Investigation of Frequency-Specific Loudness Discomfort Levels in Listeners With Migraine: A Case-Control Study.

OBJECTIVES: Hypersensitivity to auditory stimuli is a commonly reported symptom in listeners with migraine, yet it remains relatively unexplored in research. This study aims to investigate loudness discomfort levels in listeners with migraine, while identifying the frequencies most affected by the phenomenon. DESIGN: To achieve this, the study compared just audible level and loudness discomfort level ranges between participants with and without migraine from the United Kingdom, Greece as well as the participant recruitment platform Prolific, across 13 frequencies from 100 to 12,000 Hz, through an online listening test. RESULTS: Fifty-five participants with migraine and 49 participants without migraine from both countries and Prolific were included in the analysis, where threshold ranges between just audible and mildly uncomfortable levels were compared in 13 frequencies. Migraineur group participants presented significantly smaller ranges between just audible and mildly uncomfortable level, due to lower thresholds of mild discomfort in 12 of the 13 frequencies when compared with the nonmigraineur group participants. Participants taking the test during their migraine attack or aura presented a tendency for smaller ranges. In addition, participants with self-reported higher severity migraine exhibited bigger ranges compared with participants with low severity migraine within the migraineur group. No relationship between ranges and medication or migraine attack frequency within the migraineur group was observed. CONCLUSIONS: Results from the study demonstrate a tendency for the migraineur group to present lower thresholds of mild discomfort compared with the nonmigraineur group, aligning with previous studies while extending the phenomenon to more frequencies than those previously examined. Though the present study presented no relationship between ranges and medication or attack frequency, further research is required to investigate a potential link between these factors.

Selective adaptation to "oddball" sounds by the human auditory system.

Adaptation to both common and rare sounds has been independently reported in neurophysiological studies using probabilistic stimulus paradigms in small mammals. However, the apparent sensitivity of the mammalian auditory system to the statistics of incoming sound has not yet been generalized to task-related human auditory perception. Here, we show that human listeners selectively adapt to novel sounds within scenes unfolding over minutes. Listeners' performance in an auditory discrimination task remains steady for the most common elements within the scene but, after the first minute, performance improves for distinct and rare (oddball) sound elements, at the expense of rare sounds that are relatively less distinct. Our data provide the first evidence of enhanced coding of oddball sounds in a human auditory discrimination task and suggest the existence of an adaptive mechanism that tracks the long-term statistics of sounds and deploys coding resources accordingly.

Verification of chaotic behavior in an experimental loudspeaker.

The dynamics of an experimental electrodynamic loudspeaker is studied by using the tools of chaos theory and time series analysis. Delay time, embedding dimension, fractal dimension, and other empirical quantities are determined from experimental data. Particular attention is paid to issues of stationarity in a system in order to identify sources of uncertainty. Lyapunov exponents and fractal dimension are measured using several independent techniques. Results are compared in order to establish independent confirmation of low dimensional dynamics and a positive dominant Lyapunov exponent. We thus show that the loudspeaker may function as a chaotic system suitable for low dimensional modeling and the application of chaos control techniques.

The dynamic range paradox: a central auditory model of intensity change detection.

In this paper we use empirical loudness modeling to explore a perceptual sub-category of the dynamic range problem of auditory neuroscience. Humans are able to reliably report perceived intensity (loudness), and discriminate fine intensity differences, over a very large dynamic range. It is usually assumed that loudness and intensity change detection operate upon the same neural signal, and that intensity change detection may be predicted from loudness data and vice versa. However, while loudness grows as intensity is increased, improvement in intensity discrimination performance does not follow the same trend and so dynamic range estimations of the underlying neural signal from loudness data contradict estimations based on intensity just-noticeable difference (JND) data. In order to account for this apparent paradox we draw on recent advances in auditory neuroscience. We test the hypothesis that a central model, featuring central adaptation to the mean loudness level and operating on the detection of maximum central-loudness rate of change, can account for the paradoxical data. We use numerical optimization to find adaptation parameters that fit data for continuous-pedestal intensity change detection over a wide dynamic range. The optimized model is tested on a selection of equivalent pseudo-continuous intensity change detection data. We also report a supplementary experiment which confirms the modeling assumption that the detection process may be modeled as rate-of-change. Data are obtained from a listening test (N = 10) using linearly ramped increment-decrement envelopes applied to pseudo-continuous noise with an overall level of 33 dB SPL. Increments with half-ramp durations between 5 and 50,000 ms are used. The intensity JND is shown to increase towards long duration ramps (p<10(-6)). From the modeling, the following central adaptation parameters are derived; central dynamic range of 0.215 sones, 95% central normalization, and a central loudness JND constant of 5.5×10(-5) sones per ms. Through our findings, we argue that loudness reflects peripheral neural coding, and the intensity JND reflects central neural coding.

Tuning of human modulation filters is carrier-frequency dependent.

Recent studies employing speech stimuli to investigate 'cocktail-party' listening have focused on entrainment of cortical activity to modulations at syllabic (5 Hz) and phonemic (20 Hz) rates. The data suggest that cortical modulation filters (CMFs) are dependent on the sound-frequency channel in which modulations are conveyed, potentially underpinning a strategy for separating speech from background noise. Here, we characterize modulation filters in human listeners using a novel behavioral method. Within an 'inverted' adaptive forced-choice increment detection task, listening level was varied whilst contrast was held constant for ramped increments with effective modulation rates between 0.5 and 33 Hz. Our data suggest that modulation filters are tonotopically organized (i.e., vary along the primary, frequency-organized, dimension). This suggests that the human auditory system is optimized to track rapid (phonemic) modulations at high sound-frequencies and slow (prosodic/syllabic) modulations at low frequencies.