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Patch-clamp instruments including amplifier circuits and pipettes affect the recorded voltage signals. We hypothesized that realistic and complete in silico representation of recording instruments together with detailed morphology and biophysics of small recorded structures will reveal signal distortions and provide a tool that predicts native, instrument-free electrical signals from distorted voltage recordings. Therefore, we built a model that was verified by small axonal recordings. The model accurately recreated actual action potential (AP) measurements with typical recording artefacts and predicted the native electrical behavior. The simulations verified that recording instruments substantially filter voltage recordings. Moreover, we revealed that instrumentation directly interferes with local signal generation depending on the size of the recorded structures, which complicates the interpretation of recordings from smaller structures, such as axons. However, our model offers a straightforward approach that predicts the native waveforms of fast voltage signals and the underlying conductances even from the smallest neuronal structures.

Small Size of Recorded Neuronal Structures Confines the Accuracy in Direct Axonal Voltage Measurements