ArticleFrontiers in computational neuroscience2010
Dendritic excitability modulates dendritic information processing in a purkinje cell model.
Article in Frontiers in computational neuroscience, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 11 citations in OpenAlex.
- The 40-year history of modeling active dendrites in cerebellar Purkinje cells: emergence of the first single cell "community model".Frontiers in computational neuroscience · 2015Review
- Neuronal spike timing adaptation described with a fractional leaky integrate-and-fire model.PLoS computational biology · 2014Article
- Single-neuron criticality optimizes analog dendritic computation.Scientific reports · 2013Article
- Learning intrinsic excitability in medium spiny neurons.F1000Research · 2013Article
- The effect of neural noise on spike time precision in a detailed CA3 neuron model.Computational and mathematical methods in medicine · 2012Article
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3 authors at 1 institution in 1 country.
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Abstract
Using an electrophysiological compartmental model of a Purkinje cell we quantified the contribution of individual active dendritic currents to processing of synaptic activity from granule cells. We used mutual information as a measure to quantify the information from the total excitatory input current (I(Glu)) encoded in each dendritic current. In this context, each active current was considered an information channel. Our analyses showed that most of the information was encoded by the calcium (I(CaP)) and calcium activated potassium (I(Kc)) currents. Mutual information between I(Glu) and I(CaP) and I(Kc) was sensitive to different levels of excitatory and inhibitory synaptic activity that, at the same time, resulted in the same firing rate at the soma. Since dendritic excitability could be a mechanism to regulate information processing in neurons we quantified the changes in mutual information between I(Glu) and all Purkinje cell currents as a function of the density of dendritic Ca (g(CaP)) and Kca (g(Kc)) conductances. We extended our analysis to determine the window of temporal integration of I(Glu) by I(CaP) and I(Kc) as a function of channel density and synaptic activity. The window of information integration has a stronger dependence on increasing values of g(Kc) than on g(CaP), but at high levels of synaptic stimulation information integration is reduced to a few milliseconds. Overall, our results show that different dendritic conductances differentially encode synaptic activity and that dendritic excitability and the level of synaptic activity regulate the flow of information in dendrites.
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