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Solomon, S.H., Kay, K., & Schapiro, A.C. Semantic plasticity across timescales in the human brain. [bioRxiv]

Smith, C.M., Thompson-Schill, S.L., & Schapiro, A.C. Rapid learning of temporal dependencies at multiple timescales. [bioRxiv]

Tandoc, M.C., Dong, C.V., & Schapiro, A.C. Object feature memory is distorted by category structure. [PsyArXiv]

Zhou, Z., Kahana, M., J., Schapiro, A.C. Replay as context-driven memory reactivation. [bioRxiv]


Siefert, E.M., Uppuluri, S., Mu. J., Tandoc, M.C., Antony, J.W., & Schapiro, A.C. (2024). Memory reactivation during sleep does not act holistically on object memory. Journal of Neuroscience. [DOI]

Solomon, S.H. & Schapiro, A.C. (2024). Structure shapes the representation of a novel category. Journal of Experimental Psychology: Learning, Memory, and Cognition. [DOI

APA Editor’s Choice article

Mylonas, D., Schapiro, A.C., Verfaellie, M., Baxter, B., Vangel, M., Stickgold, R., & Manoach, D.S. (2024). Maintenance of procedural motor memory across brief rest periods requires the hippocampus. Journal of Neuroscience. [PDF]


Sucevic, J. & Schapiro, A.C. (2023). A neural network model of hippocampal contributions to category learning. eLife. [DOI]

Zhou, Z., Yeung, G., & Schapiro, A.C. (2023). Self-recovery of memory via generative replay. NeurIPS Workshop MemARI. [arXiv]

Zhou, Z., Singh, D., Tandoc, M.C., Schapiro, A.C. (2023). Building integrated representations through interleaved learning.  Journal of Experimental Psychology: General. [PDF]

Larson, O., Schapiro, A.C., & Gehrman, P.R. (2023). Effect of sleep manipulations on intrusive memories after exposure to an experimental analogue trauma: A meta-analytic review. Sleep Medicine Reviews. [PDF]


Singh, D., Norman, K.A., Schapiro, A.C. (2022). A model of autonomous interactions between hippocampus and neocortex driving sleep-dependent memory consolidation. Proceedings of the National Academy of Sciences. [PDF]

Plate, R. C., Schapiro, A., & Waller, R. (2022). Emotional faces facilitate statistical learning. Affective Science. [PDF]

Pudhiyidath, A., Morton, N.W., Viveros Duran, R., Schapiro, A.C., Momennejad, I.,  Hinojosa-Rowland, D.M., Molitor, R.J., & Preston, A.R. (2022). Representations of temporal community structure in hippocampus and precuneus predict inductive reasoning decisions. Journal of Cognitive Neuroscience. [PDF]

Vogelstein, et al. (2022). Prospective learning: Back to the future. [arXiv]



Tandoc, M.C., Bayda, M., Poskanzer, C., Cho, E., Cox, R., Stickgold, R., & Schapiro, A.C. (2021). Examining the effects of time of day and sleep on generalization. PLOS One. [DOI]

Cowan E.T., Schapiro, A.C., Dunsmoor, J.E., & Murty, V.P. (2021). Consolidation as an adaptive process. Psychonomic Bulletin & Review.

Zeng, T., Tompary, A., Schapiro, A. C., & Thompson-Schill, S. (2021). Tracking the relation between gist and item memory over the course of long term memory consolidation. eLife. [DOI]


Kumar, M., Michael Anderson, Antony, J., Baldassano, C., Brooks, P. P., Cai, M. B., … Norman, K. A. (2021). BrainIAK: The Brain Imaging Analysis Kit. Aperture. [PDF]


Solomon, S.H., & Schapiro, A.C. (2020). Semantic search as pattern completion across a concept. Trends in Cognitive Sciences. [PDF]

Zhou, Z., Singh, D., Tandoc, M. & Schapiro, A. C. (2020). Interleaving facilitates the rapid formation of distributed representations. Proceedings of the 42nd Annual Conference of the Cognitive Science Society.

Denis, D., Schapiro, A.C., Poskanzer, C., Bursal, V., Charron, L., Morgan, A., & Stickgold, R. (2020). Memories are selected for consolidation during sleep based on initial encoding strength: The roles of item exposure and visualization. Learning and memory. [PDF]

Karnauskas, K.B., Miller, S.L., & Schapiro, A.C. (2020). Fossil fuel combustion is driving indoor CO2 toward levels harmful to human cognition. GeoHealth. [DOI]

Ellis, C.T. , Baldassano, C., Schapiro, A.C., Cai, M.B., & Cohen, J.D. (2020). Facilitating open-science with realistic fMRI simulation: validation and application. PeerJ. [PDF]



Richards, B.A., et al. (2019). A deep learning framework for neuroscience. Nature Neuroscience. [PDF]


Schapiro, A.C., Reid, A.G., Morgan, A., Manoach, D.S., Verfaellie, M., & Stickgold, R. (2019). The hippocampus is necessary for the consolidation of a task that does not require the hippocampus for initial learning. Hippocampus. [PDF]

Antony, J.W., & Schapiro, A.C. (2019). Active and effective replay: Systems consolidation reconsidered again. Nature Reviews Neuroscience. [PDF]



Cox, R., Van Bronkhorst, M.L.V., Bayda, M., Gomillion, H., Cho, E., Parr, E., Manickas-Hill, O.P., Schapiro, A.C., & Stickgold, R. (2018). Sleep selectively stabilizes contextual aspects of negative memories. Scientific Reports. [PDF]

Schapiro, A.C., McDevitt, E.A., Rogers, T.T., Mednick, S.C., & Norman, K.A. (2018). Human hippocampal replay during rest prioritizes weakly learned information and predicts memory performance. Nature Communications. [PDF] [Data on OpenNeuro]

Cox, R., Schapiro, A.C., & Stickgold, R. (2018). Variability and stability of large-scale cortical oscillation patterns. Network Neuroscience. [PDF]


Schapiro, A.C., Turk-Browne, N.B., Botvinick, M.M., & Norman, K.A. (2017). Complementary learning systems within the hippocampus: A neural network modelling approach to reconciling episodic memory with statistical learning. Philosophical Transactions of the Royal Society B. [PDF] [Supplementary Material] [Model]

Honey, C.J., Newman, E.L., & Schapiro, A.C. (2017). Switching between internal and external modes: a multi-scale learning principle. Network Neuroscience. [PDF]

Schapiro, A.C.*, McDevitt, E.A.*, Chen, L., Norman, K.A., Mednick, S.C., & Rogers, T.T. (2017). Sleep benefits memory for semantic category structure while preserving exemplar-specific information. Scientific Reports. [PDF]

Cox, R., Schapiro, A.C., Manoach, D.S., & Stickgold, R. (2017). Individual differences in frequency and topography of slow and fast sleep spindles. Frontiers in Human Neuroscience. [DOI]




Schapiro, A.C., Turk-Browne, N.B., Norman, K.A., & Botvinick, M.M. (2016). Statistical learning of temporal community structure in the hippocampus. Hippocampus. [PDF] [Supplementary Material]


Schlichting, M.L., Guarino, K.F., Schapiro, A.C., Turk-Browne, N.B., & Preston, A.R. (2016). Hippocampal structure predicts statistical learning and associative inference abilities during development. Journal of Cognitive Neuroscience. [PDF]




Schapiro, A.C., & Turk-Browne, N.B. (2015). Statistical Learning. In: Arthur W. Toga, editor. Brain Mapping: An Encyclopedic Reference. Academic Press: Elsevier; pp. 501-506. [PDF]




Schapiro, A.C., Gregory, E., Landau, B., McCloskey, M., Turk-Browne, N.B. (2014). The necessity of the medial temporal lobe for statistical learning. Journal of Cognitive Neuroscience. [PDF]




Schapiro, A.C., Rogers, T.T., Cordova, N.I., Turk-Browne, N.B., & Botvinick, M.M. (2013). Neural representations of events arise from temporal community structure. Nature Neuroscience. [PDF] [Supplementary Material] [Data on OpenNeuro]


Schapiro, A.C., McClelland, J.L., Welbourne, S.R., Rogers, T.T., & Lambon Ralph, M.A. (2013). Why bilateral damage is worse than unilateral damage to the brain. Journal of Cognitive Neuroscience. [PDF]


Gershman, S.J., Schapiro, A.C., Hupbach, A., Norman, K.A. (2013). Neural context reinstatement predicts memory misattribution. Journal of Neuroscience. [PDF]

Diuk, C., Schapiro, A.C., Cordova, N.I., Ribas-Fernandes, J., Niv, Y., & Botvinick, M.M. (2013). Divide and conquer: Task decompositions and hierarchical reinforcement learning in humans. In Computational and Robotic Models of the Hierarchical Organization of Behavior (pp. 271-291). Springer Berlin Heidelberg. [PDF]

2012 & earlier


Schapiro, A.C., Kustner, L.V., & Turk-Browne, N.B. (2012). Shaping of object representations in the human medial temporal lobe based on temporal regularities. Current Biology. [PDF] [Supplementary Material]


Schapiro, A.C. & McClelland, J.L. (2009). A connectionist model of a continuous developmental transition in the balance scale task. Cognition. [PDF]


Thomas, M.S.C., McClelland, J.L., Richardson, F M., Schapiro, A.C., & Baughman, F. (2009). Dynamical and Connectionist Approaches to Development: Toward a Future of Mutually Beneficial Coevolution. In J.P. Spencer, M. S. C. Thomas, & J. L. McClelland, (Eds). Toward a unified theory of development: Connectionism and dynamic systems theory re-considered. New York: Oxford. [DOI]

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