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Statistical Computations Underlying the Dynamics of Memory Updating

Author(s)
Gershman, Samuel J.; Radulescu, Angela; Norman, Kenneth A.; Niv, Yael
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Abstract
Psychophysical and neurophysiological studies have suggested that memory is not simply a carbon copy of our experience: Memories are modified or new memories are formed depending on the dynamic structure of our experience, and specifically, on how gradually or abruptly the world changes. We present a statistical theory of memory formation in a dynamic environment, based on a nonparametric generalization of the switching Kalman filter. We show that this theory can qualitatively account for several psychophysical and neural phenomena, and present results of a new visual memory experiment aimed at testing the theory directly. Our experimental findings suggest that humans can use temporal discontinuities in the structure of the environment to determine when to form new memory traces. The statistical perspective we offer provides a coherent account of the conditions under which new experience is integrated into an old memory versus forming a new memory, and shows that memory formation depends on inferences about the underlying structure of our experience.
Date issued
2014-11
URI
http://hdl.handle.net/1721.1/92504
Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Journal
PLoS Computational Biology
Publisher
Public Library of Science
Citation
Gershman, Samuel J., Angela Radulescu, Kenneth A. Norman, and Yael Niv. “Statistical Computations Underlying the Dynamics of Memory Updating.” Edited by Olaf Sporns. PLoS Comput Biol 10, no. 11 (November 6, 2014): e1003939.
Version: Final published version
ISSN
1553-7358

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