Spatially distributed dendritic resonance selectively filters synaptic input

Jonathan Laudanski, Ben Torben-Nielsen, Idan Segev, Shihab Shamma

    Research output: Contribution to journalArticlepeer-review

    12 Citations (Scopus)
    64 Downloads (Pure)

    Abstract

    An important task performed by a neuron is the selection of relevant inputs from among thousands of synapses impinging on the dendritic tree. Synaptic plasticity enables this by strenghtening a subset of synapses that are, presumably, functionally relevant to the neuron. A different selection mechanism exploits the resonance of the dendritic membranes to preferentially filter synaptic inputs based on their temporal rates. A widely held view is that a neuron has one resonant frequency and thus can pass through one rate. Here we demonstrate through mathematical analyses and numerical simulations that dendritic resonance is inevitably a spatially distributed property; and therefore the resonance frequency varies along the dendrites, and thus endows neurons with a powerful spatiotemporal selection mechanism that is sensitive both to the dendritic location and the temporal structure of the incoming synaptic inputs.

    Original languageEnglish
    Article numbere1003775
    Number of pages10
    JournalPLoS Computational Biology
    Volume10
    Issue number8
    DOIs
    Publication statusPublished - Aug 2014

    Keywords

    • Computational Biology
    • Dendrites
    • Ion Channels
    • Models, Neurological
    • Neuronal Plasticity
    • Neurons
    • Synapses

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