IN a breakthrough that could accelerate research into Sudden Unexpected Death in Epilepsy (SUDEP), researchers have demonstrated that a state-of-the-art AI model, GPT-4o, can accurately extract neural projections from scientific literature. The study shows the model’s potential to automate a labor-intensive process that has long challenged neuroscientists.
SUDEP remains one of the leading causes of death in individuals with uncontrolled epilepsy, particularly among otherwise healthy young patients. A major barrier to understanding its mechanisms lies in the complexity of neural circuits regulating cardiorespiratory function. Mapping these pathways requires synthesizing data from decades of dense, often inconsistently written scientific studies—a task traditionally handled through time-consuming manual reviews.
To streamline this process, the researchers developed a set of custom prompts enabling GPT-4o to extract neuroanatomical structures, their connections, and harmonize terminology across multiple studies. The model was applied to four peer-reviewed neuroscience articles, from which it identified 205 distinct neural projections. A blinded review by an expert neuroanatomist of a random sample of 100 projections found that 95 were accurate, demonstrating the tool’s reliability in parsing and synthesizing complex academic content.
The study’s findings point to an emerging role for large language models in biomedical discovery, particularly in high-volume fields where precision and scale are essential. While the current focus was limited to identifying brain region projections, future iterations of the model aim to incorporate data on species, experimental techniques, and additional entity types. These enhancements could support broader applications in disease modeling, treatment development, and neuroscience education.
By making neural circuit data more accessible and searchable, this automated pipeline may help clinicians and researchers better understand SUDEP’s underlying biology—paving the way for more targeted prevention strategies.
Reference:
Abeysinghe R et al. Leveraging GPT-4o for Automated Extraction of Neural Projections from Scientific Literature. AMIA Jt Summits Transl Sci Proc. 2025;2025:32-41.
