Encyclopedia of Computational Neuroscience

Living Edition
| Editors: Dieter Jaeger, Ranu Jung

Dynamic Clamp Technique

  • Thomas Nowotny
  • Pablo Varona
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7320-6_126-2


Dynamic clamp is an electrophysiological technique for introducing simulated electrical components into biological cells using a real-time closed loop between the cell and a computer or another electronic device. Classic dynamic clamp protocols build a voltage-dependent current injection cycle to implement artificial membrane or synaptic conductances in the cell membrane of biological neurons. These protocols are employed to assess a large variety of neuronal computational properties and are widely applied for studying the physiology of neural systems at the cellular and circuit levels.

Detailed Description


The use of closed-loop feedback interactions with living neurons for observation and control purposes goes back to the beginnings of electrophysiology when the voltage clamp technique was developed (Marmont 1949; Cole 1955). The voltage clamp technique measures currents across the membrane of excitable cells while holding the membrane potential at a constant...


Current Clamp Synaptic Conductance Voltage Clamp Technique Dynamic Clamp Hybrid Circuit 
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  1. Brette R, Piwkowska Z, Monier C, Rudolph-Lilith M, Fournier J, Levy M, Frégnac Y, Bal T, Destexhe A (2008) High-resolution intracellular recordings using a real-time computational model of the electrode. Neuron 59:379–391PubMedCrossRefGoogle Scholar
  2. Butera RJ, Wilson CG, Delnegro CA, Smith JC (2001) A methodology for achieving high-speed rates for artificial conductance injection in electrically excitable biological cells. IEEE Trans Biomed Eng 48:1460–1470PubMedCrossRefGoogle Scholar
  3. Chamorro P, Muñiz C, Levi R, Arroyo D, Rodríguez FB, Varona P (2012) Generalization of the dynamic clamp concept in neurophysiology and behavior. PLoS ONE 7:e40887PubMedCentralPubMedCrossRefGoogle Scholar
  4. Cole KS (1955) Ions, potentials and the nerve impulse. In: Shedlovsky T (ed) Electrochemistry in biology and medicine. Wiley, New York, pp 121–140Google Scholar
  5. Destexhe A, Bal T (eds) (2009) Dynamic-clamp: from principles to applications. Springer, New YorkGoogle Scholar
  6. Dorval AD, Christini DJ, White JA (2001) Real-time linux dynamic clamp: a fast and flexible way to construct virtual ion channels in living cells. Ann Biomed Eng 29:897–907PubMedCrossRefGoogle Scholar
  7. Economo MN, Fernandez FR, White JA (2010) Dynamic clamp: alteration of response properties and creation of virtual realities in neurophysiology. J Neurosci 30:2407–2413PubMedCentralPubMedCrossRefGoogle Scholar
  8. Fernandez-Vargas J, Pfaff HU, Rodriguez FB, Varona P (2013) Assisted closed-loop optimization of SSVEP-BCI efficiency. Front Neural Circuits 7:27PubMedCentralPubMedCrossRefGoogle Scholar
  9. Goaillard J-M, Marder E (2006) Dynamic clamp analyses of cardiac, endocrine, and neural function. Physiology (Bethesda) 21:197–207CrossRefGoogle Scholar
  10. Kemenes I, Marra V, Crossley M, Samu D, Staras K, Kemenes G, Nowotny T (2011) Dynamic clamp with StdpC software. Nat Protoc 6:405–417PubMedCentralPubMedCrossRefGoogle Scholar
  11. Kullmann PHM, Wheeler DW, Beacom J, Horn JP (2004) Implementation of a fast 16-Bit dynamic clamp using LabVIEW-RT. J Neurophysiol 91:542–554PubMedCrossRefGoogle Scholar
  12. Lin RJ, Bettencourt J, Ite JW, Christini DJ, Butera RJ (2010) Real-time experiment interface for biological control applications. Conf Proc IEEE Eng Med Biol Soc 2010:4160–4163PubMedCentralPubMedGoogle Scholar
  13. Marmont G (1949) Studies on the axon membrane; a new method. J Cell Physiol 34:351–382PubMedCrossRefGoogle Scholar
  14. Muniz C, Rodriguez FB, Varona P (2009) RTBiomanager: a software platform to expand the applications of real-time technology in neuroscience. BMC Neurosci 10:P49CrossRefGoogle Scholar
  15. Nowotny T, Szucs A, Pinto RD, Selverston AI (2006) StdpC: a modern dynamic clamp. J Neurosci Methods 158:287–299PubMedCrossRefGoogle Scholar
  16. Pinto RD, Elson RC, Szücs A, Rabinovich MI, Selverston AI, Abarbanel HD (2001) Extended dynamic clamp: controlling up to four neurons using a single desktop computer and interface. J Neurosci Methods 108:39–48PubMedCrossRefGoogle Scholar
  17. Prinz AA, Abbott LF, Marder E (2004) The dynamic clamp comes of age. Trends Neurosci 27:218PubMedCrossRefGoogle Scholar
  18. Robinson HP, Kawai N (1993) Injection of digitally synthesized synaptic conductance transients to measure the integrative properties of neurons. J Neurosci Methods 49:157PubMedCrossRefGoogle Scholar
  19. Samu D, Marra V, Kemenes I, Crossley M, Kemenes G, Staras K, Nowotny T (2012) Single electrode dynamic clamp with StdpC. J Neurosci Meth 211:11–21CrossRefGoogle Scholar
  20. Sharp AA, O’Neil MB, Abbott LF, Marder E (1993) Dynamic clamp: computer-generated conductances in real neurons. J Neurophysiol 69:992–995PubMedGoogle Scholar
  21. Tan RC, Joyner RW (1990) Electrotonic influences on action potentials from isolated ventricular cells. Circ Res 67:1071–1081PubMedCrossRefGoogle Scholar
  22. Wallach A, Eytan D, Gal A, Zrenner C, Marom S (2011) Neuronal response clamp. Front Neuroengineer 4:3Google Scholar
  23. Yarom Y (1991) Rhythmogenesis in a hybrid system-interconnecting an olivary neuron to an analog network of coupled oscillators. Neuroscience 44:263–275PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Centre for Computational Neuroscience and Robotics, School of Engineering and InformaticsUniversity of SussexFalmer, BrightonUK
  2. 2.Departamento de Ingenieria InformaticaUniversidad Autónoma de MadridMadridSpain