Scotti, P.S., Banerjee, A., Goode, J., Shabalin, S., Nguyen, A., Cohen, E., Dempster, A.J., Verlinde, N., Yundler, E., Weisberg, D., Norman, K.A., & Abraham, T.M. (2023). Advances in Neural Information Processing Systems (NeurIPS) 37.
Author: Elita Lee
Bayesian surprise predicts human event segmentation in story listening
Kumar, M., Goldstein, A., Michelmann, S., Zacks, J.M., Hasson, U., & Norman, K.A. (2023). Cognitive Science.
Test-retest reliability of the human connectome: An OPM-MEG study
Rier, L., Michelmann, S., Ritz, H., Shah, V., Hill, R.M., Osborne, J., Doyle, C., Holmes, N., Bowtell, R., Brookes, M.J., Norman, K.A., Hasson, U., Cohen, J.D., & Boto, E. (2023). Imaging Neuroscience.
Optimal metacognitive control of memory recall
Callaway, F., Griffiths, T.L., Norman, K.A., & Zhang, Q. (2023). Psychological Review.
Eye tracking evidence for the reinstatement of emotionally negative and neutral memories
Brooks, P.P., Guzman, B.A., Kensinger, E.A., Norman, K.A., & Ritchey, M. (2023). PsyArXivÂ
Modeling hippocampal-cortical interaction during event processing
Lu, Q., Hasson, U., & Norman, K.A. (2018) Poster presented at the Conference of Cognitive Computational Neuroscience, Philadelphia, PA.
Patience is a virtue: learning when to encode/recall episodic memories
Lu, Q., Fan, Z.Y., Hasson, U., & Norman, K.A. (2019). Poster presented at the Context and Episodic Memory Symposium, Philadelphia, PA.
Optimal timing for episodic retrieval and encoding for event understanding
Lu, Q., Fan, Z.Y., Hasson, U., & Norman, K.A. (2019). Poster presented at the Conference of Cognitive Computational Neuroscience, Berlin, Germany.
Strategic control of episodic memory through post-gating
Dong, C., Lu, Q., & Norman, K.A. (2023). Poster presented at the Conference of Cognitive Computational Neuroscience, Oxford, UK.
Toward a more neurally plausible neural network model of latent cause inference
Lu, Q., Nguyen, T., Hasson, U., Griffiths, T., Zacks, J., Gershman, S., & Norman, K.A. (2023). Poster presented at the Conference of Cognitive Computational Neuroscience, Oxford, UK.
Blocked training facilitates learning of multiple schemas
Beukers, A.O., Collin, S.H.P., Kempner, R.P., Franklin, N.T., Gershman, S.J., & Norman, K.A. (2023). PsyArXiv.
Differentiation and integration of competing memories: a neural network model
Ritvo, V.J.H., Nguyen, A., Turk-Browne, N.B., & Norman, K.A. (2023). bioRxiv.
Improving memory search through model-based cue selection
Cornell, C.A., Norman, K.A., Griffiths, T.L., & Zhang, Q. (2023). PsyArXiv.
Large language models can segment narrative events similarly to humans
Michelmann, S., Kumar, M., Norman, K.A., & Toneva, M. (2023). arXiv.
Neural representations of naturalistic events are updated as our understanding of the past changes
Zadbood, A., Nastase, S., Chen, J., Norman, K.A., & Hasson, U. (2022). eLife.
Evidence that event boundaries are access points for memory retrieval
Michelmann, S., Hasson, U., & Norman, K.A. (2023). Psychological Science.
How well do unsupervised learning algorithms model human real-time and life-long learning?
Zhuang, C., Xiang, V., Bai, Y., Jia, X., Turk-Browne, N., Norman, K., DiCarlo, J.J., & Yamins, D.L. (2022). Advances in Neural Information Processing Systems (NeurIPS) 36.