Theta-paced flickering between place-cell maps in the hippocampus.

Nature

Kavli Institute for Systems Neuroscience and Centre for the Biology of Memory, Norwegian University of Science and Technology, Olav Kyrres gate 9, MTFS, 7489 Trondheim, Norway.

Published: September 2011

The ability to recall discrete memories is thought to depend on the formation of attractor states in recurrent neural networks. In such networks, representations can be reactivated reliably from subsets of the cues that were present when the memory was encoded, at the same time as interference from competing representations is minimized. Theoretical studies have pointed to the recurrent CA3 system of the hippocampus as a possible attractor network. Consistent with predictions from these studies, experiments have shown that place representations in CA3 and downstream CA1 tolerate small changes in the configuration of the environment but switch to uncorrelated representations when dissimilarities become larger. However, the kinetics supporting such network transitions, at the subsecond timescale, is poorly understood. Here we show in rats that instantaneous transformation of the spatial context does not change the hippocampal representation all at once but is followed by temporary bistability in the discharge activity of CA3 ensembles. Rather than sliding through a continuum of intermediate activity states, the CA3 network undergoes a short period of competitive flickering between preformed representations of the past and present environment before settling on the latter. Network flickers are extremely fast, often with complete replacement of the active ensemble from one theta cycle to the next. Within individual cycles, segregation is stronger towards the end, when firing starts to decline, pointing to the theta cycle as a temporal unit for expression of attractor states in the hippocampus. Repetition of pattern-completion processes across successive theta cycles may facilitate error correction and enhance discriminative power in the presence of weak and ambiguous input cues.

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http://dx.doi.org/10.1038/nature10439DOI Listing

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