Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairment
In the literature, auditory attention is explored through neural speech tracking, primarily entailing modeling and analyzing electroencephalography (EEG) responses to natural speech via linear filtering. Our study takes a novel approach, introducing an enhanced coherence estimation technique to asse...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2024.1415397/full |
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| author | Oskar Keding Emina Alickovic Emina Alickovic Martin A. Skoglund Martin A. Skoglund Maria Sandsten |
| author_facet | Oskar Keding Emina Alickovic Emina Alickovic Martin A. Skoglund Martin A. Skoglund Maria Sandsten |
| author_sort | Oskar Keding |
| collection | DOAJ |
| description | In the literature, auditory attention is explored through neural speech tracking, primarily entailing modeling and analyzing electroencephalography (EEG) responses to natural speech via linear filtering. Our study takes a novel approach, introducing an enhanced coherence estimation technique to assess the strength of neural speech tracking. This enables effective discrimination between attended and ignored speech. To mitigate the impact of colored noise in EEG, we address two biases–overall coherence-level bias and spectral peak-shifting bias. In a listening study involving 32 participants with hearing impairment, tasked with attending to competing talkers in background noise, our coherence-based method effectively discerns EEG representations of attended and ignored speech. We comprehensively analyze frequency bands, individual frequencies, and EEG channels. Frequency bands of importance are shown to be delta, theta and alpha, and the important EEG channels are the central. Lastly, we showcase coherence differences across different noise reduction settings implemented in hearing aids (HAs), underscoring our method's potential to objectively assess auditory attention and enhance HA efficacy. |
| format | Article |
| id | doaj-art-9e30c4a6533b466d87200bb3397e4577 |
| institution | OA Journals |
| issn | 1662-453X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj-art-9e30c4a6533b466d87200bb3397e45772025-08-20T02:12:33ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2024-11-011810.3389/fnins.2024.14153971415397Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairmentOskar Keding0Emina Alickovic1Emina Alickovic2Martin A. Skoglund3Martin A. Skoglund4Maria Sandsten5Centre for Mathematical Sciences, Lund University, Lund, SwedenEriksholm Research Centre, Oticon A/S, Snekkersten, DenmarkDepartment of Electrical Engineering, Linköping University, Linköping, SwedenEriksholm Research Centre, Oticon A/S, Snekkersten, DenmarkDepartment of Electrical Engineering, Linköping University, Linköping, SwedenCentre for Mathematical Sciences, Lund University, Lund, SwedenIn the literature, auditory attention is explored through neural speech tracking, primarily entailing modeling and analyzing electroencephalography (EEG) responses to natural speech via linear filtering. Our study takes a novel approach, introducing an enhanced coherence estimation technique to assess the strength of neural speech tracking. This enables effective discrimination between attended and ignored speech. To mitigate the impact of colored noise in EEG, we address two biases–overall coherence-level bias and spectral peak-shifting bias. In a listening study involving 32 participants with hearing impairment, tasked with attending to competing talkers in background noise, our coherence-based method effectively discerns EEG representations of attended and ignored speech. We comprehensively analyze frequency bands, individual frequencies, and EEG channels. Frequency bands of importance are shown to be delta, theta and alpha, and the important EEG channels are the central. Lastly, we showcase coherence differences across different noise reduction settings implemented in hearing aids (HAs), underscoring our method's potential to objectively assess auditory attention and enhance HA efficacy.https://www.frontiersin.org/articles/10.3389/fnins.2024.1415397/fullcoherenceEEGneural speech trackingauditory attentionmultitapershearing impairment |
| spellingShingle | Oskar Keding Emina Alickovic Emina Alickovic Martin A. Skoglund Martin A. Skoglund Maria Sandsten Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairment Frontiers in Neuroscience coherence EEG neural speech tracking auditory attention multitapers hearing impairment |
| title | Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairment |
| title_full | Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairment |
| title_fullStr | Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairment |
| title_full_unstemmed | Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairment |
| title_short | Novel bias-reduced coherence measure for EEG-based speech tracking in listeners with hearing impairment |
| title_sort | novel bias reduced coherence measure for eeg based speech tracking in listeners with hearing impairment |
| topic | coherence EEG neural speech tracking auditory attention multitapers hearing impairment |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2024.1415397/full |
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