Multiple averaged records to identify Aδ-fibers in sensory nerves.

ABSTRACT

BACKGROUND: Existing methods identify only ≈10 Aδ-fibers in human sensory nerves per recording. This study examines methods to increase the detection of Aδ-fibers. NEW METHOD: Two to 20 averages of 500 replicate responses to epidermal nerve stimulation are obtained. Pairs of different averages are constructed. Each pair is analyzed with algorithms applied to amplitude and frequency to detect replication of responses to stimulation as "simultaneous similarities in two averages" (SS2AVs) at ≥99.5th percentile of control. In a pair of averages the latencies of amplitude and frequency SS2AVs for the same response to stimulation may differ by ≤0.25 ms. Therefore, Aδ-fibers are identified by the 0.25 ms moving sum of SS2AV latencies of the pairs of averages. RESULTS: Increasing averages increases pairs of different averages and detection of Aδ-fibers from 2 to 10 Aδ-fibers with two averages (one pair) to >50 Aδ-fibers with 12-20 averages (66-190 pairs). COMPARISON WITH EXISTING METHOD(S) Existing methods identify ≤10 Aδ-fibers in 10 averages/45 pairs with the medians of amplitude and frequency algorithms applied to all 45 pairs. This study identifies Aδ-fibers (i) by applying these algorithms at the 99.5th percentile of control, (ii) to each pair of averages and (iii) by the 0.25 ms sum of algorithm identified events (SS2AVs) in all pairs. These three changes significantly increase the detection of Aδ-fibers, e.g., in 10 averages/45pairs from 10 to 45. CONCLUSIONS: Three modifications of existing methods can increase the detection of Aδ-fibers to an amount suitable (>50 with ≥12 averages) for statistical comparison of different nerves.