Borges Heidi B, Zaar Johannes, Alickovic Emina, Christensen Christian B, Kidmose Preben
Eriksholm Research Centre, Snekkersten, Denmark.
Department of Electrical and Computer Engineering, Aarhus University, Aarhus, Denmark.
Eur J Neurosci. 2025 Mar;61(6):e70083. doi: 10.1111/ejn.70083.
This study investigates the potential of speech reception threshold (SRT) estimation through electroencephalography (EEG) based envelope reconstruction techniques with continuous speech. Additionally, we investigate the influence of the stimuli's signal-to-noise ratio (SNR) on the temporal response function (TRF). Twenty young normal-hearing participants listened to audiobook excerpts with varying background noise levels while EEG was recorded. A linear decoder was trained to reconstruct the speech envelope from the EEG data. The reconstruction accuracy was calculated as the Pearson's correlation between the reconstructed and actual speech envelopes. An EEG SRT estimate (SRT) was obtained as the midpoint of a sigmoid function fitted to the reconstruction accuracy versus SNR data points. Additionally, the TRF was estimated at each SNR level, followed by a statistical analysis to reveal significant effects of SNR levels on the latencies and amplitudes of the most prominent components. The SRT was within 3 dB of the behavioral SRT for all participants. The TRF analysis showed a significant latency decrease for N1 and P2 and a significant amplitude magnitude increase for N1 and P2 with increasing SNR. The results suggest that both envelope reconstruction accuracy and the TRF components are influenced by changes in SNR, indicating they may be linked to the same underlying neural process.
本研究通过基于脑电图（EEG）的包络重建技术，利用连续语音来探究言语接受阈（SRT）估计的潜力。此外，我们还研究了刺激信号噪声比（SNR）对时间响应函数（TRF）的影响。20名听力正常的年轻参与者在记录脑电图时，收听了具有不同背景噪声水平的有声读物节选。训练了一个线性解码器，以从脑电图数据中重建语音包络。重建精度通过重建的语音包络与实际语音包络之间的皮尔逊相关性来计算。将脑电图SRT估计值（SRT）作为拟合到重建精度与SNR数据点的S形函数的中点。此外，在每个SNR水平估计TRF，然后进行统计分析，以揭示SNR水平对最突出成分的潜伏期和振幅的显著影响。所有参与者的SRT均在行为SRT的3dB范围内。TRF分析表明，随着SNR的增加，N1和P2的潜伏期显著缩短，N1和P2的振幅显著增大。结果表明，包络重建精度和TRF成分均受SNR变化的影响，表明它们可能与相同的潜在神经过程相关。
