Literature DB >> 11759927

A methodology for achieving high-speed rates for artificial conductance injection in electrically excitable biological cells.

R J Butera1, C G Wilson, C A Delnegro, J C Smith.   

Abstract

We present a novel approach to implementing the dynamic-clamp protocol (Sharp et al., 1993), commonly used in neurophysiology and cardiac electrophysiology experiments. Our approach is based on real-time extensions to the Linux operating system. Conventional PC-based approaches have typically utilized single-cycle computational rates of 10 kHz or slower. In thispaper, we demonstrate reliable cycle-to-cycle rates as fast as 50 kHz. Our system, which we call model reference current injection (MRCI); pronounced merci is also capable of episodic logging of internal state variables and interactive manipulation of model parameters. The limiting factor in achieving high speeds was not processor speed or model complexity, but cycle jitter inherent in the CPU/motherboard performance. We demonstrate these high speeds and flexibility with two examples: 1) adding action-potential ionic currents to a mammalian neuron under whole-cell patch-clamp and 2) altering a cell's intrinsic dynamics via MRCI while simultaneously coupling it via artificial synapses to an internal computational model cell. These higher rates greatly extend the applicability of this technique to the study of fast electrophysiological currents such fast a currents and fast excitatory/inhibitory synapses.

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Year:  2001        PMID: 11759927     DOI: 10.1109/10.966605

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  14 in total

1.  Real-time experiment interface for biological control applications.

Authors:  Risa J Lin; Jonathan Bettencourt; John Wha Ite; David J Christini; Robert J Butera
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2010

2.  An FPGA-based approach to high-speed simulation of conductance-based neuron models.

Authors:  E L Graas; E A Brown; Robert H Lee
Journal:  Neuroinformatics       Date:  2004

Review 3.  Dynamic clamp: a powerful tool in cardiac electrophysiology.

Authors:  Ronald Wilders
Journal:  J Physiol       Date:  2006-07-27       Impact factor: 5.182

4.  Effects of imperfect dynamic clamp: computational and experimental results.

Authors:  Jonathan C Bettencourt; Kyle P Lillis; Laura R Stupin; John A White
Journal:  J Neurosci Methods       Date:  2007-10-24       Impact factor: 2.390

5.  Functional phase response curves: a method for understanding synchronization of adapting neurons.

Authors:  Jianxia Cui; Carmen C Canavier; Robert J Butera
Journal:  J Neurophysiol       Date:  2009-05-06       Impact factor: 2.714

6.  Real-time kinetic modeling of voltage-gated ion channels using dynamic clamp.

Authors:  Lorin S Milescu; Tadashi Yamanishi; Krzysztof Ptak; Murtaza Z Mogri; Jeffrey C Smith
Journal:  Biophys J       Date:  2008-03-28       Impact factor: 4.033

Review 7.  The past, present, and future of real-time control in cellular electrophysiology.

Authors:  Jennifer A Bauer; Katherine M Lambert; John A White
Journal:  IEEE Trans Biomed Eng       Date:  2014-04-01       Impact factor: 4.538

8.  MATLAB implementation of a dynamic clamp with bandwidth of >125 kHz capable of generating I Na at 37 °C.

Authors:  Chris Clausen; Virginijus Valiunas; Peter R Brink; Ira S Cohen
Journal:  Pflugers Arch       Date:  2012-12-09       Impact factor: 3.657

9.  NeuReal: an interactive simulation system for implementing artificial dendrites and large hybrid networks.

Authors:  Stuart W Hughes; Magor Lorincz; David W Cope; Vincenzo Crunelli
Journal:  J Neurosci Methods       Date:  2007-11-01       Impact factor: 2.390

10.  Causes of transient instabilities in the dynamic clamp.

Authors:  Amanda J Preyer; Robert J Butera
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2009-02-18       Impact factor: 3.802

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