Recovering quasi-active properties of dendritic neurons from dual potential recordings.
We develop the theory and accompanying algorithm for the recovery of a dendritic neuron's cytoplasmic resistivity, membrane capacitance, leakage conductance, and two maximal channel conductances from weighted averages of simultaneous recordings of somatic and dendritic potential following a somatic current stimulus. We test our results on two model systems with distinct, though prescribed, channel kinetics and branching patterns.
Cox
S J
SJ
Department of Computational and Applied Mathematics, Rice University, 6100 Main St., Houston, TX 77005, USA. cox@caam.rice.edu
Griffith
B E
BE
D000465:Algorithms; D000818:Animals; D001369:Axons / Q000502:physiology; D002462:Cell Membrane / Q000502:physiology*; D003593:Cytoplasm / Q000502:physiology; D003712:Dendrites / Q000502:physiology*; D025802:Electric Capacitance; D019706:Excitatory Postsynaptic Potentials / Q000502:physiology*; D006801:Humans; D007473:Ion Channels / Q000502:physiology*; D007700:Kinetics; D008959:Models, Neurological; D015398:Signal Transduction / Q000502:physiology
D007473:Ion Channels