A nonparametric electrode model for intracellular recording
Romain Brette, Zuzanna Piwkowska, Michelle Rudolph, Thierry Bal
and Alain Destexhe
Neurocomputing 70: 1597-1601, 2007.
Abstract
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.
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