Reconciling Shared versus Context-Specific Information in a Neural Network Model of Latent Causes
Lu, Q., Nguyen, T., Zhang Q., Hasson, U., Griffiths, T. L., Zacks, J. M., Gershman, S. J., Norman, K. A. (2023).
arXiv / under review
paper,
code
A Neural Network Model of When to Retrieve and Encode Episodic Memories
Lu, Q., Hasson, U., & Norman, K. A. (2022).
eLife
paper,
code
BrainIAK: Brain Imaging and Analysis Kit
Kumar, M., Anderson, M.J., Antony, J.W., Baldassano C., Brooks, P.P., Cai, M.B., Chen, P.H.C., Ellis, C.T., Henselman-Petrusek, G., Huberdeau, D., Hutchinson, J.B., Li, P.Y., Lu, Q., Manning, J.R., Mennen, A.C., Nastase, S.A., Hugo, R.,
Schapiro, A.C., Schuck, N.W., Shvartsman, M., Sundaram, N., Suo, D., Turek, J.S., Vo, V.A., Wallace, G., Wang, Y., Zhang, H., Zhu, X., Capota, M., Cohen, J.D., Hasson, U., Li, K., Ramadge, P.J., Turk-Browne, N.B., Willke, T.L. & Norman,
K.A. (2022)
Aerture Neuro
paper,
software
Learning to Perform Role-Filler Binding with Schematic Knowledge
Chen, C., Lu, Q., Beukers, A., Baldassano, C., Norman, K. A. (2021)
PeerJ
paper,
code
Evidence for a deep, distributed and dynamic code for animacy in human ventral anterior temporal cortex
Rogers, T. T., Cox, C., Lu, Q., Shimotake, A., Kikuch, T., Kunieda, T., Miyamoto, S., Takahashi, R., Ikeda, A., Matsumoto, R., Lambon Ralph, M. A. (2021)
eLife
paper,
code
Learning to use episodic memory for event prediction
Lu, Q., Hasson, U., & Norman, K. A. (2020).
bioRxiv
paper
BrainIAK tutorials: User-friendly learning materials for advanced fMRI analysis
Kumar, M., Ellis, C. T., Lu, Q., Zhang, H., Capotă, M., Willke, T. L., Ramadge, P. J., Turk-Browne, N. B., & Norman, K. A. (2020).
PLoS Computational Biology
paper,
tutorial,
poster
Shared representational geometry across neural networks
Lu, Q., Chen, P. H., Pillow, J. W., Ramadge, P. J., Norman, K. A., & Hasson, U. (2018)
Workshop on Integration of Deep Learning Theories, NeurIPS.
poster,
paper,
code,
tutorial
A Parallel-Distributed Processing approach to mathematical cognition
McClelland, J. L., Mickey, K., Hansen, S., Yuan, X., & Lu, Q. (2016).
paper
Episodic memory can contribute to the acquisition of structured task representation.
Lu, Q., & Norman, K. A. (2023).
Mattar lab. New York University. PI: Marcelo Mattar
The influence of event structure on optimal memory policies
Lu, Q., Hasson, U., & Norman, K. A. (2023).
Department of Psychology. The University of Hong Kong. Host PI: Xiaoqing Hu
The influence of event structure on optimal memory policies
Lu, Q., Hasson, U., & Norman, K. A. (2023).
Shohamy Lab. Columbia University. PI: Daphna Shohamy
When to retrieve and encode episodic memories: a neural network model of hippocampal-cortical interaction.
Lu, Q., Hasson, U., & Norman, K. A. (2022).
Penn Computational Cognitive Neuroscience Lab. University of Pennsylvania. PI: Anna Schapiro
When to retrieve and encode episodic memories: a neural network model of hippocampal-cortical interaction.
Lu, Q., Hasson, U., & Norman, K. A. (2022).
Mila Neural-AI Reading Group.
Why should episodic retrieval and encoding occur selectively.
Lu, Q., Hasson, U., & Norman, K. A. (2021).
Contextual Dynamics Lab. Dartmouth College. PI: Jeremy Manning.
Why should episodic retrieval and encoding occur selectively.
Lu, Q., Hasson, U., & Norman, K. A. (2021).
Honey lab & Chen lab. Johns Hopkins University. PI: Janice Chen & Chris Honey.
When to recall and encode episodic memory.
Lu, Q., Hasson, U., & Norman, K. A. (2021).
Google DeepMind.
When to recall and encode episodic memory.
Lu, Q., Hasson, U., & Norman, K. A. (2021).
Oxford Neurotheory Lab, University of Oxford. PI: Andrew Saxe.
Learning to Perform Role-Filler Binding with Schematic Knowledge
Chen, C., Lu, Q., Beukers, A., Baldassano, C., Norman, K. A. (2021)
Oxford Neurotheory Lab, University of Oxford. PI: Andrew Saxe.
Modeling when episodic encoding should take place to support event prediction
Lu, Q., Hasson, U., & Norman, K. A. (2021)
Cognitive Neuroscience Society (CNS) Annual meeting
Invited symposium on how prior knowledge shapes encoding of new memories
video,
slides
Learning to use episodic memory for event prediction
Lu, Q., Hasson, U., & Norman, K. A. (2020)
Context and Episodic Memory Symposium (CEMS)
video,
slides
Learning when to recall
Lu, Q., Hasson, U., & Norman, K. A. (2020)
Neuromatch
Slides
Toward a More Neurally Plausible Neural Network Model of Latent Cause Inference.
Lu, Q., Nguyen, T., Hasson, U., Griffiths, T. L., Zacks, J. M., Gershman, S. J., Norman, K. A. (2023)
The Conference on Cognitive Computational Neuroscience (CCN)
poster,
paper
Strategic Control of Episodic Memory Through Post-Gating.
Dong, C., Lu, Q., Norman, K. A. (2023)
The Conference on Cognitive Computational Neuroscience (CCN)
poster,
paper
Optimal timing for episodic retrieval and encoding for event understanding
Lu, Q., Fan, Z. Y., Hasson, U., & Norman, K. A. (2019)
The Conference on Cognitive Computational Neuroscience (CCN)
poster,
paper
Patience is a virtue: A normative account of why waiting to encode and retrieve memories benefits event understanding
Lu, Q., Fan, Z. Y., Hasson, U., & Norman, K. A. (2019)
The Context and Episodic Memory Symposium (CEMS)
poster
BrainIAK tutorials: user-friendly learning materials for advanced fMRI analysis
Kumar, M., Ellis, C.T., Lu, Q., Zhang, H., Capota, M., Willke, T.L., Ramadge, P.J., Turk-Browne, N.B., & Norman, K.A. (2019)
Society for neuroscience conference (SfN)
paper,
tutorial,
poster
Shared representational geometry across neural networks
Lu, Q., Chen, P. H., Pillow, J. W., Ramadge, P. J., Norman, K. A., & Hasson, U. (2018)
Workshop on Integration of Deep Learning Theories, NeurIPS.
poster,
paper,
code,
tutorial
Modeling hippocampal-cortical dynamics during event processing
Lu, Q., Hasson, U., & Norman, K. A. (2018)
The Conference on Cognitive Computational Neuroscience (CCN)
poster,
paper
Generalized schema learning by neural networks
Chen, C., Lu, Q., Beukers, A., Baldassano, C., & Norman, K. A. (2018)
The Conference on Cognitive Computational Neuroscience (CCN)
poster,
paper
Performance optimization is insufficient for building accurate models for neural representation
Yu, J., Lu, Q., Hasson, U., Norman, K. A., & Pillow, J. W. (2018)
The Conference on Cognitive Computational Neuroscience (CCN)
poster,
paper
An interactive model accounts for ultra-rapid superordinate classification and basic-level advantage
Lu, Q., & Rogers, T. T. (2016)
The Annual Meeting of the Cognitive Science Society (CogSci)
poster,
code
Teaching a neural network to count: reinforcement learning with "social scaffolding"
Lu, Q., & McClelland, J. L. (2016)
The Neural Computation and Psychology Workshop (NCPW)
poster,
code
Iterative Lasso: An even-handed approach to whole brain multivariate pattern analysis
Cox, C. R., Lu, Q., & Rogers, T. T. (2015)
The Cognitive Neuroscience Society conference (CNS)
poster,
code