Electrophysiological correlation of auditory selective spatial attention in the "cocktail party" situation.

The auditory system can selectively attend to the target source in complex environments, the phenomenon known as the "cocktail party" effect. However, the spatiotemporal dynamics of electrophysiological activity associated with auditory selective spatial attention (ASSA) remain largely unexplored. In this study, single-source and multiple-source paradigms were designed to simulate different auditory environments, and microstate analysis was introduced to reveal the electrophysiological correlates of ASSA. Furthermore, cortical source analysis was employed to reveal the neural activity regions of these microstates. The results showed that five microstates could explain the spatiotemporal dynamics of ASSA, ranging from MS1 to MS5. Notably, MS2 and MS3 showed significantly lower partial properties in multiple-source situations than in single-source situations, whereas MS4 had shorter durations and MS5 longer durations in multiple-source situations than in single-source situations. MS1 had insignificant differences between the two situations. Cortical source analysis showed that the activation regions of these microstates initially transferred from the right temporal cortex to the temporal-parietal cortex, and subsequently to the dorsofrontal cortex. Moreover, the neural activity of the single-source situations was greater than that of the multiple-source situations in MS2 and MS3, correlating with the N1 and P2 components, with the greatest differences observed in the superior temporal gyrus and inferior parietal lobule. These findings suggest that these specific microstates and their associated activation regions may serve as promising substrates for decoding ASSA in complex environments.

EEG-based assessment of temporal fine structure and envelope effect in mandarin syllable and tone perception.

In recent years, speech perception research has benefited from low-frequency rhythm entrainment tracking of the speech envelope. However, speech perception is still controversial regarding the role of speech envelope and temporal fine structure, especially in Mandarin. This study aimed to discuss the dependence of Mandarin syllables and tones perception on the speech envelope and the temporal fine structure. We recorded the electroencephalogram (EEG) of the subjects under three acoustic conditions using the sound chimerism analysis, including (i) the original speech, (ii) the speech envelope and the sinusoidal modulation, and (iii) the fine structure of time and the modulation of the non-speech (white noise) sound envelope. We found that syllable perception mainly depended on the speech envelope, while tone perception depended on the temporal fine structure. The delta bands were prominent, and the parietal and prefrontal lobes were the main activated brain areas, regardless of whether syllable or tone perception was involved. Finally, we decoded the spatiotemporal features of Mandarin perception from the microstate sequence. The spatiotemporal feature sequence of the EEG caused by speech material was found to be specific, suggesting a new perspective for the subsequent auditory brain-computer interface. These results provided a new scheme for the coding strategy of new hearing aids for native Mandarin speakers.

Decoding selective auditory attention with EEG using a transformer model.

The human auditory system extracts valid information in noisy environments while ignoring other distractions, relying primarily on auditory attention. Studies have shown that the cerebral cortex responds differently to the sound source locations and that auditory attention is time-varying. In this work, we proposed a data-driven encoder-decoder architecture model for auditory attention detection (AAD), denoted as AAD-transformer. The model contains temporal self-attention and channel attention modules and could reconstruct the speech envelope by dynamically assigning weights according to the temporal self-attention and channel attention mechanisms of electroencephalogram (EEG). In addition, the model is conducted based on data-driven without additional preprocessing steps. The proposed model was validated using a binaural listening dataset, in which the speech stimulus was Mandarin, and compared with other models. The results showed that the decoding accuracy of the AAD-transformer in the 0.15-second decoding time window was 76.35%, which was much higher than the accuracy of the linear model using temporal response function in the 3-second decoding time window (increased by 16.27%). This work provides a novel auditory attention detection method, and the data-driven characteristic makes it convenient for neural-steered hearing devices, especially those who speak tonal languages.

Effect of exogenous methanol on glycolate oxidase and photorespiratory intermediates in cotton.

Application of methanol (MeOH) inhibits photorespiration and enhances growth and yield in C3 plants. However, the underlying cellular and molecular mechanisms are not clear. In this study, we investigated the effects of foliar application of MeOH (30%, v/v) on glycolate oxidase (GO) activity and photorespiratory intermediates in cotton leaves in a field experiment. MeOH treatment significantly inhibited GO activity (by 30% compared with the controls). We also found that endogenous glyoxylate, a photorespiratory intermediate, increased and glycine decreased significantly in MeOH-treated plants. Serine increased significantly in MeOH-treated plants. These results thus demonstrated that exogenous MeOH can modulate GO activity and the production of photorespiratory intermediates, and sheds new lights on our current understanding of how exogenous MeOH inhibits photorespiration and enhances the growth and yield of C3 plants such as cotton.

The scalp time-varying network of auditory spatial attention in "cocktail-party" situations.

Sound source localization in "cocktail-party" situations is a remarkable ability of the human auditory system. However, the neural mechanisms underlying auditory spatial attention are still largely unknown. In this study, the "cocktail-party" situations are simulated through multiple sound sources and presented through head-related transfer functions and headphones. Furthermore, the scalp time-varying network of auditory spatial attention is constructed using the high-temporal resolution electroencephalogram, and its network properties are measured quantitatively using graph theory analysis. The results show that the time-varying network of auditory spatial attention in "cocktail-party" situations is more complex and partially different than in simple acoustic situations, especially in the early- and middle-latency periods. The network coupling strength increases continuously over time, and the network hub shifts from the posterior temporal lobe to the parietal lobe and then to the frontal lobe region. In addition, the right hemisphere has a stronger network strength for processing auditory spatial information in "cocktail-party" situations, i.e., the right hemisphere has higher clustering levels, higher transmission efficiency, and more node degrees during the early- and middle-latency periods, while this phenomenon disappears and appears symmetrically during the late-latency period. These findings reveal different network patterns and properties of auditory spatial attention in "cocktail-party" situations during different periods and demonstrate the dominance of the right hemisphere in the dynamic processing of auditory spatial information.

Cochlear Implant Artifacts Removal in EEG-Based Objective Auditory Rehabilitation Assessment.

Cochlear implant (CI) is a neural prosthesis that can restore hearing for patients with severe to profound hearing loss. Observed variability in auditory rehabilitation outcomes following cochlear implantation may be due to cerebral reorganization. Electroencephalography (EEG), favored for its CI compatibility and non-invasiveness, has become a staple in clinical objective assessments of cerebral plasticity post-implantation. However, the electrical activity of CI distorts neural responses, and EEG susceptibility to these artifacts presents significant challenges in obtaining reliable neural responses. Despite the use of various artifact removal techniques in previous studies, the automatic identification and reduction of CI artifacts while minimizing information loss or damage remains a pressing issue in objectively assessing advanced auditory functions in CI recipients. To address this problem, we propose an approach that combines machine learning algorithms-specifically, Support Vector Machines (SVM)-along with Independent Component Analysis (ICA) and Ensemble Empirical Mode Decomposition (EEMD) to automatically detect and minimize electrical artifacts in EEG data. The innovation of this research is the automatic detection of CI artifacts using the temporal properties of EEG signals. By applying EEMD and ICA, we can process and remove the identified CI artifacts from the affected EEG channels, yielding a refined signal. Comparative analysis in the temporal, frequency, and spatial domains suggests that the corrected EEG recordings of CI recipients closely align with those of peers with normal hearing, signifying the restoration of reliable neural responses across the entire scalp while eliminating CI artifacts.

Musical experience enhances time discrimination: Evidence from cortical responses.

Time discrimination, a critical aspect of auditory perception, is influenced by numerous factors. Previous research has suggested that musical experience can restructure the brain, thereby enhancing time discrimination. However, this phenomenon remains underexplored. In this study, we seek to elucidate the enhancing effect of musical experience on time discrimination, utilizing both behavioral and electroencephalogram methodologies. Additionally, we aim to explore, through brain connectivity analysis, the role of increased connectivity in brain regions associated with auditory perception as a potential contributory factor to time discrimination induced by musical experience. The results show that the music-experienced group demonstrated higher behavioral accuracy, shorter reaction time, and shorter P3 and mismatch response latencies as compared to the control group. Furthermore, the music-experienced group had higher connectivity in the left temporal lobe. In summary, our research underscores the positive impact of musical experience on time discrimination and suggests that enhanced connectivity in brain regions linked to auditory perception may be responsible for this enhancement.

Electroencephalogram-based objective assessment of cognitive function level associated with age-related hearing loss.

Age-Related Hearing Loss (ARHL) is a common problem in aging. Numerous longitudinal cohort studies have revealed that ARHL is closely related to cognitive function, leading to a significant risk of cognitive decline and dementia. This risk gradually increases with the severity of hearing loss. We designed dual auditory Oddball and cognitive task paradigms for the ARHL subjects, then obtained the Montreal Cognitive Assessment (MoCA) scale evaluation results for all the subjects. Multi-dimensional EEG characteristics helped explore potential biomarkers to evaluate the cognitive level of the ARHL group, having a significantly lower P300 peak amplitude coupled with a prolonged latency. Moreover, visual memory, auditory memory, and logical calculation were investigated during the cognitive task paradigm. In the ARHL groups, the alpha-to-beta rhythm energy ratio in the visual and auditory memory retention period and the wavelet packet entropy value within the logical calculation period were significantly reduced. Correlation analysis between the above specificity indicators and the subjective scale results of the ARHL group revealed that the auditory P300 component characteristics could assess attention resources and information processing speed. The alpha and beta rhythm energy ratio and wavelet packet entropy can become potential indicators to determine working memory and logical cognitive computation-related cognitive ability.

OCT imaging of endolymphatic hydrops in mice: association with hearing loss.

BACKGROUND: The etiology of Ménière's disease (MD) is still not completely clear, but it is believed to be associated with endolymphatic hydrops (EH), which is characterized by auditory functional disorders. Vasopressin injection in C57BL/6J mice can induce EH and serve as a model for MD. Optical Coherence Tomography (OCT) has shown its advantages as a non-invasive imaging method for observing EH.AimInvestigating the relationship between hearing loss and EH to assist clinical hearing assessments and indicate the severity of hydrops. METHODS: C57BL/6J mice received 50 µg/100g/day vasopressin injections to induce EH. Auditory function was assessed using auditory brainstem response (ABR) and distortion product otoacoustic emissions (DPOAE). OCT was used to visualize the cochlea. RESULT: OCT observed accumulation of fluid within the scala media in the cochlear apex. ABR showed significant hearing loss after 4 weeks. DPOAE revealed low-frequency hearing loss at 2 weeks and widespread damage across frequencies at 4 weeks. CONCLUSION: The development of hearing loss in mouse models of MD is consistent with EH manifestations.SignificanceThis study demonstrates the possibility of indirectly evaluating the extent of EH through auditory assessment and emphasizes the significant value of OCT for imaging cochlear structures.

Liquid Metal Flexible EMG Gel Electrodes for Gesture Recognition.

Gesture recognition has been playing an increasingly important role in the field of intelligent control and human-computer interaction. Gesture recognition technology based on electromyography (EMG) with high accuracy has been widely applied. However, conventional rigid EMG electrodes do not fit the mechanical properties of human skin. Therefore, rigid EMG electrodes are easily influenced by body movements, and uncomfortable to wear and use for a long time. To solve these problems, a stretchable EMG electrode based on liquid metal nanoparticles was developed in this research. It is conformal with human skin because of its similar mechanical properties to skin. Liquid metal nanoparticles mixed in polymer can be connected to each other to form conductive circuits when pressed by mechanical force. Therefore, this preparation method of liquid metal flexible gel electrodes is low-cost and can be fabricated largely. Moreover, the liquid metal flexible gel electrodes have great stretch ability. Their resistance increases slightly at maximum strain state. Based on these advantages, the flexible gel electrodes are applied to arm to collect EMG signals generated by human hand movements. In addition, the signals are analyzed by artificial intelligence algorithm to realize accurate gesture recognition.

Assessing vestibular function using electroencephalogram rhythms evoked during the caloric test.

Introduction: The vestibular system is responsible for motion perception and balance preservation in the body. The vestibular function examination is useful for determining the cause of associated symptoms, diagnosis, and therapy of the patients. The associated cerebral cortex processes and integrates information and is the ultimate perceptual site for vestibular-related symptoms. In recent clinical examinations, less consideration has been given to the cortex associated with the vestibular system. As a result, it is crucial to increase focus on the expression of the cortical level while evaluating vestibular function. From the viewpoint of neuroelectrophysiology, electroencephalograms (EEG) can enhance the assessments of vestibular function at the cortex level. Methods: This study recorded nystagmus and EEG data throughout the caloric test. Four phases were considered according to the vestibular activation status: before activation, activation, fixation suppression, and recovery. In different phases, the distribution and changes of the relative power of the EEG rhythms (delta, theta, alpha, and beta) were analyzed, and the correlation between EEG characteristics and nystagmus was also investigated. Results: The results showed that, when the vestibule was activated, the alpha power of the occipital region increased, and the beta power of the central and top regions and the occipital region on the left decreased. The changes in the alpha and beta rhythms significantly correlate with nystagmus values in left warm stimulation. Discussion: Our findings offer a fresh perspective on cortical electrophysiology for the assessment of vestibular function by demonstrating that the relative power change in EEG rhythms can be used to assess vestibular function.

Spatial and temporal distribution of rural settlements and influencing mechanisms in Inner Mongolia, China.

Revealing the patterns and influencing mechanisms of spatial and temporal distribution of rural settlements is crucial for rural revitalization and sustainable development. However, our limited understanding of the rural settlements in China's ethnic minority border areas has hindered the process of their agricultural and rural modernization. Based on data on rural settlements in Inner Mongolia, China in four periods between 1990 and 2020, this study reveals its spatial and temporal distribution characteristics and describes the dynamic transformation process of settlement. Using a geographical detector approach, 17 factors are explored to identify the influencing mechanisms of each factor on the distribution of rural settlements in different regions. The results show obvious regional differences in the spatial distribution of rural settlements in Inner Mongolia, with the largest kernel density values in the west (Hetao irrigation area) and higher kernel densities in the central (Hohhot) and the east (Chifeng and Tongliao). While rural population decreases, rural settlements expand into cultivated land, grassland, and unused land resources. Its spatial distribution is significantly influenced by the factors of distance to cultivated land, distance to towns, and population density. The east of the study area is mainly controlled by temperature, while vegetation type and vegetation coverage have a greater impact in the west. The interactions between two influencing factors possess bilinear or nonlinear enhancement relationships. This study enriches the understanding of the rural settlements in ethnic minority border areas, which provide reference for the improvement of rural human settlement environment in Inner Mongolia.

Auditory attention decoding from EEG-based Mandarin speech envelope reconstruction.

In the cocktail party circumstance, the human auditory system extracts the information from a specific speaker of interest and ignores others. Many studies have focused on auditory attention decoding (AAD), but the stimulation materials were mainly non-tonal languages. We used a tonal language (Mandarin) as the speech stimulus and constructed a Long Short-Term Memory (LSTM) architecture for speech envelope reconstruction based on electroencephalogram (EEG) data. The correlation coefficient between the reconstructed and candidate envelopes was calculated to determine the subject's auditory attention. The proposed LSTM architecture outperformed the linear models. The average decoding accuracy in cross-subject and inter-subject cases varies from 63.02 to 74.29%, with the highest accuracy rate of 89.1% in a decision window of 0.15 s. In addition, the beta-band rhythm was found to play an essential role in identifying the attention and the non-attention state. These results provide a new AAD architecture to help develop neuro-steered hearing devices, especially for tonal languages.

Design and optimization of auditory prostheses using the finite element method: a narrative review.

Background and Objective: An auditory prosthesis refers to a device designed to restore hearing. Some parameters of the auditory prosthesis, such as mass, implanted position, and degree, need to be repeatedly designed and optimized based on the realistic geometry of the ear. Numerous auditory prostheses designs were based on animal or specimen experiments involving many complex instruments, and the experimental specimens had low repeatability. The finite element method (FEM) can overcome these disadvantages and be carried out on the computer with substantial flexibility in modifying the prosthetic parameters to optimize them. This narrative review aims to analyze the recent advances in the design and optimization of auditory prostheses using the FEM and provides suggestions for future development. Methods: The literature on the design of auditory prostheses using the FEM has been extensively studied using the PubMed and Web of Science databases, including different ear models and relevant parameters of different auditory prostheses that need to be designed and optimized. Key Content and Findings: The process of designing and optimizing a prosthesis using the FEM includes building an ear model and a prosthesis model to simulate the implantation process. The related parameters of the prosthesis can be designed and modified conveniently. The post-implantation response could be used as an indicator to evaluate the prosthesis's performance. Conclusions: The review concluded that the FEM had been widely studied in designing and optimizing middle ear implants and cochlear implants and obtained good results. FEM can be utilized to explore more effective directions for auditory prosthesis design and optimization in the future.

Microstructural interactions contribute to the hotspot in the living cochlea.

The mechanism of the active cochlea relies on a complex interaction between microstructures in the organ of Corti. A significant longitudinal vibration "hotspot" was recently observed in the high-frequency region of the living gerbil cochlea between the Deiters cells and the outer hair cells. A similar phenomenon was also found in guinea pigs with a relatively smaller magnitude. The cause is unknown, but one hypothesis is that this phenomenon is due to the structural constraints between different microstructures. It is not easy to explain the mechanism of hotspots directly from experimental observations. It may also be difficult to image or test if the hotspot will occur in the low-frequency region in the cochlea. We built two three-dimensional finite element models corresponding to the high- and low-frequency regions in the guinea pig cochlea. Responses of the organ of Corti to passive acoustic and outer hair cell electrical excitation were calculated. The two excitations were then superimposed to predict the active response of the organ of Corti. The hotspot phenomenon in the experiment was reproduced and analyzed in-depth about influencing factors. Our results indicate that hotspots appear in the low-frequency region of the cochlea as well. We hypothesize that the hotspot is a locally originated phenomenon in the cochlea, and the traveling wave further enhances the response to low-frequency excitation. The movement of outer hair cells inclined in the longitudinal direction is the leading cause of the hotspot.

A Show of Ewald's Law: I Horizontal Semicircular Canal Benign Paroxysmal Positional Vertigo.

Objective: To evaluate horizontal semicircular canal (HSC) effects according to Ewald's law and nystagmus characteristics of horizontal semicircular canal benign paroxysmal positional vertigo (HSC-BPPV) in the supine roll test. Methods: Patients with HSC-BPPV (n = 72) and healthy subjects (n = 38) were enrolled. Latency, duration, and intensity of nystagmus elicited by supine roll test were recorded using video nystagmography. Results: In patients with HSC-BPPV, horizontal nystagmus could be elicited by right/left head position (positional nystagmus) and during head-turning (head-turning nystagmus), and nystagmus direction was the same as that of head turning. Mean intensity values of head-turning nystagmus in HSC-BPPV patients were (44.70 ± 18.24)°/s and (44.65 ± 19.27)°/s on the affected and unaffected sides, respectively, which was not a significant difference (p = 0.980), while those for positional nystagmus were (40.81 ± 25.56)°/s and (17.69 ± 9.31)°/s (ratio, 2.59 ± 1.98:1), respectively, representing a significant difference (p < 0.0001). There was no positional nystagmus in 49 HSC-BPPV patients after repositioning treatment, nor in the 38 healthy subjects. No significant difference in head-turning nystagmus was detected in HSC-BPPV patients with or without repositioning. Conclusions: The direction and intensity of nystagmus elicited by supine roll test in patients with HSC-BPPV, was broadly consistent with the physiological nystagmus associated with a same HSC with single factor stimulus. Our findings suggest that HSC-BPPV can be a show of Ewald's law in human body.

Denoising Raman spectra by Wiener estimation with a numerical calibration dataset.

Most denoising methods that are currently used in the processing of Raman spectra require significant user interaction in order to optimize their performance across a range of signal-to-noise ratios. In this study, we proposed a method based on the principle of spectral integration followed by Wiener estimation using a numerical calibration dataset, which eliminates the need of experimental measurements for calibration as in the previous Wiener estimation based denoising method. The new method was tested on three types of samples, including a phantom sample, human fingernail and leukemia cells. Compared to two common denoising methods, i.e. moving-average filtering and Savitzky-Golay filtering, the performance of the proposed method is significantly less sensitive to the choices of parameters. Moreover, this method provides comparable or even better denoising performance in the cases with low signal-to-noise ratios.

Surface Enhanced Raman Spectroscopy Based Biosensor with a Microneedle Array for Minimally Invasive In Vivo Glucose Measurements.

To monitor blood glucose levels reliably, diabetic patients usually have to undergo frequent fingerstick tests to draw out fresh blood, which is painful and inconvenient with the potential risk of cross contamination especially when the lancet is reused or not properly sterilized. This work reports a novel surface-enhanced Raman spectroscopy (SERS) sensor for the in situ intradermal detection of glucose based on a low-cost poly(methyl methacrylate) microneedle (PMMA MN) array. After incorporating 1-decanethiol (1-DT) onto the silver-coated array surface, the sensor was calibrated in the range of 0-20 mM in skin phantoms then tested for the in vivo quantification of glucose in a mouse model of streptozocin (STZ)-induced type I diabetes. The results showed that the functional poly(methyl methacrylate) microneedle (F-PMMA MN) array was able to directly measure glucose in the interstitial fluid (ISF) in a few minutes and retain its structural integrity without swelling. The Clarke error grid analysis of measured data indicated that 93% of the data points lie in zones A and B. Moreover, the MN array exhibited minimal invasiveness to the skin as the skin recovered well without any noticeable adverse reaction in 10 min after measurements. With further improvement and proper validation, this polymeric MN array-based SERS biosensor has the potential to be used in painless glucose monitoring of diabetic patients in the future.

Decoding Subjective Intensity of Nociceptive Pain from Pre-stimulus and Post-stimulus Brain Activities.

Pain is a highly subjective experience. Self-report is the gold standard for pain assessment in clinical practice, but it may not be available or reliable in some populations. Neuroimaging data, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have the potential to be used to provide physiology-based and quantitative nociceptive pain assessment tools that complements self-report. However, existing neuroimaging-based nociceptive pain assessments only rely on the information in pain-evoked brain activities, but neglect the fact that the perceived intensity of pain is also encoded by ongoing brain activities prior to painful stimulation. Here, we proposed to use machine learning algorithms to decode pain intensity from both pre-stimulus ongoing and post-stimulus evoked brain activities. Neural features that were correlated with intensity of laser-evoked nociceptive pain were extracted from high-dimensional pre- and post-stimulus EEG and fMRI activities using partial least-squares regression (PLSR). Further, we used support vector machine (SVM) to predict the intensity of pain from pain-related time-frequency EEG patterns and BOLD-fMRI patterns. Results showed that combining predictive information in pre- and post-stimulus brain activities can achieve significantly better performance in classifying high-pain and low-pain and in predicting the rating of perceived pain than only using post-stimulus brain activities. Therefore, the proposed pain prediction method holds great potential in basic research and clinical applications.