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Analysis of Hippocampal Memory Replay Using Neural Population Decoding

Part of the Neuromethods book series (NM,volume 67)

Abstract

Large-scale recording of neural activity in waking animals provides us with a window on computations performed in the brain during behavior. In order to better understand these computations, population decoding techniques are used to study what information about the external environment is represented by neural ensemble activity. Decoding approaches are especially appealing when neural activity does not reflect the actual sensory experience or motor output, but is generated by internal cognitive processes, such as planning, memory, and decision making. This chapter describes the background of Bayesian decoding and outlines the general procedures for decoding ensemble activity during cognitive processes. The power of this method is demonstrated by applying it to recordings of hippocampal place cell activity in order to identify and characterize hippocampal memory replay.

Key words

  • Neural ensemble recording
  • Spike train decoding
  • Hippocampus
  • Memory replay

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  • DOI: 10.1007/7657_2011_8
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Acknowledgments

I would like to thank Audrey Chang, Zhe Chen and Matt Wilson for their comments on an earlier version of this manuscript. Many thanks to Tom Davidson for the discussions about the methods presented in this chapter and for generously providing me with hippocampal unit data to prepare some of the figures.

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Kloosterman, F. (2011). Analysis of Hippocampal Memory Replay Using Neural Population Decoding. In: Fellin, T., Halassa, M. (eds) Neuronal Network Analysis. Neuromethods, vol 67. Humana Press. https://doi.org/10.1007/7657_2011_8

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  • DOI: https://doi.org/10.1007/7657_2011_8

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