Anna C. Schapiro

Affiliations: 
Princeton University, Princeton, NJ 
Area:
learning, memory, sleep
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"Anna Schapiro"
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SNBCP

Parents

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James L. McClelland research assistant 2006-2009 Princeton
Matthew M. Botvinick grad student 2009-2014 Princeton
 (Learning and representation of recent structure in the environment: Behavioral, neuroimaging, and computational investigations.)
Kenneth A. Norman grad student 2009-2014 Princeton
 (Learning and representation of recent structure in the environment: Behavioral, neuroimaging, and computational investigations.)
Timothy T. Rogers grad student 2009-2014 Princeton
Nicholas B. Turk-Browne grad student 2009-2014 Princeton
Robert Stickgold post-doc 2015- Harvard Medical School

Children

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Zhenglong Zhou grad student 2019- Penn
BETA: Related publications

Publications

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Ellis CT, Baldassano C, Schapiro AC, et al. (2020) Facilitating open-science with realistic fMRI simulation: validation and application. Peerj. 8: e8564
Richards BA, Lillicrap TP, Beaudoin P, et al. (2019) A deep learning framework for neuroscience. Nature Neuroscience. 22: 1761-1770
Schapiro AC, Reid AG, Morgan A, et al. (2019) The hippocampus is necessary for the consolidation of a task that does not require the hippocampus for initial learning. Hippocampus
Schapiro AC, McDevitt EA, Rogers TT, et al. (2018) Human hippocampal replay during rest prioritizes weakly learned information and predicts memory performance. Nature Communications. 9: 3920
Honey CJ, Newman EL, Schapiro AC. (2018) Switching between internal and external modes: A multiscale learning principle. Network Neuroscience (Cambridge, Mass.). 1: 339-356
Schapiro AC, McDevitt EA, Chen L, et al. (2017) Sleep Benefits Memory for Semantic Category Structure While Preserving Exemplar-Specific Information. Scientific Reports. 7: 14869
Cox R, Schapiro AC, Manoach DS, et al. (2017) Individual Differences in Frequency and Topography of Slow and Fast Sleep Spindles. Frontiers in Human Neuroscience. 11: 433
Schapiro AC, Turk-Browne NB, Botvinick MM, et al. (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 of London. Series B, Biological Sciences. 372
Schapiro A, McDevitt E, Chen L, et al. (2017) 0225 SLEEP BENEFITS MEMORY FOR SEMANTIC CATEGORY STRUCTURE WHILE PRESERVING INDIVIDUAL EXEMPLARS Sleep. 40: A83-A83
Schlichting ML, Guarino KF, Schapiro AC, et al. (2016) Hippocampal Structure Predicts Statistical Learning and Associative Inference Abilities during Development. Journal of Cognitive Neuroscience. 1-15
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