Publication: Prediction of acoustic tinnitus suppression using resting-state EEG via explainable AI approach
Prediction of acoustic tinnitus suppression using resting-state EEG via explainable AI approach
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Shabestari, P. S., Schoisswohl, S., Wellauer, Z., Naas, A., Kleinjung, T., Schecklmann, M., Langguth, B., & Neff, P. (2025). Prediction of acoustic tinnitus suppression using resting-state EEG via explainable AI approach. Scientific Reports, 15(1), 10968. https://doi.org/10.1038/s41598-025-95351-w
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Abstract
Tinnitus is defined as the perception of sound without an external source. Its perceptual suppression or on/off states remain poorly understood. This study investigates neural traits linked to brief acoustic tinnitus suppression (BATS) using naive resting-state EEG (closed eyes) from 102 individuals. A set of EEG features (band power, entropy, aperiodic slope and offset of the EEG spectrum, and connectivity) and standard classifiers were applied achieving consistent high accuracy across data splits: 98% for sensor and 86% for source m
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- Shabestari, Payam S
- Schoisswohl, Stefan
- Wellauer, Zino
- Naas, Adrian
- Kleinjung, Tobias
- Schecklmann, Martin
- Langguth, Berthold
- Neff, Patrick
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Shabestari, P. S., Schoisswohl, S., Wellauer, Z., Naas, A., Kleinjung, T., Schecklmann, M., Langguth, B., & Neff, P. (2025). Prediction of acoustic tinnitus suppression using resting-state EEG via explainable AI approach. Scientific Reports, 15(1), 10968. https://doi.org/10.1038/s41598-025-95351-w
