Physiological Measures of Reduced Listening Effort in Active Noise Canceling: Evidence From a Low-β Functional...

In this study, we investigated the neurophysiological impact of active noise cancellation (ANC) technology on auditory-cognitive processing and listening effort, addressing a critical gap in the literature on ANC efficacy. Although ANC is increasingly adopted in contemporary devices, its influence on underlying neurophysiological mechanisms remains underexplored. Given that current assessment approaches rely predominantly on subjective measures, we employed a multi-condition experimental design integrating subjective self-reports with electroencephalographic assessments, thereby providing a more comprehensive evaluation of ANC's capacity to mitigate cognitive load.

Thirty participants underwent comprehensive audiological testing and cognitive event-related potential recordings during an auditory oddball paradigm to elucidate the efficacy of ANC functionality and its impact on cognitive processing, as indexed by the P3 component. Functional connectivity was quantified using the source-localized weighted phase-lag index, and graph-theory-based network analysis was applied to assess changes in neural efficiency under noisy conditions with and without ANC activation.

The analyses revealed significant alterations in low-β-band functional architecture across the central executive, dorsal attention, salience, and default mode networks during effortless listening with ANC enabled, compared with the effortful listening condition. Subjective listening effort correlated with network efficiency in the left posterior middle frontal gyrus, dorsal anterior cingulate cortex, and inferior parietal lobule during ANC-aided effortless listening tasks.

Our findings suggest that ANC activation significantly reduces neural processing demands across key cognitive networks during effortless listening. These.

reinforce the role of ANC in alleviating cognitive load and enhancing neural efficiency in auditory-cognitive processing. Furthermore, the findings provide empirical support to inform evidence-based noise mitigation strategies in both clinical and ecological contexts.