Implementation of a Fast 16-Bit Dynamic Clamp Using LabVIEW-RT

• Published in: Journal of neurophysiology Vol. 91; no. 1; pp. 542 - 554
• Main Authors: Kullmann, Paul H. M, Wheeler, Diek W, Beacom, Joshua, Horn, John P
• Format: Journal Article
• Language: English
• Published: United States Am Phys Soc 01.01.2004
• Subjects: Analog-Digital Conversion; Animals; Cells, Cultured; Computer Graphics; Computer Simulation; Computer Systems - trends; Database Management Systems; Electric Conductivity; Electrophysiology - methods; Membrane Potentials - physiology; Microcomputers; Models, Neurological; Neural Conduction; Neural Networks (Computer); Neurons - physiology; Patch-Clamp Techniques - instrumentation; Patch-Clamp Techniques - methods; Software; Stochastic Processes; Synapses; Synaptic Transmission
• ISSN: 0022-3077; 1522-1598
• DOI: 10.1152/jn.00559.2003

Department of Neurobiology and Center for the Neural Basis of Cognition, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261 Submitted 10 June 2003; accepted in final form 22 September 2003 The dynamic-clamp method provides a powerful electrophysiological tool for creating virtual ionic conductances in living cells and studying their influence on membrane potential. Here we describe G-clamp, a new way to implement a dynamic clamp using the real-time version of the Lab-VIEW programming environment together with a Windows host, an embedded microprocessor that runs a real-time operating system and a multifunction data-acquisition board. The software includes descriptions of a fast voltage-dependent sodium conductance, delayed rectifier, M-type and A-type potassium conductances, and a leak conductance. The system can also read synaptic conductance waveforms from preassembled data files. These virtual conductances can be reliably implemented at speeds 43 kHz while simultaneously saving two channels of data with 16-bit precision. G-clamp also includes utilities for measuring current-voltage relations, synaptic strength, and synaptic gain. Taking an approach built on a commercially available software/hardware platform has resulted in a system that is easy to assemble and upgrade. In addition, the graphical programming structure of LabVIEW should make it relatively easy for others to adapt G-clamp for new experimental applications. Address for reprint requests and other correspondence: P.H.M. Kullmann, Dept. of Neurobiology, E 1440 Biomedical Science Tower, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261 (E-mail: pkullman{at}pitt.edu ).