In recent years, remarkable progress has been made in brain–computer interface (BCI) technology. This review comprehensively explores its applications in multiple diseases, such as stroke, disorders of consciousness, and Parkinson's disease. However, this approach poses challenges in terms of signal processing accuracy, ethic, and individual differences. Future research is crucial to address these challenges and unlock the full potential of BCIs in clinical practice.

Carbon doped black phosphorus artificial synaptic devices as a promising fire monitoring system, exhibit exceptional perceptual capabilities for rapid fire event detection, effectively overcoming the limitations of conventional fire detection systems by leveraging hardware sensitivity and system processing speed.

This perspective examines the synergy between DeepSeek, a leader in efficient, open-source artificial intelligence models, and next-generation brain–computer interface (BCI) technologies. Based on the advanced technology of DeepSeek, this study explores the fusion of large language models (LLMs) in the fields of BCI devices, electroencephalogram signal processing, and individual service, and deeply discusses the data safety and ethical issues that are inevitable with LLMs, providing unique insights into the path to democratizing neurotechnology.

Parkinson's disease ranks as the second most prevalent neurodegenerative disorder, and there is an urgent need for proper experimental models to enhance our understanding of this complex disease. Non-human primates exhibit various similarities to humans, particularly in terms of motor skills, cognitive functions, and the complexity of their neural architecture. Models of Parkinson's disease using non-human primates can help us to understand the pathogenesis of Parkinson's disease, advance current therapies, and develop new methods in neuroscience.

This study aims to address the challenges in brain tumor classification by leveraging magnetic resonance imaging (MRI) to optimize diagnostic accuracy. Five classification models, namely machine learning, pre-trained deep learning, convolutional neural network (CNN), hyperparameter-tuned deep CNN, and deep siamese CNN (DeepSCNN), were evaluated. The high precision and robustness establish this model as a new benchmark in neuro-oncology diagnostics, facilitating more timely and accurate brain tumor identification for improved patient outcomes.

Research on invasive and non-invasive brain–computer interfaces (BCIs) is developing rapidly, especially in the field of medicine. This article reviews BCI software, hardware, related neural mechanisms, and clinical applications. The principles of invasive and non-invasive BCI differ; however, it is widely used in various scenarios. Based on different brain functional areas, a variety of cutting-edge clinical applications could be derived in future.

Small-world networks, with a high degree of clustering and a small characteristic path length, are the universal nature of the human brain network. This review summarizes trends in small-world networks for different neurological and psychiatric disorders, with the brain network topology analysis in treating and diagnosing mental and neurological disorders.

Peripheral nerve disease is a common disorder that can lead to sensory, motor, and autonomic dysfunction, with common symptoms including pain, loss of sensation, lack of coordination, muscle weakness, and atrophy. Defensins (which can be divided into mammal, insect, and plant defensins), as regulatory factors of the immune system, can influence peripheral nerve diseases by participating in inflammatory processes, immune responses, and pathogen resistance. As therapeutic targets, they have the potential to restore the quality of life of patients and reduce the healthcare burden.

This study proposes a model of consciousness based on information theory, positing contra the Integrated Information Theory (IIT) that perception arises from uncertainty minimization (negative entropy). Unlike the causal information definition of IIT, this model adopts the framework of standard information theory, emphasizing the role of quantum coherence in consciousness and offering a new perspective for understanding the computational mechanisms of consciousness.

Large language models, including DeepSeek and ChatGPT, have the potential to significantly advance brain-computer interfaces and brain-inspired computing by enhancing the accuracy of brain signal decoding and optimizing user interaction. In brain-computer interfaces, these models facilitate more precise and responsive communication, while in brain-inspired computing, they enable realistic simulation of neural networks and improved hardware energy efficiency. However, substantial challenges remain, particularly in healthcare applications and other broader fields.

This study investigates the transcriptional profiles of gliomas across different grades (WHO II-IV) and clinical states (primary vs. recurrent). Utilizing RNA-seq data from public databases (e.g., GEO), we analyzed low-grade gliomas and high-grade gliomas, including oligodendrogliomas, glioblastomas, and other glioma subtypes. Key analyses encompassed differential gene expression, glioma subpopulation characterization (e.g., glioma-associated microglia/macrophages), regulatory network construction (WGCNA and transcription factor activity), and cell state analysis comparing primary and recurrent gliomas. Our findings reveal distinct transcriptional signatures and identify potential biomarkers associated with glioma progression and recurrence.

This review summarizes recent advances in the fundamental materials, functional designs, and application schemes of hydrogels for peripheral nerve repair. The hydrogels discussed here can be used to repair peripheral nerve injury, including filling the damaged area, transmitting electrical stimulation signals, and delivering therapeutic ingredients. The advances summarized in this review can guide the future direction of this biomaterial and provide a foundation for next-generation functionalized hydrogels.

A steady-state visually evoked potential (SSVEP) is a response to visual stimuli frequencies, but brain–computer interfaces (BCIs) struggle to distinguish it from spontaneous signals. This study proposes the variational mode decomposition–based filter bank canonical correlation analysis (VMD-FBCCA) algorithm to improve recognition accuracy by addressing overlapping frequency coverage between evoked and spontaneous electroencephalography signals. The algorithm has great prospects for developing improved BCI systems and offers a novel perspective for SSVEP-BCI research. Future research should enhance the robustness of the VMD-FBCCA algorithm and apply it to the development of SSVEP-BCI systems.

The optimal treatment for chronic intracranial arterial occlusion remains uncertain, with endovascular recanalization presenting significant challenges. Accurate assessment of the distal vascular bed during the procedure is critical for success. This paper introduces a technique utilizing dynamic real-time three-dimensional roadmap guidance, which reduces radiation exposure, contrast medium usage, and procedure-related complications such as vessel perforation or dissection. The dynamic 3D roadmap offers a safe, accurate, and effective tool for endovascular recanalization in chronic intracranial arterial occlusion.

Sciatica is a severe pain that radiates from the back to the hip and outer side of the leg caused by compression of the sciatic nerve. However, traditional treatments can be invasive and costly and may not provide long-term relief. Occupational therapy offers a promising alternative. This article explores occupational therapy-based assessments, interventions, outcomes, progress tracking, pharmacotherapy, challenges owing to surgical approaches, and devices for sciatic pain rehabilitation. Future research could focus on developing and validating new assessment tools and outcome measures specific to sciatica, enabling more accurate evaluation and progress monitoring.

This perspective paper discusses how the development of flexible neural interfaces and devices can overcome the limitations of traditional neurotechnology and could revolutionize investigations into neural principles behind intelligence, consciousness, and behavior. Innovations in material science and device/system-level integrations further extend research capabilities to free-behaving animals, enabling profound insights into neurocognitive functions. Advances in artificial intelligence and brain organoids promise future decoding of complex neural signals. The development of transient materials and devices will provide the foundation for deploying next-generation neurotechnologies in clinics, aiming to treat complex neurogenic diseases and improve neurorehabilitation.

This paper reviews the pathogenesis of hydrocephalus, emphasizing the role of oxidative stress in hydrocephalus, including the causes of oxidative stress, related signaling pathways, and pathological changes from oxidative stress. This paper aims to discuss the possibility of oxidative stress as a new target for hydrocephalus treatment; thus it details antioxidants with potential for future hydrocephalus research.

Physiological roles of Piezo channels in the auditory system. The Piezo channels in hair cells are related to the anomalous current, Nelson's notch, ultrasonic hearing, hair cell differentiation, and the mechanotransduction process in the cochlear.

Coronavirus disease (COVID-19) and long COVID can result in changes in brain perfusion, which may contribute to impaired cognition and hindered recovery. Arterial spin labeling (ASL), as a non-invasive magnetic resonance imaging technique, proves useful for investigating the effects of COVID-19 on cerebral function. This review emphasizes that both COVID-19 and long COVID may induce alterations in brain perfusion.

This review addresses welfare issues through the 3Rs: refining experimental conditions, reducing animal usage, and replacing animals with alternative methods, and systematically examines the main kinds of model animals in neuroscience. Their current status is concisely summarized, representing a thoughtful and comprehensive consideration of the welfare aspects.

An update for molecular basis and treatment: The major posttranslational modification (PTM) changes and crosstalk in the evolution of retinal degenerative disorders including glaucoma, diabetic retinopathy (DR), age-related macular degeneration and myopia retinopathy.