An alternative method for the analysis of neuron passive electrical data which uses integrals of voltage transients.
The traditional method for analyzing passive electrical data from neurons when specific morphological data are unavailable consists of decomposing the voltage response of the cell into a series of exponential functions (the peeling method) and substituting the time constants of these exponential functions into equations derived from cable theory (Rall W, Core conductor theory and cable properties of neurons. In: Handbook of Physiology. The Nervous System. Cellular Biology of Neurons. Bethesda, MD. Am Physiol Soc. Section 1, Part 1, 1977;1(3):39-97). In the present report, an alternative method is examined for analyzing these kinds of data, the integrals of transients method (Eisenberg RS, Mathias RT. Structural analysis of electrical properties of cells and tissues. CRC Critical Reviews in Bioengineering 1980;4:203-232). The integrals required are easily obtained from input resistance data and any theoretical model that is appropriate for the neurons under study can be used, provided that the impedance function can be determined. In order to demonstrate this alternative method, a simple 3-compartment model with both dendritic taper and somatic shunt is used to model data obtained from fast-type alpha-motoneurons in the spinal cord of the cat. These results are compared with results obtained using the traditional peeling method. This comparison indicates that passive electrical data from fast-type motoneurons are best analyzed using a theoretical model that includes both dendritic taper and somatic shunt. Furthermore, our results show that the integrals of transients method can facilitate this analysis.
Department of Physiology, UCLA School of Medicine, University of California, Los Angeles 90024, USA.
J K
JK
Engelhardt
F R
FR
Morales
M H
MH
Chase
D000818:Animals; D002415:Cats; D002462:Cell Membrane / Q000502:physiology; D017097:Electric Impedance; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D009046:Motor Neurons / Q000502:physiology*; D009431:Neural Conduction / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D013116:Spinal Cord; D013499:Surface Properties