Preprints​

Solomon, S.H. & Schapiro, A.C. Structure shapes the representation of a novel category. [PsyArXiv]

Zhou, Z., Singh, D., Tandoc, M.C., Schapiro, A.C. Distributed representations for human inference.[bioRxiv]

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

Plate, R. C., Schapiro, A., & Waller, R. Emotional congruency facilitates statistical learning. [PsyArXiv]

2021

 

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. (in press). BrainIAK: The Brain Imaging Analysis Kit. Aperture. [OSF]

2020

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]

2019

 

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]

2018

 

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]

2017

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]

 

2016

 

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]

 

2015

 

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]

 

2014

 

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]

 

2013

 

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]