Autonomic Decoupling in Listening Effort: Why Single-Channel Biomarkers Fail

Autonomic Decoupling in Listening Effort: Why Single-Channel Biomarkers Fail

Abstract

Abstract
Objective: Current theoretical frameworks operationalize listening effort as a monolithic, unified sympathetic response, driving the search for a single universal clinical biomarker (predominantly task-evoked pupillometry). This study stress-tests the "unified arousal" hypothesis by evaluating the continuous cross-modal overlap of autonomic and cortical responses during a speech-in-noise paradigm. Design: Continuous, simultaneous physiological tracking-including Pupillometry (Locus Coeruleus), Galvanic Skin Response (GSR), Cardiac Inter-beat Interval (IBI), Respiration Rate, and Frontal Alpha EEG-was conducted on N=28 normal-hearing adults. Participants completed a continuous speech-in-noise task (OLSA) across varying Signal-to-Noise Ratios (+12 dB to -16 dB). A continuous Spearman's rank correlation matrix was utilized to assess physiological decoupling, and Linear Mixed-Effects (LME) models isolated single-trial effort dynamics. Results: The data revealed a lack of meaningful cross-modal overlap. Continuous correlation matrices demonstrated negligible relationships across the four autonomic channels (all p>0.05). Trial-level cross-correlations confirmed extremely weak functional coupling across the autonomic nervous system (mean effect sizes strictly bounded between {rho}=-0.042 and {rho}=0.065). These negligible effect sizes fail to support the "unified sympathetic storm" hypothesis, providing strong evidence for heavy physiological decoupling, where autonomic channels fail to synchronize during acute stress. Furthermore, subjective retrospective effort was highly collinear with objective task difficulty (r=0.848), offering limited independent tracking of internal state. Conclusions: Listening effort is not a unified whole-body state; it is an idiosyncratic, heavily decoupled biological routing process. The reliance on single-channel tracking is structurally flawed, as it is blind to autonomic diversity. Future models of cognitive exertion must decouple generalized capacity allocation from idiosyncratic autonomic routing, and experimental paradigms must separate genuine effortful limits from active task withdrawal.
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