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- Learning to apply schematic knowledge to novel instances
Chen, C., Lu, Q., Beukers, A., Baldassano, C., & Norman, K.A. (2019). arXiv.
- Structured event memory: a neuro-symbolic model of event cognition
Franklin, N., Norman, K.A., Ranganath, C., Zacks, J.M., & Gershman, S.J. (2019). bioRxiv.
- Shared representational geometry across neural networks
Lu, Q., Chen, P.H., Pillow, J.W., Ramadge, P., Norman, K.A., & Hasson, U. (2018). arXiv.
- Targeted memory reactivation during sleep elicits neural signals related to learning content
Wang, B., Antony, J., Lurie, S., Brooks, P.P., Paller, K., & Norman, K.A. (2018). bioRxiv.
- Leabra7: a Python package for modeling recurrent, biologically-realistic neural networks
Greenidge, C.D., Miller, N., & Norman, K.A. (2018). arXiv.
* Simulation Code
- Neurofeedback helps to reveal a relationship between context reinstatement and memory retrieval
deBettencourt, M.T., Turk-Browne, N.B., & Norman, K.A. (2018). bioRxiv.
- Perceptual decisions result from the continuous accumulation of memory and sensory evidence
Bornstein, A.M., Aly, M., Feng, S., Turk-Browne, N.B., Norman, K.A., & Cohen, J.D. (2017). bioRxiv.
* fMRI data