From regulatory mechanisms to cutting‐edge applications: Research progress of ultrasound, electrical, magnetic, and optical stimulation in neural modulation
Year: 2026
Type: article
Abstract: In recent years, the clinical treatment and symptom management of neurological disorders have faced significant challenges due to the high complexity of the nervous system's structure and function. Against this backdrop, physical stimulation techniques have emerged as a vital complementary approach to traditional pharmacological treatments and surgical interventions. These techniques utilize physical modalities to specifically target and modulate neural function and tissue activity, thereby achieving therapeutic outcomes. They offer several advantages, including noninvasive or minimally invasive properties, high safety profiles, and strong adjustability, which enable precise intervention while effectively mitigating the risks associated with drug dependence and adverse effects. This article systematically reviews four physical stimulation modalities—ultrasound, electrical, magnetic, and optical stimulation—focusing on their mechanisms and research findings for neuromodulation and the treatment of neurological diseases. It also summarizes the latest research trends in the field of physical neuromodulation, including the application of novel experimental models (such as brain organoids), the development of closed‐loop modulation systems, and the integration of multimodal stimulation approaches. Furthermore, the article discusses the existing limitations and challenges in this field and outlines future directions and prospects, aiming to provide reference for the further development and clinical translation of physical neuromodulation technologies.
Source: Journal of intelligent medicine.
DOI: 10.1002/jim4.70031
Authors: Wanying Li, Liqun Chen
Institution: Tianjin University
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Award: G103148860
OpenAlex ID: W7160870120
