Title |
Spatially Distributed Dendritic Resonance Selectively Filters Synaptic Input
|
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Published in |
PLoS Computational Biology, August 2014
|
DOI | 10.1371/journal.pcbi.1003775 |
Pubmed ID | |
Authors |
Jonathan Laudanski, Benjamin Torben-Nielsen, Idan Segev, Shihab Shamma |
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. |
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