Literature DB >> 11764320

Real-Time linux dynamic clamp: a fast and flexible way to construct virtual ion channels in living cells.

A D Dorval1, D J Christini, J A White.   

Abstract

We describe a system for real-time control of biological and other experiments. This device, based around the Real-Time Linux operating system, was tested specifically in the context of dynamic clamping, a demanding real-time task in which a computational system mimics the effects of nonlinear membrane conductances in living cells. The system is fast enough to represent dozens of nonlinear conductances in real time at clock rates well above 10 kHz. Conductances can be represented in deterministic form, or more accurately as discrete collections of stochastically gating ion channels. Tests were performed using a variety of complex models of nonlinear membrane mechanisms in excitable cells, including simulations of spatially extended excitable structures, and multiple interacting cells. Only in extreme cases does the computational load interfere with high-speed "hard" real-time processing (i.e., real-time processing that never falters). Freely available on the worldwide web, this experimental control system combines good performance. immense flexibility, low cost, and reasonable ease of use. It is easily adapted to any task involving real-time control, and excels in particular for applications requiring complex control algorithms that must operate at speeds over 1 kHz.

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Year:  2001        PMID: 11764320     DOI: 10.1114/1.1408929

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  59 in total

1.  Synchronization of strongly coupled excitatory neurons: relating network behavior to biophysics.

Authors:  Corey D Acker; Nancy Kopell; John A White
Journal:  J Comput Neurosci       Date:  2003 Jul-Aug       Impact factor: 1.621

2.  Detecting effective connectivity in networks of coupled neuronal oscillators.

Authors:  Erin R Boykin; Pramod P Khargonekar; Paul R Carney; William O Ogle; Sachin S Talathi
Journal:  J Comput Neurosci       Date:  2011-10-14       Impact factor: 1.621

3.  Metabolic cost as a unifying principle governing neuronal biophysics.

Authors:  Andrea Hasenstaub; Stephani Otte; Edward Callaway; Terrence J Sejnowski
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-23       Impact factor: 11.205

4.  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

5.  The variance of phase-resetting curves.

Authors:  G Bard Ermentrout; Bryce Beverlin; Todd Troyer; Theoden I Netoff
Journal:  J Comput Neurosci       Date:  2011-01-05       Impact factor: 1.621

6.  Engineering the synchronization of neuron action potentials using global time-delayed feedback stimulation.

Authors:  Craig G Rusin; Sarah E Johnson; Jaideep Kapur; John L Hudson
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2011-12-06

7.  Feedback control of variability in the cycle period of a central pattern generator.

Authors:  Ryan M Hooper; Ruben A Tikidji-Hamburyan; Carmen C Canavier; Astrid A Prinz
Journal:  J Neurophysiol       Date:  2015-09-02       Impact factor: 2.714

8.  Reduction of spike afterdepolarization by increased leak conductance alters interspike interval variability.

Authors:  Fernando R Fernandez; John A White
Journal:  J Neurosci       Date:  2009-01-28       Impact factor: 6.167

9.  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

10.  An intrinsic neuronal oscillator underlies dopaminergic neuron bursting.

Authors:  Christopher A Deister; Mark A Teagarden; Charles J Wilson; Carlos A Paladini
Journal:  J Neurosci       Date:  2009-12-16       Impact factor: 6.167

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