Dynamic observer: ion channel measurement beyond voltage clamp
© Drix and Nowotny; licensee BioMed Central Ltd. 2011
Published: 18 July 2011
To date, the gold standard for characterizing neurons and assessing the action of drugs on them are voltage clamp protocols in patch clamp recordings . However, it is now clear that the classical procedure, where measurements performed using constant voltage steps and channel blockers are averaged over several cells, does not typically allow the construction of accurate Hodgkin-Huxley type models . Here we propose to go beyond the classical procedure and rely on optimized stimulation patterns to isolate the effect of different ion channels.
We represent stimulation patterns as clamped cubic splines defined by a number of support points. Cubic splines can approximate steps or sinusoids, as well as arbitrary shapes; clamped splines avoid discontinuities around the endpoints. To measure the degree to which a given pattern can isolate the contribution of one channel, a reference neuron is detuned in two different ways. The first detuned neuron has one set of parameters increased by a certain factor, while in the second a different set of parameters is similarly detuned. The separation power of a stimulation pattern for these two sets of parameters is then defined as the ratio of the divergence factors of the two detuned neurons, which are defined as the sum of squared errors between the reference and detuned trans-membrane currents. Optimal patterns are constructed by adjusting the support points to maximize this ratio, typically through a combination of a genetic algorithm for exploring the search space, and gradient descent for fine-tuning.
To conclude, there clearly is a potential for isolating the effect of various parameters using optimized voltage clamp stimulation patterns. The offline process presented here is a first step towards a fully-automated online fitting method capable of extracting a model from a single cell in a patch clamp protocol. Such a method will be able to select the most informative stimulation pattern at any point of the fitting process and thus work incrementally to refine the fitting of these parameters which are less clearly dissociable from the others.
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