Mutual Information Analysis of Neural Representations of Speech in Noise in the Aging Midbrain

Abstract

Younger adults with normal hearing can typically understand speech in the presence of a competing speaker without much effort, but this ability to understand speech in challenging conditions deteriorates with age. Older adults, even with clinically normal hearing, often have problems understand- ing speech in noise. Earlier auditory studies using the frequency- following response (FFR), primarily believed to be generated by the midbrain, demonstrated age-related neural deficits when analyzed with traditional measures. Here we use a mutual information paradigm to analyze the FFR to speech (masked by a competing speech signal) by estimating the amount of stimulus information contained in the FFR. Our results show, first, a broadband informational loss associ- ated with aging for both FFR amplitude and phase. Second, this age-related loss of information is more severe in higher-frequency FFR bands (several hundred hertz). Third, the mutual information between the FFR and the stimulus decreases as noise level increases for both age groups. Fourth, older adults benefit neurally, i.e., show a reduction in loss of information, when the speech masker is changed from meaningful (talker speaking a language that they can compre- hend, such as English) to meaningless (talker speaking a language that they cannot comprehend, such as Dutch). This benefit is not seen in younger listeners, which suggests that age-related informational loss may be more severe when the speech masker is meaningful than when it is meaningless. In summary, as a method, mutual information analysis can unveil new results that traditional measures may not have enough statistical power to assess.

Publication

Peng Zan, Alessandro Presacco, Samira Anderson, and Jonathan Z. Simon. (2019). “Mutual Information Analysis of Neural Representations of Speech in Noise in the Aging Midbrain” Journal of Nuerophysiology. 122(6):2372-2387. Download Paper