Abstract: High-throughput detection techniques have become a class of efficient assays for assessing chemical neurotoxicity, showing significant promise for future applications. This paper reviews the current status of the application of four high-throughput detection technologies, namely spatial omics detection, high-content imaging, high-throughput sequencing, and computational toxicology, in neurotoxicity assessment studies. Their respective advantages and development prospects are analyzed and discussed. Spatial omics, by integrating multiple omics approaches such as metabolomics, transcriptomics, and proteomics, helps to elucidate the spatial distribution of metabolites and gene expression, thereby promoting a deeper understanding of neurotoxicity mechanisms. High-content imaging technology enables the efficient assessment of chemical neurotoxicity by identifying cellular phenotypic changes and discovering sensitive biomarkers in a high-throughput manner. High-throughput sequencing, as a class of large-scale parallel technologies, encompasses RNA sequencing, epigenomic sequencing, single-cell sequencing, and whole-genome sequencing for the analysis of gene expression profiles and epigenetic modifications, providing critical support for elucidating neurotoxicity mechanisms and identifying potential biomarkers. Computational toxicological approaches facilitate the toxicity assessment and risk management of neurotoxicants from a high-throughput perspective by constructing adverse outcome pathways, thereby serving as an alternative to animal experiments for neurotoxicity detection.