Using extracellular action potential recordings to constrain compartmental models

We investigate the use of extracellular action potential (EAP) recordings for biophysically faithful compartmental models. We ask whether constraining a model to fit the EAP is superior to matching the intracellular action potential (IAP). In agreement with previous studies, we find that the IAP method under-constrains the parameters. As a result, significantly different sets of parameters can have virtually identical IAP’s. In contrast, the EAP method results in a much tighter constraint. We find that the distinguishing characteristics of the waveform—but not its amplitude- resulting from the distribution of active conductances are fairly invariant to changes of electrode position and detailed cellular morphology. Based on these results, we conclude that EAP recordings are an excellent source of data for the purpose of constraining compartmental models.

[1]  D. A. Dunnett Classical Electrodynamics , 2020, Nature.

[2]  G. Shepherd,et al.  Emerging rules for the distributions of active dendritic conductances , 2002, Nature Reviews Neuroscience.

[3]  G. Buzsáki,et al.  Somadendritic backpropagation of action potentials in cortical pyramidal cells of the awake rat. , 1998, Journal of neurophysiology.

[4]  W. Rall Electrophysiology of a dendritic neuron model. , 1962, Biophysical journal.

[5]  G. Holt A critical reexamination of some assumptions and implications of cable theory in neurobiology , 1998 .

[6]  Christof Koch,et al.  Biophysics of Computation: Information Processing in Single Neurons (Computational Neuroscience Series) , 1998 .

[7]  C. Bédard,et al.  Model of low-pass filtering of local field potentials in brain tissue. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  Winfred Max Schwarz,et al.  Intermediate Electromagnetic Theory , 1973 .

[9]  D. Johnston,et al.  K+ channel regulation of signal propagation in dendrites of hippocampal pyramidal neurons , 1997, Nature.

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

[11]  C. Koch,et al.  On the origin of the extracellular action potential waveform: A modeling study. , 2006, Journal of neurophysiology.

[12]  Liam Paninski,et al.  Efficient estimation of detailed single-neuron models. , 2006, Journal of neurophysiology.

[13]  R. L. Nó,et al.  Action potential of the motoneurons of the hypoglossus nucleus. , 1947 .

[14]  Christof Koch,et al.  Electrical Interactions via the Extracellular Potential Near Cell Bodies , 1999, Journal of Computational Neuroscience.

[15]  R. Quian Quiroga,et al.  Unsupervised Spike Detection and Sorting with Wavelets and Superparamagnetic Clustering , 2004, Neural Computation.

[16]  M L Hines,et al.  Neuron: A Tool for Neuroscientists , 2001, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[17]  Noam Peled,et al.  Constraining compartmental models using multiple voltage recordings and genetic algorithms. , 2005, Journal of neurophysiology.

[18]  T. Sejnowski,et al.  A model of spike initiation in neocortical pyramidal neurons , 1995, Neuron.

[19]  P Varona,et al.  Macroscopic and subcellular factors shaping population spikes. , 2000, Journal of neurophysiology.

[20]  N. Spruston,et al.  Perforated patch-clamp analysis of the passive membrane properties of three classes of hippocampal neurons. , 1992, Journal of neurophysiology.

[21]  James M. Bower,et al.  A Comparative Survey of Automated Parameter-Search Methods for Compartmental Neural Models , 1999, Journal of Computational Neuroscience.

[22]  O Herreras,et al.  Activity-dependent changes of tissue resistivity in the CA1 region in vivo are layer-specific: modulation of evoked potentials , 2001, Neuroscience.

[23]  D. Johnston,et al.  Characterization of single voltage‐gated Na+ and Ca2+ channels in apical dendrites of rat CA1 pyramidal neurons. , 1995, The Journal of physiology.

[24]  H. Markram,et al.  Correlation maps allow neuronal electrical properties to be predicted from single-cell gene expression profiles in rat neocortex. , 2004, Cerebral cortex.

[25]  D. Johnston,et al.  Slow Recovery from Inactivation of Na+ Channels Underlies the Activity-Dependent Attenuation of Dendritic Action Potentials in Hippocampal CA1 Pyramidal Neurons , 1997, The Journal of Neuroscience.

[26]  Douglas A. Baxter,et al.  Estimation of single-neuron model parameters from spike train data , 2005, Neurocomputing.

[27]  J. Csicsvari,et al.  Intracellular features predicted by extracellular recordings in the hippocampus in vivo. , 2000, Journal of neurophysiology.

[28]  U. Heinemann,et al.  Comparison of voltage-dependent potassium currents in rat pyramidal neurons acutely isolated from hippocampal regions CA1 and CA3. , 1995, Journal of neurophysiology.

[29]  C. Koch,et al.  Methods in Neuronal Modeling: From Ions to Networks , 1998 .

[30]  Jean Ponce,et al.  Computer Vision: A Modern Approach , 2002 .

[31]  Lyle J. Borg-Graham,et al.  Interpretations of Data and Mechanisms for Hippocampal Pyramidal Cell Models , 1999 .