Real-time experimental control in cellular neurophysiology

Abstract

Electrophysiologists study neuronal input-output behavior by approximating synaptic input with a predetermined current waveform. In living tissue however, a synaptic event induces a conductance change in the neuronal membrane, and the current passed through that conductance is not predetermined, but a function of the continuously changing membrane potential. Using high frequency feedback, the dynamic clamp technique allows experimentalists to introduce conductance changes in living neurons. Using a dynamic clamp, we find that current steps elicit greater membrane potential variance than more natural conductance steps. In addition, reliability profiles to the same pseudo-synaptic waveform change when currents are substituted for conductances. Hence, under certain conditions current input is an invalid approximation of conductance changes, and dynamic clamp should be used to examine neuronal input-output behaviors. Furthermore, dynamic clamp can be used as a control tool for other neuronal experiments. We demonstrate the use of a dynamic clamp as a signal detector, a frequency control device, and as a way to connect living cells to virtual networks. Thus we show that the dynamic clamp technique is a critical tool not only useful for mapping neuronal input-output function, but in a broader context of neuronal control.