Parameterization of neuronal membrane conductance models relies on data acquired from current clamp (CC) or voltage clamp (VC) recordings. Although the CC approach provides key information on a neuron\'s firing properties, it is often difficult to disentangle the influence of multiple conductances that contribute to the excitation properties of a real neuron. Isolation of a single conductance using pharmacological agents or heterologous expression simplifies analysis but requires extensive VC evaluation to explore the complete state behavior of the channel of interest.
We present an improved parameterization approach that uses data derived from dynamic action potential clamp (DAPC) recordings to extract conductance equation parameters. We demonstrate the utility of the approach by applying it to the standard Hodgkin-Huxley conductance model although other conductance models could be easily incorporated as well.
Using a fully simulated setup we show that, with as few as five action potentials previously recorded in DAPC mode, sodium conductance equation parameters can be determined with average parameter errors of less than 4% while action potential firing accuracy approaches 100%. In real DAPC experiments, we show that by \"training\" our model with five or fewer action potentials, subsequent firing lasting for several seconds could be predicted with ˜96% mean firing rate accuracy and 94% temporal overlap accuracy.
Our DAPC-based approach surpasses the accuracy of VC-based approaches for extracting conductance equation parameters with a significantly reduced temporal overhead.
DAPC-based approach will facilitate the rapid and systematic characterization of neuronal channelopathies.

De novo variants in SCN2A developmental and epileptic encephalopathy (DEE) show distinctive genotype-phenotype correlations. The two most recurrent SCN2A variants in DEE, R1882Q and R853Q, are associated with different ages and seizure types at onset. R1882Q presents on day 1 of life with focal seizures, while infantile spasms is the dominant seizure type seen in R853Q cases, presenting at a median age of 8 months. Voltage clamp, which characterizes the functional properties of ion channels, predicted gain-of-function for R1882Q and loss-of-function for R853Q. Dynamic action potential clamp, that we implement here as a method for modeling neurophysiological consequences of a given epilepsy variant, predicted that the R1882Q variant would cause a dramatic increase in firing, whereas the R853Q variant would cause a marked reduction in action potential firing. Dynamic clamp was also able to functionally separate the L1563V variant, seen in benign familial neonatal-infantile seizures from R1882Q, seen in DEE, suggesting a diagnostic potential for this type of analysis. Overall, the study shows a strong correlation between clinical phenotype, SCN2A genotype, and functional modeling. Dynamic clamp is well positioned to impact our understanding of pathomechanisms and for development of disease mechanism-targeted therapies in genetic epilepsy.