NACS 645: NeuroAI
Links between artificial neural systems and biological cognition: models, limits, and interpretations.
Course material for NACS 645: Introduction to Cognitive Science (Fall 2025) at the University of Maryland. Sessions covered: NeuroAI 1 (is ai part of cognitive science), NeuroAI 2 (cognitive properties of llms).
Required readings:
- Yamins, D. L. K., & DiCarlo, J. J. (2016). Using goal-driven deep learning models to understand sensory cortex. Nature Neuroscience, 19(3), 356–365.
- Richards, B. A. et al. (2019). A deep learning framework for neuroscience. Nature Neuroscience, 22(11), 1761–1770.
- Palminteri, S., & Pistilli, G. (2025). Navigating Inflationary and Deflationary Claims Concerning Large Language Models Avoiding Cognitive Biases
- Silver, D., Singh, S., Precup, D., & Sutton, R. S. (2021). Reward is enough. Artificial intelligence, 299, 103535.
- Fedorenko, E., Piantadosi, S. T., & Gibson, E. A. (2024). Language is primarily a tool for communication rather than thought. Nature, 630(8017), 575-586
The material is provided below as a single PDF.
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