As AI continues to advance, its integration into neuroimaging and biomedical research brings both immense potential and complex challenges. We will examine the role of open science principles in AI-based brain decoding projects, the ethical considerations of AI in biomedical research, and how biological systems can inspire machine learning models. The session will also highlight emerging standards for AI-readiness in biomedical data and the ethical implications of AI in clinical practice. Experts with diverse backgrounds in AI, neuroimaging, and biological systems will share their insights and experiences, fostering an open discussion that encourages critical thinking about the future of AI in neuroimaging. By exploring these timely issues, the symposium will provide valuable knowledge on the best practices for responsible AI use and how biological systems can enhance machine learning efficiency. The goal is to promote deeper understanding and encourage the development of AI methods that are both scientifically rigorous and ethically sound, benefiting researchers, clinicians, and AI practitioners alike.

Provide insights into the ethical considerations and standards for AI applications in neuroimaging and biomedical research, including AI-readiness of biomedical data and explainable AI (XAI).

Stimulate critical thinking on how open science principles, including reproducibility, can be implemented inclusively in AI-driven neuroimaging research, addressing both financial and accessibility challenges.

Explore the role of biological neural networks in enhancing the efficiency of machine learning models, encouraging discussions on how biological systems can inspire advancements in AI and neuroimaging applications.

OSR 2025 | OSR Panel: Harnessing AI and Biological Systems for Advancing Neuroimaging and Biomedical Research