Evaluating aperiodic and periodic neural activity as markers of listening effort in speech perception.

Auditory perception & cognition Pub Date : 2024-01-01 Epub Date: 2024-09-02 DOI:10.1080/25742442.2024.2395217
Sarah J Woods, Jack W Silcox, Brennan R Payne
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Abstract

Listening effort (LE) is critical to understanding speech perception in acoustically challenging environments. EEG alpha power has emerged as a potential neural correlate of LE. However, the magnitude and direction of the relationship between acoustic challenge and alpha power has been inconsistent in the literature. In the current study, a secondary data analysis of Silcox and Payne (2021), we examine the broadband 1/f-like exponent and offset of the EEG power spectrum as measures of aperiodic neural activity during effortful speech perception and the influence of this aperiodic activity on reliable estimation of periodic (i.e., alpha) neural activity. EEG was continuously recorded during sentence listening and the broadband (1-40 Hz) EEG power spectrum was computed for each participant for quiet and noise trials separately. Using the specparam algorithm, we decomposed the power spectrum into both aperiodic and periodic components and found that broadband aperiodic activity was sensitive to background noise during speech perception and additionally impacted the measurement of noise-induced changes on alpha oscillations. We discuss the implications of these results for the LE and neural speech processing literatures.

评估非周期性和周期性神经活动作为语音感知中听力努力的标记。
聆听努力(LE)对于理解声学挑战环境中的语音感知至关重要。脑电图α功率已成为聆听强度的潜在神经相关因素。然而,声学挑战与阿尔法功率之间关系的大小和方向在文献中并不一致。本研究是对 Silcox 和 Payne(2021 年)的二次数据分析,我们将脑电图功率谱的宽带 1/f 样指数和偏移量作为努力言语感知期间非周期性神经活动的测量指标,并研究这种非周期性活动对周期性(即α)神经活动可靠估计的影响。在听句子期间连续记录脑电图,并分别计算每位受试者在安静和噪音试验中的宽带(1-40 Hz)脑电图功率谱。通过使用 specparam 算法,我们将功率谱分解为非周期性和周期性成分,并发现宽带非周期性活动对语音感知过程中的背景噪声非常敏感,而且还会影响噪声引起的阿尔法振荡变化的测量。我们讨论了这些结果对 LE 和神经语音处理文献的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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