Neurosurgery is entering an era of intelligent and personalized precision. The new generation of neurosurgeons needs not only superb surgical skills, but also the ability to master computer technology, imaging technology and neuromodulation. The application of artificial intelligence (AI) technology in neurosurgery includes machine learning (ML), deep learning (DL) and large language model (LLM). This article introduces specific cases in neurological tumors, spinal diseases, epilepsy and cerebrovascular diseases. Digit-intelligent neurosurgery focuses on the deep integration of digitalization and intelligentization in the field of neurosurgery. Digit-intelligent neurosurgery should establish a technical system of intelligent perception, intelligent cognition, intelligent decision-making and intelligent operation. With the deep integration of digitalization and intelligentization, neurosurgery will usher in unprecedented technological changes.
The application and development of digital intelligence technology in the field of neuroscience have provided powerful tools for fundamental research on brain functions, as well as for the diagnosis, treatment and rehabilitation of neurological disorders. This article reviews the latest advancements in the application of digital intelligence technology in basic brain function research, neurosurgery, neurology and neurorehabilitation, while also addressing the challenges and future development trends in the field. The aim is to provide new insights for the advancement of digital intelligence technology in neurology.
High performance computing (HPC) is transforming the field of large-scale brain simulation by enabling the integration of multi-scale computational modeling with massive neuroscience data. With advanced HPC resources, researchers can simulate neural activities from ion-channel dynamics to whole-brain network interactions, thereby illuminating the mechanisms underlying cognition, neural disorders, and emerging neuromorphic intelligence. This review examines the theoretical principles and technical foundations of supercomputer brain simulation, including distributed parallel algorithms, graphics processing unit (GPU)-based acceleration, and multimodal data management. It also surveys prominent simulation platforms such as NEST, NEURON, and The Virtual Brain (TVB), highlighting their strengths in modeling spiking neuronal network (SNN), multicompartmental neurons, and large-scale functional connectivity, respectively. Furthermore, we discuss the practical applications of these simulations in elucidating disease mechanisms in Alzheimer's disease (AD), Parkinson's disease (PD), autism spectrum disorder (ASD), schizophrenia, and epilepsy. Special emphasis is placed on how supercomputer brain simulation assists in virtual drug screening, optimizing deep brain stimulation parameters, and supporting digital twin approaches for personalized medicine. Finally, we address the critical challenges and future directions in this rapidly evolving domain, including the trade-off between computational cost and biological realism, data integration and validation, and the necessity for interdisciplinary collaboration. The advent of exascale supercomputers and the convergence of neuroinformatics and machine learning (ML) are poised to propel brain simulation research toward unprecedented clinical and scientific breakthroughs.
The motor network is a key system in the central nervous system responsible for motor control and coordination, and its dysfunction is closely associated with various nervous system diseases. This review summarizes the physiological and pathological characteristics of the motor network, with a focus on its structural and functional changes in nervous system diseases. Additionally, the potential future developments in precision medicine and data integration are discussed.
Intraoperative ultrasound (iUS) is a low-cost, portable and user-friendly auxiliary tool in brain tumor surgery, yet there is a lack of standardized operational guidelines. This review begins with the ultrasound physics and summarizes the workflow of iUS, followed by a grading system for ultrasonographic visibility of intracerebral lesions, iUS in assessing brain tumor resection, the limitations of iUS-guided brain tumor resection, multimodal ultrasound imaging, and the application of artificial intelligence (AI) in iUS. This review shows the clinical practice of iUS in brain tumor surgery from multiple perspectives and proposes practical standards.
The high heterogeneity and resistance of glioma present significant challenges in clinical treatment. The rapid development of multi-omics technologies has greatly advanced the understanding of the molecular mechanisms, resistance characteristics, and potential new drug targets in glioma. Building on this, multi-omics data is now being used for drug screening, mechanism exploration, and clinical trial guidance, thereby accelerating the translation of novel therapies and precision medicine strategies into clinical applications for the treatment of glioma. This review focuses on the latest advancements in the application of multi-omics technologies in glioma drug research and development, highlighting how insights into genetic mutations, gene expression, protein functions, and metabolic reprogramming can aid in understanding the molecular mechanisms, resistance, and complexity of the tumor microenvironment. Furthermore, it provides critical support for the identification of new drug targets, the development of personalized treatment plans, and drug screening, thus advancing the field of personalized and precision medicine in the treatment of glioma.
The rapid development of neurosurgery robots and navigation systems has significantly enhanced surgical precision and safety. Neurosurgery robots, based on stereotactic technology, achieve submillimeter-level positioning through multi-modal image fusion and non-invasive registration techniques. Equipped with high-degree-of-freedom robotic arms and integrated sensors, they precisely perform complex procedures such as stereo-electroencephalography (SEEG) electrode implantation, deep brain stimulation (DBS) device placement, and magnetic resonance-guided laser interstitial thermal therapy (MRgLITT). Navigation systems employ optical or electromagnetic tracking technologies combined with multi-modal imaging to assist surgeons in tracking important structures and target lesion tissue precisely. Future advancements may autonomously generate personalized surgical plans to reduce human error, while flexible robotic arms and novel endoscope-holding robots could expand endoscopic applications. Furthermore, the integration of multiple technologies will broaden neurosurgical applications. These innovations not only minimize complication risks and shorten treatment periods, but also propel the field toward intelligent, minimally invasive neurosurgery.
With its high positioning accuracy, transcranial magnetic stimulation (TMS) has become an important means of non-invasive neuromodulation technique. This article analyzes the current status and challenges of precise positioning navigation technology, points out that the current navigation equipment is expensive and caliper-based simplified precision positioning method is difficult to monitor head movements in real time, and proposes the necessity of developing low-cost, high-precision navigation technology. Focus on the precise positioning technology of TMS and its application in clinical treatment and cognitive function positioning. Finally, the application prospects of precise positioning TMS in clinical treatment and cognitive function positioning are discussed, and it is pointed out that future research directions should focus on comparative studies of precise positioning and non - precise positioning treatment, as well as in - depth exploration of the precise positioning TMS treatment mechanism guided by fiber connections.
Non-invasive neuromodulation techniques have achieved remarkable advancements in the field of neuroscience in recent years, emerging as a crucial tool for researching and treating numerous neuropsychiatric disorders. The primary methods of non-invasive neuromodulation techniques, including transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), have increasingly been incorporated into clinical practice and demonstrated impressive outcomes in depression, anxiety, and chronic pain. However, the application of non-invasive neuromodulation techniques still encounter several challenges, such as significant individual response variations, limited duration of therapeutic effects, and issues with standardizing stimulation parameters. This paper provides a comprehensive review of the primary non-invasive neuromodulation techniques and their current applications in brain functional diseases, analyzes the efficacy evaluation and future development direction to provide reference for further exploring their expanded applications in brain functional diseases and neural functions.
