Stochastic simulations on the reliability of action potential propagation in thin axons.
It is generally assumed that axons use action potentials (APs) to transmit information fast and reliably to synapses. Yet, the reliability of transmission along fibers below 0.5 microm diameter, such as cortical and cerebellar axons, is unknown. Using detailed models of rodent cortical and squid axons and stochastic simulations, we show how conduction along such thin axons is affected by the probabilistic nature of voltage-gated ion channels (channel noise). We identify four distinct effects that corrupt propagating spike trains in thin axons: spikes were added, deleted, jittered, or split into groups depending upon the temporal pattern of spikes. Additional APs may appear spontaneously; however, APs in general seldom fail (<1%). Spike timing is jittered on the order of milliseconds over distances of millimeters, as conduction velocity fluctuates in two ways. First, variability in the number of Na channels opening in the early rising phase of the AP cause propagation speed to fluctuate gradually. Second, a novel mode of AP propagation (stochastic microsaltatory conduction), where the AP leaps ahead toward spontaneously formed clusters of open Na channels, produces random discrete jumps in spike time reliability. The combined effect of these two mechanisms depends on the pattern of spikes. Our results show that axonal variability is a general problem and should be taken into account when considering both neural coding and the reliability of synaptic transmission in densely connected cortical networks, where small synapses are typically innervated by thin axons. In contrast we find that thicker axons above 0.5 microm diameter are reliable.
Faisal
A Aldo
AA
Department of Zoology, Cambridge University, Cambridge, United Kingdom. a.faisal@zoo.cam.ac.uk
Laughlin
Simon B
SB
D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001369:Axons / Q000502:physiology* / Q000648:ultrastructure*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D049832:Decapodiformes; D015640:Ion Channel Gating / Q000502:physiology*; D008564:Membrane Potentials / Q000502:physiology; D051379:Mice; D008959:Models, Neurological; D015233:Models, Statistical; D009431:Neural Conduction / Q000502:physiology*; D051381:Rats; D013269:Stochastic Processes