High-Resolution Intracellular Recordings Using a Real-Time Computational Model of the Electrode

Intracellular recordings of neuronal membrane potential are a central tool in neurophysiology. In many situations, especially in vivo, the traditional limitation of such recordings is the high electrode resistance and capacitance, which may cause significant measurement errors during current injection. We introduce a computer-aided technique, Active Electrode Compensation (AEC), based on a digital model of the electrode interfaced in real time with the electrophysiological setup. The characteristics of this model are first estimated using white noise current injection. The electrode and membrane contribution are digitally separated, and the recording is then made by online subtraction of the electrode contribution. Tests performed in vitro and in vivo demonstrate that AEC enables high-frequency recordings in demanding conditions, such as injection of conductance noise in dynamic-clamp mode, not feasible with a single high-resistance electrode until now. AEC should be particularly useful to characterize fast neuronal phenomena intracellularly in vivo.

[1]  W. Klaus,et al.  Switched single-electrode voltage-clamp amplifiers allow precise measurement of gap junction conductance. , 1999, American journal of physiology. Cell physiology.

[2]  Nicholas T. Carnevale,et al.  The NEURON Simulation Environment , 1997, Neural Computation.

[3]  O D Creutzfeldt,et al.  Whole cell recording and conductance measurements in cat visual cortex in-vivo. , 1991, Neuroreport.

[4]  D. Contreras,et al.  Cellular mechanisms of suppressive interactions between somatosensory responses in vivo. , 2007, Journal of neurophysiology.

[5]  R. D. Purves,et al.  Microelectrode methods for intracellular recording and ionophoresis , 1981 .

[6]  J. Deuchars,et al.  Synaptic interactions in neocortical local circuits: dual intracellular recordings in vitro. , 1997, Cerebral cortex.

[7]  T. Sejnowski,et al.  Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons , 2001, Neuroscience.

[8]  Johannes J. Letzkus,et al.  Dendritic patch-clamp recording , 2006, Nature Protocols.

[9]  M. V. Thomas,et al.  Microelectrode amplifier with improved method of input-capacitance neutralisation , 1977, Medical and Biological Engineering and Computing.

[10]  B. Lindemann,et al.  Design of a fast voltage clamp for biological membranes, using discontinuous feedback. , 1974, The Review of scientific instruments.

[11]  R. Hedrich,et al.  Discontinuous single electrode voltage-clamp measurements: assessment of clamp accuracy in Vicia faba guard cells. , 2001, Journal of experimental botany.

[12]  William H. Press,et al.  Book-Review - Numerical Recipes in Pascal - the Art of Scientific Computing , 1989 .

[13]  Michael Rudolph,et al.  Extracting Information from the Power Spectrum of Synaptic Noise , 2004, Journal of Computational Neuroscience.

[14]  Eve Marder,et al.  The dynamic clamp: artificial conductances in biological neurons , 1993, Trends in Neurosciences.

[15]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[16]  Mikko Juusola,et al.  Stimulus History Reliably Shapes Action Potential Waveforms of Cortical Neurons , 2005, The Journal of Neuroscience.

[17]  A. Zador,et al.  Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex , 2003, Nature.

[18]  Ohad Ben-Shahar,et al.  Stochastic Emergence of Repeating Cortical Motifs in Spontaneous Membrane Potential Fluctuations In Vivo , 2007, Neuron.

[19]  Y. Frégnac,et al.  In vitro and in vivo measures of evoked excitatory and inhibitory conductance dynamics in sensory cortices , 2008, Journal of Neuroscience Methods.

[20]  D. McCormick,et al.  Modulation of intracortical synaptic potentials by presynaptic somatic membrane potential , 2006, Nature.

[21]  D. Contreras,et al.  Stimulus-Dependent Changes in Spike Threshold Enhance Feature Selectivity in Rat Barrel Cortex Neurons , 2005, The Journal of Neuroscience.

[22]  A. Destexhe,et al.  A method to estimate synaptic conductances from membrane potential fluctuations. , 2004, Journal of neurophysiology.

[23]  B. Sakmann,et al.  In vivo, low-resistance, whole-cell recordings from neurons in the anaesthetized and awake mammalian brain , 2002, Pflügers Archiv.

[24]  A. Destexhe.  Kinetic Models of Synaptic Transmission , 1997 .

[25]  A. Strickholm.  A supercharger for single electrode voltage and current clamping , 1995, Journal of Neuroscience Methods.

[26]  M. Carandini,et al.  Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex. , 2000, Journal of neurophysiology.

[27]  A. Destexhe,et al.  The high-conductance state of neocortical neurons in vivo , 2003, Nature Reviews Neuroscience.

[28]  A. Destexhe,et al.  Synaptic background activity controls spike transfer from thalamus to cortex , 2005, Nature Neuroscience.

[29]  A Shrier,et al.  Series resistance compensation for whole-cell patch-clamp studies using a membrane state estimator. , 1999, Biophysical journal.

[30]  D. McCormick,et al.  Enhancement of visual responsiveness by spontaneous local network activity in vivo. , 2007, Journal of neurophysiology.

[31]  Romain Brette,et al.  A non-parametric electrode model for intracellular recording , 2007, Neurocomputing.

[32]  B. Lindemann,et al.  Theory of a membrane‐voltage clamp with discontinuous feedback through a pulsed current clamp , 1974 .

[33]  Y. Frégnac,et al.  Visual input evokes transient and strong shunting inhibition in visual cortical neurons , 1998, Nature.

[34]  Thierry Bal,et al.  Calculating event-triggered average synaptic conductances from the membrane potential. , 2006, Journal of neurophysiology.

[35]  D. Contreras,et al.  Dynamics of excitation and inhibition underlying stimulus selectivity in rat somatosensory cortex , 2005, Nature Neuroscience.

[36]  Jean-Michel Deniau,et al.  Activity of Ventral Medial Thalamic Neurons during Absence Seizures and Modulation of Cortical Paroxysms by the Nigrothalamic Pathway , 2007, The Journal of Neuroscience.

[37]  H. L. Bryant,et al.  Spike initiation by transmembrane current: a white‐noise analysis. , 1976, The Journal of physiology.

[38]  Pablo Fuentealba,et al.  Synaptic plasticity in local cortical network in vivo and its modulation by the level of neuronal activity. , 2006, Cerebral cortex.

[39]  Stephen Redman,et al.  Theory and operation of a single microelectrode voltage clamp , 1984, Journal of Neuroscience Methods.

[40]  R. Reid,et al.  Synaptic Integration in Striate Cortical Simple Cells , 1998, The Journal of Neuroscience.

[41]  H. Robinson,et al.  Injection of digitally synthesized synaptic conductance transients to measure the integrative properties of neurons , 1993, Journal of Neuroscience Methods.

[42]  D. Wilkin,et al.  Neuron , 2001, Brain Research.

[43]  Andrea Hasenstaub,et al.  Barrages of Synaptic Activity Control the Gain and Sensitivity of Cortical Neurons , 2003, The Journal of Neuroscience.

[44]  Virginia R. de Sa,et al.  Model fitting as an aid to bridge balancing in neuronal recording , 2001, Neurocomputing.

[45]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[46]  M. Steriade,et al.  Natural waking and sleep states: a view from inside neocortical neurons. , 2001, Journal of neurophysiology.

[47]  C. Gray,et al.  Dynamic spike threshold reveals a mechanism for synaptic coincidence detection in cortical neurons in vivo. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[48]  Idan Segev,et al.  Methods in Neuronal Modeling , 1988 .

[49]  Michael Rudolph,et al.  Note on “ Characterization of subthreshold voltage fluctuations in neuronal membranes ” , 2008 .

[50]  Eve Marder,et al.  The dynamic clamp comes of age , 2004, Trends in Neurosciences.

[51]  William H. Press,et al.  The Art of Scientific Computing Second Edition , 1998 .