Sho Otsuka

Background/Objectives: This study proposes Diffusion Inverse Filtering (DIF), a spatially informed transformation designed to counteract spatial smoothing in functional-connectivity representations (i.e., functional networks) and thereby enhance their discriminative power for pattern recognition. Spatial smoothing in electroencephalography (EEG) signals and derived features, such as functional connectivity, is largely attributed to volume conduction. Functional connectivity has been increasingly used in brain–computer interface (BCI) studies; however, this spatial smoothing can introduce spurious connections and distort functional-connectivity patterns. Methods: DIF approximates spatial smoothing in functional connectivity, which is potentially associated with volume conduction, as a diffusion-like process and applies a regularized inverse operation to transform the observed functional networks into networks with enhanced discriminative representations. The effectiveness of DIF in enhancing the discriminative power of functional-connectivity representations in pattern recognition was evaluated using emotion recognition as the paradigm task, which is a critical component of BCI systems. Experimental results show that DIF generally improves emotion-recognition performance relative to the originally observed functional networks under electrode-sparsification conditions, with the most consistent improvements observed for Pearson correlation coefficient (PCC) estimation. Both signal-level processing, which operates on EEG signals before functional-connectivity estimation, and function-al-connectivity-level transformations, including graph signal processing (GSP)-based filtering applied after functional-connectivity estimation, were included as comparators. Under this framework, DIF is also considered a functional-connectivity-level transformation, but does not rely on a GSP framework. Results: The performance of DIF demonstrates the potential of functional-connectivity-level transformation as a complement or alternative to signal-level processing for enhancing connectivity-based pattern recognition. Overall, DIF improves classification performance and offers strong compatibility with modern functional-connectivity-based BCI pipelines.

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.

Rhythms are the most natural cue for temporal anticipation because many sounds in our living environment have rhythmic structures. Humans have cortical mechanisms that can predict the arrival of the next sound based on rhythm and periodicity. Herein, we showed that temporal anticipation, based on the regularity of sound sequences, modulates peripheral auditory responses via efferent innervation. The medial olivocochlear reflex (MOCR), a sound-activated efferent feedback mechanism that controls outer hair cell motility, was inferred noninvasively by measuring the suppression of otoacoustic emissions (OAE). First, OAE suppression was compared between conditions in which sound sequences preceding the MOCR elicitor were presented at regular (predictable condition) or irregular (unpredictable condition) intervals. We found that OAE suppression in the predictable condition was stronger than that in the unpredictable condition. This implies that the MOCR is strengthened by the regularity of preceding sound sequences. In addition, to examine how many regularly presented preceding sounds are required to enhance the MOCR, we compared OAE suppression within stimulus sequences with 0–3 preceding tones. The OAE suppression was strengthened only when there were at least three regular preceding tones. This suggests that the MOCR was not automatically enhanced by a single stimulus presented immediately before the MOCR elicitor, but rather that it was enhanced by the regularity of the preceding sound sequences.

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.

Disaster alerts are usually accompanied by auditory signals at the beginning. It is to be desired that the auditory signal itself produces the sense of warning. Effects of (1) degree of consonance and (2) temporal pattern of the auditory signal on the auditory impression of warning were investigated using paired-comparison tests. In the both tests, sequences of 3 triads were used as stimuli. First, 7 types of stimuli were generated by varying the degree of consonance of the triad (frequency ratio of sinusoids was varied systematically from 2:3:4, 4:5:6, 6:7:8, 8:9:10, 10:11:12, 12:13:14 through to 14:15:16). Each subject showed changes of the auditory impression of warning depending on the degree of consonance, however, variation among subjects were observed. Second, 21 types of stimuli were generated in total by changing several temporal parameters (duration of the triad, interval between the triads, duty rate of the sequence). The results indicated that the auditory impression of warning increased as the duration of the triad increased the interval between the triads decreased.

Bone-conduction microphones (BCMs) can detect speakers' voices with high signal-to-noise ratio even under extremely noisy environments like a machine factory or an engine room of a watercraft. BCMs are ordinarily attached to the front of the neck (larynx), therefore, it is sometimes accompanied by discomfort and esthetic problems. In order to solve such problems, we have been developing a novel BCM system built in a helmet, however, characteristics of bone-conducted speech detected on the scalp need to be clarified. In this study, mono-syllable articulations of bone-conducted speech detected at several locations on the head and neck were measured. Also, the speech transmission index (STI), objective measure of signal transmission quality, was calculated. The results indicated that the forehead and the vertex showed better articulation and STI than the mastoid process of the temporal bone, the mandibular condyle, and the occiput. In terms of the gender difference, the forehead and the vertex showed higher scores for the male voice, whereas the cheek showed the highest for the female voice. Additionally, the larynx showed lower scores than others. These results indicated that the attenuation of high-frequency components are smaller at the forehead and the vertex.

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

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.