systems depend on or can compensate after losing a highly interconnected hub is controversial. We report intracranial recordings from two patients during a speech prediction task, obtained minutes before and after neurosurgical treatment requiring disconnection of the left anterior temporal lobe (ATL), a candidate semantic knowledge hub. Informed by modern diaschisis and predictive coding frameworks, we tested hypotheses ranging from solely neural network disruption to complete compensation by the indirectly affected language-related and speech-processing sites. Immediately after ATL disconnection, we observed neurophysiological alterations in the recorded frontal and auditory sites, providing direct evidence for the importance of the ATL as a semantic hub. We also obtained evidence for rapid, albeit incomplete, attempts at neural network compensation, with neural impact largely in the forms stipulated by the predictive coding framework, in specificity, and the modern diaschisis framework, more generally. The overall results validate these frameworks and reveal an immediate impact and capability of the human brain to adjust after losing a brain hub
Recommended from our members
Immediate neural impact and incomplete compensation after semantic hub disconnection
The human brain extracts meaning using an extensive neural system for semantic knowledge. Whether broadly distributed systems depend on or can compensate after losing a highly interconnected hub is controversial. We report intracranial recordings from two patients during a speech prediction task, obtained minutes before and after neurosurgical treatment requiring disconnection of the left anterior temporal lobe (ATL), a candidate semantic knowledge hub. Informed by modern diaschisis and predictive coding frameworks, we tested hypotheses ranging from solely neural network disruption to complete compensation by the indirectly affected language-related and speech-processing sites. Immediately after ATL disconnection, we observed neurophysiological alterations in the recorded frontal and auditory sites, providing direct evidence for the importance of the ATL as a semantic hub. We also obtained evidence for rapid, albeit incomplete, attempts at neural network compensation, with neural impact largely in the forms stipulated by the predictive coding framework, in specificity, and the modern diaschisis framework, more generally. The overall results validate these frameworks and reveal an immediate impact and capability of the human brain to adjust after losing a brain hub