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 language | English |
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Article number | e1003775 |
Number of pages | 10 |
Journal | PLoS Computational Biology |
Volume | 10 |
Issue number | 8 |
DOIs | |
Publication status | Published - Aug 2014 |
Keywords
- Computational Biology
- Dendrites
- Ion Channels
- Models, Neurological
- Neuronal Plasticity
- Neurons
- Synapses