Bone-conducted ultrasound (BCU) is perceived even by the profoundly hearing impaired and a novel hearing aid has been developed. In the BCU hearing aid, the ultrasonic carrier is amplitude-modulated by speech signals and presented to the mastoid process of the temporal bone by a vibrator. However, BCU presented to parts of the body distant from the head can be perceived. In this study, vibration at the external auditory meatus was measured when amplitude-modulated BCU was presented to distal parts of the body. The results showed spectrum peaks corresponding to the carrier frequency (30 kHz) and the modulation frequency. The peak level of the carrier frequency tended to decrease depending on the distance between the external auditory meatus and the stimulation part basically. On the other hand, the peak level of the modulation frequency did not change with the distance between the external auditory meatus and the stimulation part, whereas the effect of modulation frequency was significant.

Expectations concerning the timing of a stimulus enhance attention at the time at which the event occurs, which confers significant sensory and behavioral benefits. Herein, we show that temporal expectations modulate even the sensory transduction in the auditory periphery via the descending pathway. We measured the medial olivocochlear reflex (MOCR), a sound-activated efferent feedback that controls outer hair cell motility and optimizes the dynamic range of the sensory system. MOCR was noninvasively assessed using otoacoustic emissions. We found that the MOCR was enhanced by a visual cue presented at a fixed interval before a sound but was unaffected if the interval was changing between trials. The MOCR was also observed to be stronger when the learned timing expectation matched with the timing of the sound but remained unvaried when these two factors did not match. This implies that the MOCR can be voluntarily controlled in a stimulus- and goal-directed manner. Moreover, we found that the MOCR was enhanced by the expectation of a strong but not a weak, sound intensity. This asymmetrical enhancement could facilitate antimasking and noise protective effects without disrupting the detection of faint signals. Therefore, the descending pathway conveys temporal and intensity expectations to modulate auditory processing.

Japan's largest platform for academic e-journals: J-STAGE is a full text database for reviewed academic papers published by Japanese societies

Japan's largest platform for academic e-journals: J-STAGE is a full text database for reviewed academic papers published by Japanese societies

When an amplitude modulated signal with a constant-frequency carrier is fed into a generic nonlinear amplifier, the phase of the carrier of the output signal is also modulated. This phenomenon is referred to as amplitude-modulation-to-phase-modulation (AM-to-PM) conversion and regarded as an unwanted signal distortion in the field of electro-communication engineering. Herein, we offer evidence that AM-to-PM conversion also occurs in the human cochlea and that listeners can use the PM information effectively to process the AM of sounds. We recorded otoacoustic emissions (OAEs) evoked by AM signals. The results showed that the OAE phase was modulated at the same rate as the stimulus modulation. The magnitude of the AM-induced PM of the OAE peaked generally around the stimulus level corresponding to the compression point of individual cochlear input-output functions, as estimated using a psychoacoustic method. A computational cochlear model incorporating a nonlinear active process replicates the abovementioned key features of the AM-induced PM observed in OAEs. These results indicate that AM-induced PM occurring at the cochlear partition can be estimated by measuring OAEs. Psychophysical experiments further revealed that, for individuals with higher sensitivity to PM, the PM magnitude is correlated with AM-detection performance. This result implies that the AM-induced PM information cannot be a dominant cue for AM detection, but listeners with higher sensitivity may partly rely on the AM-induced PM cue.

Background/Objectives: Advancements in neuroscience and machine learning have increasingly enabled brain pattern recognition based on bio-signal measurements, such as electroencephalography (EEG). These developments support next-generation technologies, including brain–computer interfaces (BCIs) and AI-assisted systems. However, volume conduction (VC) effects remain a major source of contamination in EEG recordings, affecting both univariate analyses and functional connectivity estimation. Methods: In this work, we propose a VC mitigation method that explicitly models and suppresses VC components in the observed functional networks. Specifically, the observed functional network is decomposed into a matrix capturing only VC-related components (i.e., components attributed to volume conduction) and a residual matrix, where the residual is regarded as a proxy for a VC-mitigated functional network that better reflects the underlying functional interactions. The VC component matrix is modeled using a decay function parameterized by the inter-electrode distance matrix, capturing the dominant spatial bias induced by VC. To estimate these parameters, we introduce supervised channel importance, quantified as the mutual information between experimental labels and channel signals, as a proxy for task-relevant neural activity. The parameters are optimized such that the unsupervised node importance derived from the VC-mitigated functional network, defined as the average node strength, aligns with the supervised channel importance. Results: Evaluation results using a deep-learning framework demonstrate that, compared with the observed functional network, the VC-mitigated functional network improves classification performance in brain pattern recognition tasks.