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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-12-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811921009927 |
| _version_ | 1819229473284816896 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-23T11:13:44Z |
| format | Article |
| id | doaj.art-e8680c7353a3428d9f9c7003fc319663 |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-23T11:13:44Z |
| publishDate | 2021-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-e8680c7353a3428d9f9c7003fc3196632022-12-21T17:49:17ZengElsevierNeuroImage1095-95722021-12-01245118720Functional mapping of language-related areas from natural, narrative speech during awake craniotomy surgeryTianyi Zhou0Tao Yu1Zheng Li2Xiaoxia Zhou3Jianbin Wen4Xiaoli Li5Center for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University at Zhuhai 519087, ChinaBeijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, ChinaCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University at Zhuhai 519087, ChinaBeijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, ChinaState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, ChinaCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University at Zhuhai 519087, China; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Corresponding author.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.http://www.sciencedirect.com/science/article/pii/S1053811921009927EpilepsyECoGTCAContinuous speech comprehension |
| spellingShingle | 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 NeuroImage Epilepsy ECoG TCA Continuous speech comprehension |
| title | 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_short | 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 |
| topic | Epilepsy ECoG TCA Continuous speech comprehension |
| url | http://www.sciencedirect.com/science/article/pii/S1053811921009927 |
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