Local modulation of Neurofilament transport at Nodes of Ranvier.

Neurofilaments (NFs) are the most abundant cytoskeletal filaments undergoing 'slow axonal transport' in axons, and the population of NFs determines the axonal morphology. Both in vitro and ex-vivo experimental evidences show that the caliber of node is much thinner and the number of NFs in the node is much lower than the internode. Based on the Continuity equation, lower population of NFs indicates faster transport velocity. We propose that the local acceleration of NFs transport at node may result from the higher on-track rate [Formula: see text] or higher transition rate [Formula: see text] from pausing to running. We construct a segment of axon including both node and internode, and inject NFs by a fixed flux into it continuously. By upregulating transition rate of either [Formula: see text] or [Formula: see text] locally at the Node of Ranvier in the '6-state'model, we successfully accelerate NFs velocity and reproduce constriction of nodes. Our work demonstrates that local modulation of NF kinetics can change NFs distribution and shape the morphology of Node of Ranvier.

Comparison of algorithms for the simulation of action potentials with stochastic sodium channels.

This paper presents a comparison of computational algorithms to simulate action potentials using stochastic sodium channels. Four algorithms are compared in single-node models: Strassberg and DeFelice (1993) (SD), Rubinstein (1995) (R), Chow and White (1996) (CW), and Fox (1997) (F). Neural responses are simulated to a simple and a preconditioned monophasic current pulse. Three exact algorithms implementing Markov jumping processes (SD, R, CW) resulted in similar responses, while the approximation algorithm using Langevin's equation (F) showed quite different responses from those in the exact algorithms. The computational time was measured as well: 1(F), 7(CW), 32(SD), 39(R) relative to that of the F algorithm. Furthermore, it is shown that as the sampling step for integration of the transmembrane potential increases, neural responses in all algorithms tended to be different from those in dense sampling steps, however, the CW algorithm was robust even at a sparse sampling step. It is concluded that the most computationally efficient algorithm having appropriate properties of neural excitability is the CW algorithm.

Effects of stochastic sodium channels on extracellular excitation of myelinated nerve fibers.

The effects of the stochastic gating properties of sodium channels on the extracellular excitation properties of mammalian nerve fibers was determined by computer simulation. To reduce computation time, a hybrid multicompartment cable model including five central nodes of Ranvier containing stochastic sodium channels and 16 flanking nodes containing detenninistic membrane dynamics was developed. The excitation properties of the hybrid cable model were comparable with those of a full stochastic cable model including 21 nodes of Ranvier containing stochastic sodium channels, indicating the validity of the hybrid cable model. The hybrid cable model was used to investigate whether or not the excitation properties of extracellularly activated fibers were influenced by the stochastic gating of sodium channels, including spike latencies, strength-duration (SD), current-distance (IX), and recruitment properties. The stochastic properties of the sodium channels in the hybrid cable model had the greatest impact when considering the temporal dynamics of nerve fibers, i.e., a large variability in latencies, while they did not influence the SD, IX, or recruitment properties as compared with those of the conventional deterministic cable model. These findings suggest that inclusion of stochastic nodes is not important for model-based design of stimulus waveforms for activation of motor nerve fibers. However, in cases where temporal fine structure is important, for example in sensory neural prostheses in the auditory and visual systems, the stochastic properties of the sodium channels may play a key role in the design of stimulus waveforms.