QUANTITATIVE-ANALYSIS OF ELECTROTONIC STRUCTURE AND MEMBRANE-PROPERTIES OF NMDA-ACTIVATED LAMPREY SPINAL NEURONS

Citation
Cr. Murphey et al., QUANTITATIVE-ANALYSIS OF ELECTROTONIC STRUCTURE AND MEMBRANE-PROPERTIES OF NMDA-ACTIVATED LAMPREY SPINAL NEURONS, Neural computation, 7(3), 1995, pp. 486-506
Citations number
28
Categorie Soggetti
Computer Sciences","Computer Science Artificial Intelligence",Neurosciences
Journal title
ISSN journal
08997667
Volume
7
Issue
3
Year of publication
1995
Pages
486 - 506
Database
ISI
SICI code
0899-7667(1995)7:3<486:QOESAM>2.0.ZU;2-I
Abstract
Parameter optimization methods were used to quantitatively analyze fre quency-domain-voltage-clamp data of NMDA-activated lamprey spinal neur ons simultaneously over a wide range of membrane potentials. A neurona l cable model was used to explicitly take into account receptors locat ed on the dendritic trees. The driving point membrane admittance was m easured from the cell soma in response to a Fourier synthesized point voltage clamp stimulus. The data were fitted to an equivalent cable mo del consisting of a single lumped soma compartment coupled resistively to a series of equal dendritic compartments. The model contains volta ge-dependent NMDA sensitive (I-NMDA), slow potassium (I-K), and leakag e (I-L) currents. Both the passive cable properties and the voltage de pendence of ion channel kinetics were estimated, including the electro tonic structure of the cell, the steady-state gating characteristics, and the time constants for particular voltage- and time-dependent ioni c conductances. An alternate kinetic formulation was developed that co nsisted of steady-state values for the gating parameters and their tim e constants at half-activation values as well as slopes of these param eters at half-activation. This procedure allowed independent restricti ons on the magnitude and slope of both the steady-state gating variabl e and its associated time constant. Quantitative estimates of the volt age-dependent membrane ion conductances and their kinetic parameters w ere used to solve the nonlinear equations describing dynamic responses . The model accurately predicts current clamp responses and is consist ent with experimentally measured TTX-resistant NMDA-induced patterned activity. In summary, an analysis method is developed that provides a Pragmatic approach to quantitatively describe a nonlinear neuronal sys tem.