Biology subjects

Bleeck, S.

Publications and source records attributed to Bleeck, S..

3 recordsLinked to original sources

bioRxiv2026

The Effect of Plosive Content on the Loudness Perception of Vowel-Consonant-Vowel Syllables in Listeners with Sensorineural Hearing Loss

Objective: This study investigated whether plosive consonants carry a perceptual loudness weighting that significantly exceeds that of non-plosive consonants when judged by hearing-impaired listeners. Design: A prospective loudness matching experiment utilizing the method of adjustment. Study Sample: 19 consenting native English speakers (Mean age: 61.4, SD: 16.4) with bilateral mild to moderate high-frequency sensorineural hearing loss, indicative of presbycusis. Stimuli: 13 vowel-consonant-vowel (VCV) nonsense syllables, exclusively utilizing the flanking vowel /u/. Results: Descriptive analysis revealed a strong time-order effect influencing loudness judgments for 7 of the 13 VCV test stimuli. Statistical testing showed no significant didference (P = 0.94) between the relative amplitudes corresponding to the point of equal loudness for plosive-containing versus non-plosive-containing VCV stimuli. However, 6 individual VCV stimuli, containing consonants from 4 separate manners of articulation, produced significant loudness matching data (P < 0.01). Conclusions: The results falsify the hypothesis that plosives, analyzed collectively as a class, possess a heavier perceptual loudness weighting than non-plosive consonants. While 6 individual VCV stimuli indicated potential individual consonantal loudness weightings, these findings must be interpreted cautiously due to the restriction to a single vowel context and the presence of procedural time-order biases.

neuroscience↗

bioRxiv2026

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

ObjectiveCurrent 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. DesignContinuous, 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 Spearmans rank correlation matrix was utilized to assess physiological decoupling, and Linear Mixed-Effects (LME) models isolated single-trial effort dynamics. ResultsThe 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. ConclusionsListening 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.

neuroscience↗

bioRxiv2026

Power-Law Adaptation Stabilizes Primary Sensory Encoding of Natural Variance

Natural physical environments constantly fluctuate across multiple timescales, often following a scale-free (1/f ) pattern where = 0.5 governs the fractional adaptation dynamics (Drew and Abbott 2006, Lundstrom et al. 2008). Here, we demonstrate how a multi-timescale sensory model successfully tracks these long-term trends to maintain stable encoding. Using an event-based Generalized Leaky Integrate-and-Fire (GLIF) paradigm, we found that a fast-adapting, single-exponential model with a short time constant{tau} [≤] 31.6 ms quickly crashes into complete refractory saturation when faced with large, low-frequency environmental shifts. In contrast, introducing a deep fractional memory tail of 1000.0 ms acts as an automated, high-pass balancing mechanism that continuously tracks and subtracts slow environmental variance. This predictive balancing prevents sensory collapse, anchors the mean firing rate to a steady homeostatic baseline, and maximizes coding efficiency for rapid, localized signals. Our results show that while a simple single-pole exponential model fails to retain history, a parallel bank of physiological relaxation processes converging on a target fractional profile t-0.5 provides the necessary historical memory to safely navigate natural stimulus fluctuations. Comfortingly, even a simplified three-pole approximation captures the bulk of this homeostatic benefit, making efficient fractional adaptation biologically viable at the sensory periphery without requiring infinite historical storage.

neuroscience↗