A non-parametric electrode model for intracellular recording.

Romain Brette , Zuzana Piwkowska (1, 2) , Michael Rudolph (1, 2) , Thierry Bal (1, 2) , Alain Destexhe (1, 2)

1 UNIC - Unité de neurosciences intégratives et computationnelles
2 INAF - Institut de Neurobiologie Alfred Fessard

We present a new way to model the response of an electrode to an injected current. The electrode is represented by an unknown complex linear circuit, characterized by a kernel which we determine by injecting a noisy current. We show both in simulations and experiments that, when applied to a full recording setup (including acquisition board and amplifier), the method captures not only the characteristics of the electrode, but also those of all the devices between the computer and the tip of the electrode, including filters and the capacitance neutralization circuit on the amplifier. Simulations show that the method allows correct predictions of the response of complex electrode models. Finally, we successfully apply the technique to challenging intracellular recording situations in which the voltage across the electrode during injection needs to be subtracted from the recording, in particular conductance injection with the dynamic clamp protocol. We show in numerical simulations and confirm with experiments that the method performs well in cases when both bridge recording and recording in discontinuous mode (DCC) exhibit artefacts.

Domaines: Neurosciences [q-bio.NC]

Romain Brette, Zuzana Piwkowska, Michael Rudolph, Thierry Bal, Alain Destexhe. A non-parametric electrode model for intracellular recording.. Proceedings of the 15th Annual Computational Neuroscience Meeting, 2006, Edinburgh, United Kingdom. pp.38. ⟨hal-00380035⟩