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• W2913906720 abstract "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." @default.
• W2913906720 created "2019-02-21" @default.
• W2913906720 creator A5060634869 @default.
• W2913906720 creator A5071583189 @default.
• W2913906720 date "2018-01-01" @default.
• W2913906720 modified "2023-09-23" @default.
• W2913906720 title "Experiment-Modelling Cycling with Populations of Multi-compartment Models: Application to Hippocampal Interneurons" @default.
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• W2913906720 doi "https://doi.org/10.1007/978-3-319-99103-0_25" @default.
• W2913906720 hasPublicationYear "2018" @default.
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