Objective:To determine the effectiveness of a one-stage hearing screening protocol in detecting hearing loss in high risk newborns at the Neonatal Intensive Care Unit of the Jose R. Reyes Memorial Medical Center.

Methods:
Design:Cross-Sectional Study
Setting:Tertiary Government Training Hospital
Population:High-risk newborns admitted at the Neonatal Intensive Care Unit of the Jose R. Reyes Memorial Medical Center from March to December 2023 underwent a one stage universal newborn hearing screening protocol. Excluded from the study were patients who were admitted for less than 48 hours, without consent from their parents or guardians and babies who were not cleared medically to undergo testing, and those who presented with aural atresia and/or any physical anomaly of the head and the external ear.

Results:A total of 169 babies were initially seen with 16 babies lost to follow up resulting in a final total of 153 babies (or 306 ears) tested. The refer and false positive rates were 9.8% and 8.92%, respectively, on average comparable to or even better than the two-step protocol in most studies. Sensitivity was determined to be 100% while specificity was 91.08%. The incidence of hearing loss in the study population was 19.8/1000, consistent with various study outcomes for high risk newborns. There was no reported incidence of auditory neuropathy in this study. The primary risk factors that were present in babies with hearing loss were: low birth weight, prematurity, neonatal intensive care unit admission of more than 5 days and exposure to ototoxic medications.

Conclusion:The one-staged Automated Auditory Brainstem Response (AABR) is an effective and efficient newborn hearing screening protocol for high-risk newborns in the Neonatal Intensive Care Unit (NICU) setting and eventually, may be considered as an alternative hearing screening technique whenever available in this cohort. More studies about improving newborn hearing screening, cost-analysis, diagnostics and interventions of hearing loss should be pursued in implementation of the Universal Hearing Screening Law in the Philippines.

Noise-induced hearing loss is a worldwide public health issue that is characterized by temporary or permanent changes in hearing sensitivity. This condition is closely linked to inflammatory responses, and interventions targeting the inflammatory gene tumor necrosis factor-alpha (TNFα) are known to mitigate cochlear noise damage. TNFα-induced proteins (TNFAIPs) are a family of translucent acidic proteins, and TNFAIP6 has a notable association with inflammatory responses. To date, there have been few reports on TNFAIP6 levels in the inner ear. To elucidate the precise mechanism, we generated transgenic mouse models with conditional knockout of Tnfaip6 (Tnfaip6 cKO). Evaluation of hair cell morphology and function revealed no significant differences in hair cell numbers or ribbon synapses between Tnfaip6 cKO and wild-type mice. Moreover, there were no notable variations in hair cell numbers or hearing function in noisy environments. Our results indicate that Tnfaip6 does not have a substantial impact on the auditory system.
Animals ; Mice, Knockout ; Hair Cells, Auditory, Inner/pathology* ; Mice ; Mice, Transgenic ; Hearing Loss, Noise-Induced ; Evoked Potentials, Auditory, Brain Stem/physiology*

Attempts have been made to modulate motor sequence learning (MSL) through repetitive transcranial magnetic stimulation, targeting different sites within the sensorimotor network. However, the target with the optimum modulatory effect on neural plasticity associated with MSL remains unclarified. This study was therefore designed to compare the role of the left primary motor cortex and the left supplementary motor area proper (SMAp) in modulating MSL across different complexity levels and for both hands, as well as the associated neuroplasticity by applying intermittent theta burst stimulation together with the electroencephalogram and concurrent transcranial magnetic stimulation. Our data demonstrated the role of SMAp stimulation in modulating neural communication to support MSL, which is achieved by facilitating regional activation and orchestrating neural coupling across distributed brain regions, particularly in interhemispheric connections. These findings may have important clinical implications, particularly for motor rehabilitation in populations such as post-stroke patients.
Humans ; Transcranial Magnetic Stimulation ; Motor Cortex/physiology* ; Male ; Electroencephalography ; Neuronal Plasticity/physiology* ; Female ; Adult ; Evoked Potentials, Motor/physiology* ; Young Adult ; Learning/physiology*

The pain-evoked potential electroencephalogram (EEG) is an effective electrophysiological indicator for pain assessment, yet its extraction is challenging due to interference from background activity and involuntary blinks. Although existing blink artifact-removal methods show efficacy, they face limitations such as the need for reference signals, neglect of individual differences, and reliance on user input, hindering their practical application in clinical pain assessments. In this paper, we propose a novel framework applying adaptive quadrature mirror filter banks (AQMFB) with discrete wavelet transform (DWT) to remove blink artifacts in pain EEG. Unlike traditional DWT methods that apply fixed wavelets across subjects, our method adapts wavelet construction based on the characteristics of EEG. Experimental results demonstrate that AQMFB-DWT outperforms four leading methods in removing blink artifacts with minimal distortion of pain information, all within an acceptable processing time. This technique is a valuable preprocessing step for enhancing the extraction of pain-evoked potentials.
Humans ; Artifacts ; Blinking/physiology* ; Electroencephalography/methods* ; Pain/diagnosis* ; Male ; Wavelet Analysis ; Adult ; Female ; Evoked Potentials/physiology* ; Young Adult ; Brain/physiopathology* ; Pain Measurement/methods* ; Signal Processing, Computer-Assisted

This paper realized a portable brain-computer interface (BCI) system tailored for smart healthcare. Through the decoding of steady-state visual evoked potential (SSVEP), this system can rapidly and accurately identify the intentions of subjects, thereby meeting the practical demands of daily medical scenarios. Firstly, an SSVEP stimulation interface and an electroencephalogram (EEG) signal acquisition software were designed, which enable the system to execute multi-target and multi-task operations while also incorporating data visualization functionality. Secondly, the EEG signals recorded from the occipital region were decomposed into eight sub-frequency bands using filter bank canonical correlation analysis (FBCCA). Subsequently, the similarity between each sub-band signal and the reference signals was computed to achieve efficient SSVEP decoding. Finally, 15 subjects were recruited to participate in the online evaluation of the system. The experimental results indicated that in real-world scenarios, the system achieved an average accuracy of 85.19% in identifying the intentions of the subjects, and an information transfer rate (ITR) of 37.52 bit/min. This system was awarded third prize in the Visual BCI Innovation Application Development competition at the 2024 World Robot Contest, validating its effectiveness. In conclusion, this study has developed a portable, multifunctional SSVEP online decoding system, providing an effective approach for human-computer interaction in smart healthcare.
Brain-Computer Interfaces ; Humans ; Evoked Potentials, Visual/physiology* ; Electroencephalography ; Signal Processing, Computer-Assisted ; Software ; Adult ; Male

Brain-computer interface (BCI) has high application value in the field of healthcare. However, in practical clinical applications, convenience and system performance should be considered in the use of BCI. Wearable BCIs are generally with high convenience, but their performance in real-life scenario needs to be evaluated. This study proposed a wearable steady-state visual evoked potential (SSVEP)-based BCI system equipped with a small-sized electroencephalogram (EEG) collector and a high-performance training-free decoding algorithm. Ten healthy subjects participated in the test of BCI system under simplified experimental preparation. The results showed that the average classification accuracy of this BCI was 94.10% for 40 targets, and there was no significant difference compared to the dataset collected under the laboratory condition. The system achieved a maximum information transfer rate (ITR) of 115.25 bit/min with 8-channel signal and 98.49 bit/min with 4-channel signal, indicating that the 4-channel solution can be used as an option for the few-channel BCI. Overall, this wearable SSVEP-BCI can achieve good performance in real-life scenario, which helps to promote BCI technology in clinical practice.
Brain-Computer Interfaces ; Humans ; Evoked Potentials, Visual/physiology* ; Electroencephalography ; Wearable Electronic Devices ; Algorithms ; Signal Processing, Computer-Assisted ; Adult ; Male

In recent years, it has become a new direction in the field of neuroscience to explore the mode characteristics, functional significance and interaction mechanism of resting spontaneous electroencephalography (EEG) and task-evoked EEG. This paper introduced the basic characteristics of spontaneous EEG and task-evoked EEG, and summarized the core role of spontaneous EEG in shaping the adaptability of the nervous system. It focused on how the spontaneous EEG interacted with the task-evoked EEG in the process of task processing, and emphasized that the spontaneous EEG could significantly affect the performance of tasks such as perception, cognition and movement by regulating neural activities and predicting external stimuli. These studies provide an important theoretical basis for in-depth understanding of the principle and mechanism of brain information processing in resting and task states, and point out the direction for further exploring the complex relationship between them in the future.
Humans ; Electroencephalography/methods* ; Brain/physiology* ; Rest/physiology* ; Cognition/physiology* ; Evoked Potentials/physiology* ; Task Performance and Analysis

Brain-computer interface (BCI) technology faces structural risks due to a misalignment between its technological maturity and industrialization expectations. This study used the Technology Readiness Level (TRL) framework to assess the status of major BCI paradigms-such as steady-state visual evoked potential (SSVEP), motor imagery, and P300-and found that they predominantly remained at TRL4 to TRL6, with few stable applications reaching TRL9. The analysis identified four interrelated sources of bubble risk: overly broad definitions of BCI, excessive focus on decoding performance, asynchronous translational progress, and imprecise terminology usage. These distortions have contributed to the misallocation of research resources and public misunderstanding. To foster the sustainable development of BCI, this paper advocated the establishment of a standardized TRL evaluation system, clearer terminological boundaries, stronger support for fundamental research, enhanced ethical oversight, and the implementation of inclusive and diversified governance mechanisms.
Brain-Computer Interfaces ; Humans ; Evoked Potentials, Visual ; Electroencephalography ; Event-Related Potentials, P300

In recent years, hybrid brain-computer interfaces (BCIs) have gained significant attention due to their demonstrated advantages in increasing the number of targets and enhancing robustness of the systems. However, Existing studies usually construct BCI systems using intense auditory stimulation and strong central visual stimulation, which lead to poor user experience and indicate a need for improving system comfort. Studies have proved that the use of peripheral visual stimulation and lower intensity of auditory stimulation can effectively boost the user's comfort. Therefore, this study used high-frequency peripheral visual stimulation and 40-dB weak auditory stimulation to elicit steady-state visual evoked potential (SSVEP) and auditory steady-state response (ASSR) signals, building a high-comfort hybrid BCI based on weak audio-visual evoked responses. This system coded 40 targets via 20 high-frequency visual stimulation frequencies and two auditory stimulation frequencies, improving the coding efficiency of BCI systems. Results showed that the hybrid system's averaged classification accuracy was (78.00 ± 12.18) %, and the information transfer rate (ITR) could reached 27.47 bits/min. This study offers new ideas for the design of hybrid BCI paradigm based on imperceptible stimulation.
Brain-Computer Interfaces ; Humans ; Evoked Potentials, Visual/physiology* ; Acoustic Stimulation ; Photic Stimulation ; Electroencephalography ; Evoked Potentials, Auditory/physiology* ; Adult

Early identification of adolescent depression requires objective biomarkers. This study investigated the functional near-infrared spectroscopy (fNIRS) activation patterns and mismatch negativity (MMN) characteristics in adolescents with first-episode mild-to-moderate depression. We enrolled 33 patients and 33 matched healthy controls, measuring oxyhemoglobin (Oxy-Hb) concentration in the frontal cortex during verbal fluency tasks via fNIRS, and recording MMN latency/amplitude at Fz/Cz electrodes using event-related potentials (ERP). Compared with healthy controls, the depression group showed significantly prolonged MMN latency [Fz: (227.88 ± 31.08) ms vs. (208.70 ± 25.35) ms, P < 0.01; Cz: (223.73 ± 29.03) ms vs. (204.18 ± 22.43) ms, P < 0.01], and obviously reduced Fz amplitude [(2.42 ± 2.18) μV vs. (5.65 ± 5.59) μV, P = 0.03]. A significant positive correlation was observed between MMN latencies at Fz and Cz electrodes ( P < 0.01). Oxy-Hb in left frontopolar prefrontal channels (CH15/17) was significantly decreased in patient group ( P < 0.05). Our findings suggest that adolescents with depression exhibit hypofunction in the left prefrontal cortex and impaired automatic sensory processing. The combined application of fNIRS and ERP techniques may provide an objective basis for early clinical identification.
Humans ; Spectroscopy, Near-Infrared/methods* ; Adolescent ; Prefrontal Cortex/physiopathology* ; Evoked Potentials/physiology* ; Depression/physiopathology* ; Female ; Male ; Oxyhemoglobins ; Electroencephalography