BIONB 3500

NeuroAI: Bridging Brains and AI

Course Description

Course information provided by the 2025-2026 Catalog.

We are in an AI revolution, yet these systems still can't match the brain's remarkable ability to build deep understanding of the world and use it flexibly for reasoning, planning, and adapting to new situations. This course examines neural information processing across multiple scales - from single neurons to brain systems - and their parallels in AI architectures. The course emphasizes how neuroscience insights drive AI innovation, from memory systems and neural dynamics to predictive processing and world models. For students with AI/CS/Math backgrounds, it provides deep insights into brain computation principles for developing neuroinspired algorithms. For neuroscience students, it introduces modern AI frameworks for understanding neural systems. Through topics spanning biological/artificial neural networks, hippocampal-cortical interactions, world models, and emerging neuroinspired architectures, students will explore how understanding the brain's computational principles can lead to more robust and general AI systems.

Distribution Requirements (PSC-AG)

Exploratory Studies (CU-UGR)

Last 4 terms offered (None)

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