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Symmetric spike timing-dependent plasticity at CA3–CA3 synapses optimizes storage and recall in autoassociative networks

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  • Rajiv K. Mishra

    (Institute of Science and Technology Austria)

  • Sooyun Kim

    (Institute of Science and Technology Austria
    Present address: Department of Physiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu Seoul, 110-799, Republic of Korea)

  • Segundo J. Guzman

    (Institute of Science and Technology Austria)

  • Peter Jonas

    (Institute of Science and Technology Austria)

Abstract

CA3–CA3 recurrent excitatory synapses are thought to play a key role in memory storage and pattern completion. Whether the plasticity properties of these synapses are consistent with their proposed network functions remains unclear. Here, we examine the properties of spike timing-dependent plasticity (STDP) at CA3–CA3 synapses. Low-frequency pairing of excitatory postsynaptic potentials (EPSPs) and action potentials (APs) induces long-term potentiation (LTP), independent of temporal order. The STDP curve is symmetric and broad (half-width ∼150 ms). Consistent with these STDP induction properties, AP–EPSP sequences lead to supralinear summation of spine [Ca2+] transients. Furthermore, afterdepolarizations (ADPs) following APs efficiently propagate into dendrites of CA3 pyramidal neurons, and EPSPs summate with dendritic ADPs. In autoassociative network models, storage and recall are more robust with symmetric than with asymmetric STDP rules. Thus, a specialized STDP induction rule allows reliable storage and recall of information in the hippocampal CA3 network.

Suggested Citation

  • Rajiv K. Mishra & Sooyun Kim & Segundo J. Guzman & Peter Jonas, 2016. "Symmetric spike timing-dependent plasticity at CA3–CA3 synapses optimizes storage and recall in autoassociative networks," Nature Communications, Nature, vol. 7(1), pages 1-11, September.
  • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms11552
    DOI: 10.1038/ncomms11552
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    Cited by:

    1. Matteo Saponati & Martin Vinck, 2023. "Sequence anticipation and spike-timing-dependent plasticity emerge from a predictive learning rule," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    2. Daniel Müller-Komorowska & Baris Kuru & Heinz Beck & Oliver Braganza, 2023. "Phase information is conserved in sparse, synchronous population-rate-codes via phase-to-rate recoding," Nature Communications, Nature, vol. 14(1), pages 1-18, December.

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