Functional mapping of language-related areas from natural, narrative speech during awake craniotomy surgery

Accurate localization of brain regions responsible for language and cognitive functions in epilepsy patients is important. Electrocorticography (ECoG)-based real-time functional mapping (RTFM) has been shown to be a safer alternative to electrical cortical stimulation mapping (ESM), which is current...

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Autores principales:	Tianyi Zhou, Tao Yu, Zheng Li, Xiaoxia Zhou, Jianbin Wen, Xiaoli Li
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Epilepsy ECoG TCA Continuous speech comprehension Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/e8680c7353a3428d9f9c7003fc319663
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id	oai:doaj.org-article:e8680c7353a3428d9f9c7003fc319663
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spelling	oai:doaj.org-article:e8680c7353a3428d9f9c7003fc3196632021-11-18T04:44:59ZFunctional mapping of language-related areas from natural, narrative speech during awake craniotomy surgery1095-957210.1016/j.neuroimage.2021.118720https://doaj.org/article/e8680c7353a3428d9f9c7003fc3196632021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1053811921009927https://doaj.org/toc/1095-9572Accurate localization of brain regions responsible for language and cognitive functions in epilepsy patients is important. Electrocorticography (ECoG)-based real-time functional mapping (RTFM) has been shown to be a safer alternative to electrical cortical stimulation mapping (ESM), which is currently the clinical/gold standard. Conventional methods for analyzing RTFM data mostly account for the ECoG signal in certain frequency bands, especially high gamma. Compared to ESM, they have limited accuracy when assessing channel responses. In the present study, we developed a novel RTFM method based on tensor component analysis (TCA) to address the limitations of current estimation methods. Our approach analyzes the whole frequency spectrum of the ECoG signal during natural continuous speech. We construct third-order tensors that contain multichannel time-frequency information and use TCA to extract low-dimensional temporal, spectral and spatial modes. Temporal modulation scores (correlation values) are then calculated between the time series of voice envelope features and TCA-estimated temporal courses, and significant temporal modulation determines which components' channel weightings are displayed to the neurosurgeon as a guide for follow-up ESM. In our experiments, data from thirteen patients with refractory epilepsy were recorded during preoperative evaluation for their epileptogenic zones (EZs), which were located adjacent to the eloquent cortex. Our results showed higher detection accuracy of our proposed method in a narrative speech task, suggesting that our method complements ESM and is an improvement over the prior RTFM method. To our knowledge, this is the first TCA-based method to pinpoint language-specific brain regions during continuous speech that uses whole-band ECoG.Tianyi ZhouTao YuZheng LiXiaoxia ZhouJianbin WenXiaoli LiElsevierarticleEpilepsyECoGTCAContinuous speech comprehensionNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENNeuroImage, Vol 245, Iss , Pp 118720- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Epilepsy ECoG TCA Continuous speech comprehension Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Epilepsy ECoG TCA Continuous speech comprehension Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Tianyi Zhou Tao Yu Zheng Li Xiaoxia Zhou Jianbin Wen Xiaoli Li Functional mapping of language-related areas from natural, narrative speech during awake craniotomy surgery
description	Accurate localization of brain regions responsible for language and cognitive functions in epilepsy patients is important. Electrocorticography (ECoG)-based real-time functional mapping (RTFM) has been shown to be a safer alternative to electrical cortical stimulation mapping (ESM), which is currently the clinical/gold standard. Conventional methods for analyzing RTFM data mostly account for the ECoG signal in certain frequency bands, especially high gamma. Compared to ESM, they have limited accuracy when assessing channel responses. In the present study, we developed a novel RTFM method based on tensor component analysis (TCA) to address the limitations of current estimation methods. Our approach analyzes the whole frequency spectrum of the ECoG signal during natural continuous speech. We construct third-order tensors that contain multichannel time-frequency information and use TCA to extract low-dimensional temporal, spectral and spatial modes. Temporal modulation scores (correlation values) are then calculated between the time series of voice envelope features and TCA-estimated temporal courses, and significant temporal modulation determines which components' channel weightings are displayed to the neurosurgeon as a guide for follow-up ESM. In our experiments, data from thirteen patients with refractory epilepsy were recorded during preoperative evaluation for their epileptogenic zones (EZs), which were located adjacent to the eloquent cortex. Our results showed higher detection accuracy of our proposed method in a narrative speech task, suggesting that our method complements ESM and is an improvement over the prior RTFM method. To our knowledge, this is the first TCA-based method to pinpoint language-specific brain regions during continuous speech that uses whole-band ECoG.
format	article
author	Tianyi Zhou Tao Yu Zheng Li Xiaoxia Zhou Jianbin Wen Xiaoli Li
author_facet	Tianyi Zhou Tao Yu Zheng Li Xiaoxia Zhou Jianbin Wen Xiaoli Li
author_sort	Tianyi Zhou
title	Functional mapping of language-related areas from natural, narrative speech during awake craniotomy surgery
title_short	Functional mapping of language-related areas from natural, narrative speech during awake craniotomy surgery
title_full	Functional mapping of language-related areas from natural, narrative speech during awake craniotomy surgery
title_fullStr	Functional mapping of language-related areas from natural, narrative speech during awake craniotomy surgery
title_full_unstemmed	Functional mapping of language-related areas from natural, narrative speech during awake craniotomy surgery
title_sort	functional mapping of language-related areas from natural, narrative speech during awake craniotomy surgery
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/e8680c7353a3428d9f9c7003fc319663
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Functional mapping of language-related areas from natural, narrative speech during awake craniotomy surgery

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