Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks
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DOI: 10.1038/s41467-017-01109-y
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Cited by:
- Stefano Recanatesi & Gabriel Koch Ocker & Michael A Buice & Eric Shea-Brown, 2019. "Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity," PLOS Computational Biology, Public Library of Science, vol. 15(7), pages 1-29, July.
- Louis Kang & Taro Toyoizumi, 2024. "Distinguishing examples while building concepts in hippocampal and artificial networks," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
- Ting-Feng Lin & Silas E. Busch & Christian Hansel, 2024. "Intrinsic and synaptic determinants of receptive field plasticity in Purkinje cells of the mouse cerebellum," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
- A. Barri & M. T. Wiechert & M. Jazayeri & D. A. DiGregorio, 2022. "Synaptic basis of a sub-second representation of time in a neural circuit model," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
- 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.
- Zhiwei Xu & Erez Geron & Luis M. Pérez-Cuesta & Yang Bai & Wen-Biao Gan, 2023. "Generalized extinction of fear memory depends on co-allocation of synaptic plasticity in dendrites," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
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