ArticlePLoS computational biology2010
Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Lateral entorhinal cortex inputs modulate hippocampal dendritic excitability by recruiting a local disinhibitory microcircuit.Cell reports · 2023Article
- Place fields of single spikes in hippocampus involve Kcnq3 channel-dependent entrainment of complex spike bursts.Nature communications · 2021Article
- Spatiotemporal model of tripartite synapse with perinodal astrocytic process.Journal of computational neuroscience · 2020Article
- Article
- A simulation study on the effects of dendritic morphology on layer V prefrontal pyramidal cell firing behavior.Frontiers in cellular neuroscience · 2014Article
- Perspectives for computational modeling of cell replacement for neurological disorders.Frontiers in computational neuroscience · 2013Article
- Induction and modulation of persistent activity in a layer V PFC microcircuit model.Frontiers in neural circuits · 2013Article
- The energy cost of action potential propagation in dopamine neurons: clues to susceptibility in Parkinson's disease.Frontiers in computational neuroscience · 2013Article
- Predictive features of persistent activity emergence in regular spiking and intrinsic bursting model neurons.PLoS computational biology · 2012Article
- Distinguishing Linear vs. Non-Linear Integration in CA1 Radial Oblique Dendrites: It's about Time.Frontiers in computational neuroscience · 2011Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code.
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