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  • Electrophysiology and morph...
    Vleggeert-Lankamp, Carmen L A M; van den Berg, Rutgeris J; Feirabend, Hans K P; Lakke, Egbert A J F; Malessy, Martijn J A; Thomeer, Ralph T W M

    Experimental neurology 187, Issue: 2
    Journal Article

    We studied electrophysiological and morphological properties of the Aalpha- and Abeta-fibers in the regenerating sciatic nerve to establish whether these fiber types regenerate in numerical proportion and whether and how the electrophysiological properties of these fiber types are adjusted during regeneration. Compound action potentials were evoked from isolated sciatic nerves 12 weeks after autografting. Nerve fibers were gradually recruited either by increasing the stimulus voltage from subthreshold to supramaximal levels or by increasing the interval between two supramaximal stimuli to obtain the cumulative distribution of the extracellular firing thresholds and refractory periods, respectively. Thus, the mean conduction velocity (MCV), the maximal charge displaced during the compound action potential (Q(max)), the mean firing threshold (V(50)), and the mean refractory period (t(50)) were determined. The number of myelinated nerve fibers and their fiber diameter frequency distributions were determined in the peroneal nerve. Mathematical modeling applied to fiber recruitment and diameter distributions allowed discrimination of the Aalpha- and Abeta-fiber populations. In regenerating nerves, the number of Aalpha-fibers increased fourfold while the number of Abeta-fibers did not change. In regenerating Aalpha- and Abeta-fibers, the fiber diameter decreased and V(50) and t(50) increased. The regenerating Aalpha-fibers' contribution to Q(max) decreased considerably while that of the Abeta-fibers remained the same. Correlation of the electrophysiological data to the morphological data provided indications that the ion channel composition of both the Aalpha- and Abeta-fibers are altered during regeneration. This demonstrates that combining morphometric and electrophysiological analysis provides better insight in the changes that occur during regeneration.