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Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks

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  • Friedemann Zenke

    (School of Computer and Communication Sciences and School of Life Sciences, Brain-Mind Institute, École Polytechnique Fédérale de Lausanne)

  • Everton J. Agnes

    (School of Computer and Communication Sciences and School of Life Sciences, Brain-Mind Institute, École Polytechnique Fédérale de Lausanne
    Instituto de Física, Universidade Federal do Rio Grande do Sul)

  • Wulfram Gerstner

    (School of Computer and Communication Sciences and School of Life Sciences, Brain-Mind Institute, École Polytechnique Fédérale de Lausanne)

Abstract

Synaptic plasticity, the putative basis of learning and memory formation, manifests in various forms and across different timescales. Here we show that the interaction of Hebbian homosynaptic plasticity with rapid non-Hebbian heterosynaptic plasticity is, when complemented with slower homeostatic changes and consolidation, sufficient for assembly formation and memory recall in a spiking recurrent network model of excitatory and inhibitory neurons. In the model, assemblies were formed during repeated sensory stimulation and characterized by strong recurrent excitatory connections. Even days after formation, and despite ongoing network activity and synaptic plasticity, memories could be recalled through selective delay activity following the brief stimulation of a subset of assembly neurons. Blocking any component of plasticity prevented stable functioning as a memory network. Our modelling results suggest that the diversity of plasticity phenomena in the brain is orchestrated towards achieving common functional goals.

Suggested Citation

  • Friedemann Zenke & Everton J. Agnes & Wulfram Gerstner, 2015. "Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks," Nature Communications, Nature, vol. 6(1), pages 1-13, November.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms7922
    DOI: 10.1038/ncomms7922
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    Cited by:

    1. Gabriel Koch Ocker & Ashok Litwin-Kumar & Brent Doiron, 2015. "Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-40, August.
    2. Douglas Feitosa Tomé & Sadra Sadeh & Claudia Clopath, 2022. "Coordinated hippocampal-thalamic-cortical communication crucial for engram dynamics underneath systems consolidation," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    3. 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.
    4. Mizusaki, Beatriz E.P. & Agnes, Everton J. & Erichsen, Rubem & Brunnet, Leonardo G., 2017. "Learning and retrieval behavior in recurrent neural networks with pre-synaptic dependent homeostatic plasticity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 279-286.

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