Experiment-Modelling Cycling with Populations of Multi-compartment Models: Application to Hippocampal Interneurons
Understanding how neurons operate involves investigating how their complements of ion channels interact dynamically along the extent of their somatodendritic trees to produce spiking output appropriate to the cell type in question. This can be approached using experiments where individual ion channel activity is manipulated. However, a large body of experimental and theoretical work has demonstrated that a single neuron may dynamically alter its intrinsic ion channel expression profile in order to maintain output that is required for it to perform its functional role within the network that it is embedded. To appreciate this, a clear sense of the cellular functional role would be required, and this is not usually known. More typically, cellular output for an identified cell type can be characterized and captured in models with different complements of intrinsic properties. In this chapter we propose a cycling approach using experimental data as constraints for building populations of multi-compartment models with a range of ion channel expression patterns that underlie cell-type appropriate model output. These populations or databases can be analyzed to develop predictions regarding the intrinsic property balances for the cell type in question and for the proposed function. Predicted balances and functions can be examined experimentally.
KeywordsInhibitory cell Ensemble modelling Ion channel co-regulation O-LM interneuron Theta rhythm h-channels Dendrites
A subfield in the mammalian hippocampus, referring to “Cornu Ammonis 1,” or the first region in “Amun’s horns,” a name for the hippocampus coined by de Garengeot in the mid-eighteenth century.
Oriens/lacunosum-moleculare; the abbreviation of a type of interneuron in hippocampal CA1/CA3 with soma in stratum oriens and axons projecting to stratum lacunosum/moleculare.
An open-source MATLAB toolbox that provides an object-oriented framework for assembling and manipulating databases of electrophysiological data, whether from computational models or experiment.
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