###### Abstract  
Noise reduction (NR) algorithms are employed in nearly all commercially available hearing aids to attenuate background noise. However, NR processing also involves undesirable speech distortions, leading to variability in hearing outcomes among individuals with different noise tolerance. Leveraging 30 participants with normal hearing engaged in speech-in-noise tasks, the present study examined whether the cortical measure of neural signal-to-noise ratio (SNR)--the amplitude ratio of auditory evoked responses to target speech onset and noise onset--could predict individual variability in NR outcomes with varying strength, thus serving as a reliable indicator of individual noise tolerance. In addition, we also measured subjective ratings of noise tolerance to see if these measures could capture different perspectives on individual noise tolerance. Results indicated a significant correlation between neural SNR and NR outcomes that intensified with increasing strength of NR processing. While subjective ratings of noise tolerance were not correlated with the neural SNR, noise-tolerance ratings could predict outcomes with stronger NR processing and account for additional variance in the regression model, although the effect was limited. Our findings underscore the importance of accurately assessing an individual's noise tolerance characteristics in predicting perceptual benefits from various NR processing methods and suggest the advantage of incorporating both cortical and subjective measures in the relevant methodologies. noise reduction; noise reduction strength; EEG; noise tolerance; hearing aids +
Footnote †: journal: Medical  
psychoacoustical and audiological measures, those approaches only partially accounted for individual noise tolerance that may drive this variability [9; 16; 20; 21], suggesting the need for alternative methods sensitive enough to capture the neurophysiological mechanisms underlying the variability in individual noise tolerance and NR outcomes. Several studies indicated that cortical auditory evoked potential measurements, such as N1 and P2 latency and amplitude, can be predictive of individual speech perception ability in noise in populations of various ages and hearing statuses [22; 23; 24]. Emerging studies have also shown that neural tracking of the speech envelope might serve as an objective predictor of speech understanding performance in noisy environments [25; 26; 27] and that it could indicate enhanced neural representation of speech due to NR schemes [28; 29]. Although critical, both the aspect of an individual's ability to suppress the noise--potentially by engaging top-down attentional modulation even before encountering target speech sounds [30]--and the relationship between said ability and hearing outcomes have been largely overlooked in existing studies. More specifically, developing cortical measures that reflect an individual's efficiency in both suppression of noise and neural encoding of target speech remains understudied, and using those cortical measures to empirically investigate the neurophysiological mechanisms underlying individual variability in NR outcomes has been minimally addressed within the field. Our recent work introduced a novel cortical measure for quantifying individual noise tolerance at the sensor- or source-space level [30; 31]. This approach hinged on respective cortical auditory responses to target speech onset and responses to noise onset, computing the amplitude ratio between these responses, named the _neural signal-to-noise ratio_ (SNR) [31]. The neural SNR can provide a unique means of measuring noise tolerance, consistent with the literature indicating the increased neural form of target-to-masker ratios due to successful auditory scene analysis [32; 33]. Our latest studies showed that the neural SNR can predict behavioral speech-in-noise performance in people with normal hearing [30] and in a large cohort of cochlear implant users [34; 35], and NR outcomes in another cohort of people with normal hearing [31].