@inproceedings{367e86c6acbd41ed8f49b03288fe5315,
title = "EEG Phase Synchrony Reflects SNR Levels During Continuous Speech-In-Noise Tasks",
abstract = "Comprehension of speech in noise is a challenge for hearing-impaired (HI) individuals. Electroencephalography (EEG) provides a tool to investigate the effect of different levels of signal-to-noise ratio (SNR) of the speech. Most studies with EEG have focused on spectral power in well-defined frequency bands such as alpha band. In this study, we investigate how local functional connectivity, i.e. functional connectivity within a localized region of the brain, is affected by two levels of SNR. Twenty-two HI participants performed a continuous speech in noise task at two different SNRs (+3 dB and +8 dB). The local connectivity within eight regions of interest was computed by using a multivariate phase synchrony measure on EEG data. The results showed that phase synchrony increased in the parietal and frontal area as a response to increasing SNR. We contend that local connectivity measures can be used to discriminate between speech-evoked EEG responses at different SNRs.",
author = "Baboukani, {Payam Shahsavari} and Carina Graversen and Emina Alickovic and Jan {\O}stergaard",
year = "2021",
month = oct,
doi = "10.1109/EMBC46164.2021.9630139",
language = "English",
isbn = "978-1-7281-1180-3",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "IEEE",
pages = "531--534",
booktitle = "43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)",
address = "United States",
note = "2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) ; Conference date: 01-11-2021 Through 05-11-2021",
}