A Simple Method to Simultaneously Track the Numbers of Expressed Channel Proteins in a Neuron
Neurons express particular combinations of ion channels that confer specific membrane properties. Although many ion channels have been characterized the functional implications of particular combinations and the regulatory mechanisms controlling their expression are often difficult to assess in vivo and remain unclear. We introduce a method, Reverse Channel Identification (RCI), which enables the numbers and mixture of active ion channels to be determined. We devised a current-clamp stimulus that allows each channels characteristics to be determined. We test our method on simulated data from a computational model of squid giant axons and from fly photoreceptors to identify both the numbers of ion channels and their specific ratios. Our simulations suggest that RCI is a robust method that will allow identification of ion channel number and mixture in vivo.
KeywordsVirtual Channel Single Channel Conductance Channel Density Squid Giant Axon Channel Open Probability
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