Listening effort is increasingly recognized as a factor in communication, particularly for and with nonnative speakers, for the elderly, for individuals with hearing impairment and/or for those working in noise. However, as highlighted by McGarrigle et al., International Journal of Audiology, 2014, 53, 433–445, the term “listening effort” encompasses a wide variety of concepts, including the engagement and control of multiple possibly distinct neural systems for information processing, and the affective response to the expenditure of those resources in a given context. Thus, experimental or clinical methods intended to objectively quantify listening effort may ultimately reflect a complex interaction between the operations of one or more of those information processing systems, and/or the affective and motivational response to the demand on those systems. Here we examine theoretical, behavioral, and psychophysiological factors related to resolving the question of what we are measuring, and why, when we measure “listening effort.” This article is categorized under: Linguistics > Language in Mind and Brain Psychology > Theory and Methods Psychology > Attention Psychology > Emotion and Motivation

Listeners vary in their ability to understand speech in adverse conditions. Differences in both cognitive and linguistic capacities play a role, but increasing evidence suggests that such factors may contribute differentially depending on the listening challenge. Here, we used multilevel modeling to evaluate contributions of individual differences in age, hearing thresholds, vocabulary, selective attention, working memory capacity, personality traits, and noise sensitivity to variability in measures of comprehension and listening effort in two listening conditions. A total of 35 participants completed a battery of cognitive and linguistic tests as well as a spoken story comprehension task using (1) native-accented English speech masked by speech-shaped noise and (2) nonnative accented English speech without masking. Masker levels were adjusted individually to ensure each participant would show (close to) equivalent word recognition performance across the two conditions. Dependent measures included comprehension tests results, self-rated effort, and electrodermal, cardiovascular, and facial electromyographic measures associated with listening effort. Results showed varied patterns of responsivity across different dependent measures as well as across listening conditions. In particular, results suggested that working memory capacity may play a greater role in the comprehension of nonnative accented speech than noise-masked speech, while hearing acuity and personality may have a stronger influence on physiological responses affected by demands of understanding speech in noise. Furthermore, electrodermal measures may be more strongly affected by affective response to noise-related interference while cardiovascular responses may be more strongly affected by demands on working memory and lexical access.

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Oscillatory brain activity in the alpha frequency range (7–13 Hz) is commonly implicated in the attention literature, though the exact role it plays in facilitating attention is debated. A popular functional theory, the “alpha suppression hypothesis,” suggests that changes in alpha amplitudes can be interpreted as a marker of active suppression of neural assemblies that code for distractors. Recent studies of visual selective attention have questioned this hypothesis. In the auditory attention literature, alpha power during listening has been reported to fluctuate with the temporal structure of target sounds. Yet, studies examining whether purely endogenous alpha activity during orienting of attention predicts trends in subsequent task performance are limited. The current study addresses this gap by quantifying changes in alpha power observed in the electroencephalography (EEG) signal during an auditory selective attention task. This analysis focuses on the preparatory period, a window of time following a directional attention cue but preceding the auditory stimulus. Preliminary results suggest the presence of robust endogenous oscillations between 10 and 20 Hz during this preparatory period. Further analysis will compare the strength of these rhythms to individual differences in task performance, to variations in task demands, and to within-individual trial-to-trail variations in perceptual outcomes.

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