Augmented reality (AR) involves the overlay of computer-generated images onto the user’s real-world visual field to modify or enhance the user’s visual experience. With respect to neurosurgery, AR integrates preoperative and intraoperative imaging data to create an enriched surgical experience that has been shown to improve surgical planning, refine neuronavigation, and reduce operation time. In addition, AR has the potential to serve as a valuable training tool for neurosurgeons in a way that minimizes patient risk while facilitating comprehensive training opportunities. The increased use of AR in neurosurgery over the past decade has led to innovative research endeavors aiming to develop novel, more efficient AR systems while also improving and refining present ones. In this review, we provide a concise overview of AR, detail current and emerging uses of AR in neurosurgery and neurosurgical training, discuss the limitations of AR, and provide future research directions. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), 386 articles were initially identified. Two independent reviewers (GH and AC) assessed article eligibility for inclusion, and 31 articles are included in this review. The literature search included original (retrospective and prospective) articles and case reports published in English between 2013 and 2023. AR assistance has shown promise within neuro-oncology, spinal neurosurgery, neurovascular surgery, skull-base surgery, and pediatric neurosurgery. Intraoperative use of AR was found to primarily assist with surgical planning and neuronavigation. Similarly, AR assistance for neurosurgical training focused primarily on surgical planning and neuronavigation. However, studies included in this review utilize small sample sizes and remain largely in the preliminary phase. Thus, future research must be conducted to further refine AR systems before widespread intraoperative and educational use.

Gliomas are common primary brain malignancies that remain difficult to treat due to their overall aggressiveness and heterogeneity. Although a variety of therapeutic strategies have been employed for the treatment of gliomas, there is increasing evidence that suggests ligand-gated ion channels (LGICs) can serve as a valuable biomarker and diagnostic tool in the pathogenesis of gliomas. Various LGICs, including P2X, SYT16, and PANX2, have the potential to become altered in the pathogenesis of glioma, which can disrupt the homeostatic activity of neurons, microglia, and astrocytes, further exacerbating the symptoms and progression of glioma. Consequently, LGICs, including purinoceptors, glutamate-gated receptors, and Cys-loop receptors, have been targeted in clinical trials for their potential therapeutic benefit in the diagnosis and treatment of gliomas. In this review, we discuss the role of LGICs in the pathogenesis of glioma, including genetic factors and the effect of altered LGIC activity on the biological functioning of neuronal cells. Additionally, we discuss current and emerging investigations regarding the use of LGICs as a clinical target and potential therapeutic for gliomas.

Holmes Tremor (HT) is an irregular, slow-frequency (<4.5 Hz) tremor characterized by a combination of resting, postural, and action tremors mostly of the upper extremities. Symptoms of HT typically emerge 4 weeks to 2 years after a brain injury caused by a spectrum of etiologies. HT pathophysiology is thought to result from aberrant collateral axonal sprouting and synaptic dysfunction following neuronal damage. To date, the dopaminergic nigrostriatal system, cerebello-thalamo-cortical pathway, and dentate-rubro-olivary pathway have all been implicated in the clinical manifestations of HT. The diversity of HT etiologies usually requires a personalized treatment plan. Current treatment options include carbidopa-levodopa, levetiracetam, and trihexyphenidyl, and surgical management such as deep brain stimulation in selected medication-refractory patients. In this review we discuss the pathophysiology, etiology, neuroimaging, and the latest clinical guidelines for care and management of HT.

Artificial intelligence (AI) has become an increasingly prominent tool in the field of neurosurgery, revolutionizing various aspects of patient care and surgical practices. AI-powered systems can provide real-time feedback to surgeons, enhancing precision and reducing the risk of complications during surgical procedures. The objective of this study is to review the role of AI in training neurosurgical residents, improving accuracy during surgery, and reducing complications. The literature search method involved searching PubMed using relevant keywords to identify English literature publications, including full texts, and concerning human subject matter from its inception until May 2024, initially generating 247,747 results. Articles were then screened for topic relevancy by abstract contents. Further articles were retrieved from the sources cited by the initially reviewed articles. A comprehensive review was then performed on various studies, including observational studies, case-control studies, cohort studies, clinical trials, meta-analyses, and reviews by 4 reviewers individually and then collectively. Studies on AI in neurosurgery reach more than 4000 produced over a decade alone. The majority of studies regarding clinical diagnosis, risk prediction, and intraoperative guidance remain retrospective in nature. In its current form, AI-based paradigm performed inferiorly to neurosurgery residents in test taking. AI has potential for broad applications in neurosurgery from use as a diagnostic, predictive, intraoperative, or educational tool. Further research is warranted for prospective use of AI-based technology for delivery of neurosurgical care.

Spinal cord injury (SCI) is a profoundly debilitating yet common central nervous system condition resulting in significant morbidity and mortality rates. Major causes of SCI encompass traumatic incidences such as motor vehicle accidents, falls, and sports injuries. Present treatment strategies for SCI aim to improve and enhance neurologic functionality. The ability for neural stem cells (NSCs) to differentiate into diverse neural and glial cell precursors has stimulated the investigation of stem cell scaffolds as potential therapeutics for SCI. Various scaffolding modalities including composite materials, natural polymers, synthetic polymers, and hydrogels have been explored. However, most trials remain largely in the preclinical stage, emphasizing the need to further develop and refine these treatment strategies before clinical implementation. In this review, we delve into the physiological processes that underpin NSC differentiation, including substrates and signaling pathways required for axonal regrowth post-injury, and provide an overview of current and emerging stem cell scaffolding platforms for SCI.