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Dipole characterization of single neurons from their extracellular action potentials

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Abstract

The spatial variation of the extracellular action potentials (EAP) of a single neuron contains information about the size and location of the dominant current source of its action potential generator, which is typically in the vicinity of the soma. Using this dependence in reverse in a three-component realistic probe + brain + source model, we solved the inverse problem of characterizing the equivalent current source of an isolated neuron from the EAP data sampled by an extracellular probe at multiple independent recording locations. We used a dipole for the model source because there is extensive evidence it accurately captures the spatial roll-off of the EAP amplitude, and because, as we show, dipole localization, beyond a minimum cell-probe distance, is a more accurate alternative to approaches based on monopole source models. Dipole characterization is separable into a linear dipole moment optimization where the dipole location is fixed, and a second, nonlinear, global optimization of the source location. We solved the linear optimization on a discrete grid via the lead fields of the probe, which can be calculated for any realistic probe + brain model by the finite element method. The global source location was optimized by means of Tikhonov regularization that jointly minimizes model error and dipole size. The particular strategy chosen reflects the fact that the dipole model is used in the near field, in contrast to the typical prior applications of dipole models to EKG and EEG source analysis. We applied dipole localization to data collected with stepped tetrodes whose detailed geometry was measured via scanning electron microscopy. The optimal dipole could account for 96% of the power in the spatial variation of the EAP amplitude. Among various model error contributions to the residual, we address especially the error in probe geometry, and the extent to which it biases estimates of dipole parameters. This dipole characterization method can be applied to any recording technique that has the capabilities of taking multiple independent measurements of the same single units.

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Acknowledgment

This work was supported by NIH grant EY9314 (JDV, FM).

We thank Qin Hu, Ifije Ohiorhenuan, Mike Repucci and Anita Schmid for their help in the data collection; Dirk Hoehl and Thomas Recording Gmbh for their consistently reliable tetrodes; Dr Stephen B. Doty and Tony Labassiere of Analytical Microscopy Core Facility, Hospital for Special Surgery New York, NY, for the scanning electron-microscopy; and Drs Partha Mitra and Alexander Polyakov for stimulating early discussions and introducing the use of Femlab.

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  1. Department of Neurology and Neuroscience, Medical College of Cornell University, 1300 York Avenue, New York, NY, 10065–4805, USA

    Ferenc Mechler & Jonathan D. Victor

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  1. Ferenc Mechler
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  2. Jonathan D. Victor
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Correspondence to Ferenc Mechler.

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Mechler, F., Victor, J.D. Dipole characterization of single neurons from their extracellular action potentials. J Comput Neurosci 32, 73–100 (2012). https://doi.org/10.1007/s10827-011-0341-0

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