Transfer impedances between different regions of branched excitable cells.
1. The excitable properties of branched cells were measured using a combination of voltage-clamp and frequency-domain techniques. Point impedance functions from either the soma or growth cone of NG-108 cells were curve fitted with a reduced cable model at different membrane potentials to establish kinetic parameters. 2. Transfer impedance functions between the soma and growth cone were measured and simulated with a morphologically determined model. In these experiments the membrane potential was controlled by a single-electrode voltage clamp thus allowing an estimate of transfer functions for any arbitrary input, such as a single synaptic current for differing degrees of tonic synaptic drive. Furthermore, the integration of different regional inputs was evaluated based on the transfer functions between different locations on an individual cell. 3. The activation of an outward steady-state current leads to resonating impedance functions that were used to evaluate the kinetic properties of ionic channels in different regions of branched excitable cells. For simple branching patterns the point and transfer impedances show lower resonant frequencies for active growth cones compared with active somas. 4. More complex branching patterns showed the unexpected result that the voltage-dependent resonant frequency was higher for the growth cone recording than the soma. The presence of a higher resonant frequency when the growth cone is activated does not require more rapid kinetics of the active potassium conductance, since the time constant of the active conductance can be the same in the growth cone and the soma membrane. 5. In conclusion, the resonant frequencies, as well as all other aspects of the impedance functions, are complicated interactions of the detailed branching patterns and active conductances. In general, these interactions are not predictable from a passive electrotonic analysis, especially when the voltage-dependent conductances are distributed throughout the dendritic tree.
Moore
L E
LE
Department of Physiology and Biophysics, University of Texas Medical Branch, Galveston 77550.
Yoshii
K
K
Christensen
B N
BN
D000818:Animals; D003198:Computer Simulation; D006822:Hybrid Cells; D008959:Models, Neurological; D009433:Neural Inhibition; D009474:Neurons / Q000166:cytology / Q000502:physiology*; D009435:Synaptic Transmission