Propagation of action potentials along complex axonal trees. Model and implementation.

Axonal trees are typically morphologically and physiologically complicated structures. Because of this complexity, axonal trees show a large repertoire of behavior: from transmission lines with delay, to frequency filtering devices in both temporal and spatial domains. Detailed theoretical exploration of the electrical behavior of realistically complex axonal trees is notably lacking, mainly because of the absence of a simple modeling tool. AXONTREE is an attempt to provide such a simulator. It is written in C for the SUN workstation and implements both a detailed compartmental modeling of Hodgkin and Huxley-like kinetics, and a more abstract, event-driven, modeling approach. The computing module of AXONTREE is introduced together with its input/output features. These features allow graphical construction of arbitrary trees directly on the computer screen, and superimposition of the results on the simulated structure. Several numerical improvements that increase the computational efficiency by a factor of 5-10 are presented; most notable is a novel method of dynamic lumping of the modeled tree into simpler representations ("equivalent cables"). AXONTREE's performance is examined using a reconstructed terminal of an axon from a Y cell in cat visual cortex. It is demonstrated that realistically complicated axonal trees can be handled efficiently. The application of AXONTREE for the study of propagation delays along axonal trees is presented in the companion paper (Manor et al., 1991).

[1]  G. Shepherd,et al.  Computer simulation of a dendrodendritic synaptic circuit for self- and lateral-inhibition in the olfactory bulb , 1979, Brain Research.

[2]  B. Katz,et al.  Propagation of electric activity in motor nerve terminals , 1965, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[3]  W Rall,et al.  Changes of action potential shape and velocity for changing core conductor geometry. , 1974, Biophysical journal.

[4]  George D. Bittner,et al.  Differentiation of Nerve Terminals in the Crayfish Opener Muscle and Its Functional Significance , 1968, The Journal of general physiology.

[5]  T. B. Woolf,et al.  Neuron simulations with SABER , 1990, Journal of Neuroscience Methods.

[6]  M Hines,et al.  A program for simulation of nerve equations with branching geometries. , 1989, International journal of bio-medical computing.

[7]  I. Parnas,et al.  Differential block at high frequency of branches of a single axon innervating two muscles. , 1972, Journal of neurophysiology.

[8]  I. Parnas,et al.  Differential conduction block in branches of a bifurcating axon. , 1979, The Journal of physiology.

[9]  Mark E. Nelson,et al.  Simulating neurons and networks on parallel computers , 1989 .

[10]  N. Stockbridge,et al.  Theoretical response of a bifurcating axon with a locally altered axial resistivity. , 1989, Journal of theoretical biology.

[11]  M. Sereno,et al.  Caudal topographic nucleus isthmi and the rostral nontopographic nucleus isthmi in the turtle, pseudemys scripta , 1987, The Journal of comparative neurology.

[12]  I Segev,et al.  Electrotonic architecture of type-identified alpha-motoneurons in the cat spinal cord. , 1988, Journal of neurophysiology.

[13]  J S Shiner,et al.  Computation of action potential propagation and presynaptic bouton activation in terminal arborizations of different geometries. , 1990, Biophysical journal.

[14]  I Segev,et al.  Computer study of presynaptic inhibition controlling the spread of action potentials into axonal terminals. , 1990, Journal of neurophysiology.

[15]  M. Hines,et al.  Efficient computation of branched nerve equations. , 1984, International journal of bio-medical computing.

[16]  J. Clements,et al.  Cable properties of cat spinal motoneurones measured by combining voltage clamp, current clamp and intracellular staining. , 1989, The Journal of physiology.

[17]  J W Moore,et al.  A numerical method to model excitable cells. , 1978, Biophysical journal.

[18]  J. Lettvin,et al.  Multiple meaning in single visual units. , 1970, Brain, behavior and evolution.

[19]  M. Konishi,et al.  Axonal delay lines for time measurement in the owl's brainstem. , 1988, Proceedings of the National Academy of Sciences of the United States of America.

[20]  W. Rall Cable theory for dendritic neurons , 1989 .

[21]  W. Rall Branching dendritic trees and motoneuron membrane resistivity. , 1959, Experimental neurology.

[22]  Micheal V. Mascagni Numerical methods for neuronal modeling , 1989 .

[23]  Idan Segev,et al.  Compartmental models of complex neurons , 1989 .

[24]  A. Schüz,et al.  Synaptic density on the axonal tree of a pyramidal cell in the cortex of the mouse , 1985, Neuroscience.

[25]  I Segev,et al.  A mathematical model for conduction of action potentials along bifurcating axons. , 1979, The Journal of physiology.

[26]  S Hochstein,et al.  Theoretical analysis of parameters leading to frequency modulation along an inhomogeneous axon. , 1976, Journal of neurophysiology.

[27]  S G Waxman,et al.  Integrative properties and design principles of axons. , 1975, International review of neurobiology.

[28]  A. Light,et al.  The ultrastructure of group Ia afferent fiber synapses in the lumbosacral spinal cord of the cat , 1984, Brain Research.

[29]  C. Koch,et al.  Effect of geometrical irregularities on propagation delay in axonal trees. , 1991, Biophysical journal.

[30]  V. Braitenberg Is the cerebellar cortex a biological clock in the millisecond range? , 1967, Progress in brain research.

[31]  N. T. Carnevale,et al.  Numerical analysis of electrotonus in multicompartmental neuron models , 1987, Journal of Neuroscience Methods.

[32]  J. Cooley,et al.  Digital computer solutions for excitation and propagation of the nerve impulse. , 1966, Biophysical journal.

[33]  J S Shiner,et al.  Simulation of action potential propagation in complex terminal arborizations. , 1990, Biophysical journal.

[34]  A. L. Humphrey,et al.  Projection patterns of individual X‐ and Y‐cell axons from the lateral geniculate nucleus to cortical area 17 in the cat , 1985, The Journal of comparative neurology.

[35]  R. Keynes The ionic channels in excitable membranes. , 1975, Ciba Foundation symposium.

[36]  H. Atwood,et al.  THREE-DIMENSIONAL ULTRASTRUCTURE OF THE CRAYFISH NEUROMUSCULAR APPARATUS , 1974, The Journal of cell biology.

[37]  A. Hodgkin,et al.  A quantitative description of membrane current and its application to conduction and excitation in nerve , 1952, The Journal of physiology.

[38]  D. H. Barron,et al.  Intermittent conduction in the spinal cord , 1935, The Journal of physiology.

[39]  E De Schutter Computer software for development and simulation of compartmental models of neurons. , 1989, Computers in biology and medicine.

[40]  K. Rockland,et al.  Bistratified distribution of terminal arbors of individual axons projecting from area V1 to middle temporal area (MT) in the macaque monkey , 1989, Visual Neuroscience.

[41]  J W Moore,et al.  On numerical integration of the Hodgkin and Huxley equations for a membrane action potential. , 1974, Journal of theoretical biology.

[42]  H. Swadlow,et al.  Modulation of impulse conduction along the axonal tree. , 1980, Annual review of biophysics and bioengineering.

[43]  B. Khodorov,et al.  Nerve impulse propagation along nonuniform fibres. , 1975, Progress in biophysics and molecular biology.

[44]  P. Somogyi,et al.  Evidence for interlaminar inhibitory circuits in the striate cortex of the cat , 1987, The Journal of comparative neurology.