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This Article Full Text Full Text (PDF) All Versions of this Article: 98/3/1718    most recent 01283.2006v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (3) Citing Articles via Google Scholar Google Scholar Articles by Hooper, S. L. Articles by Büschges, A. Search for Related Content PubMed PubMed Citation Articles by Hooper, S. L. Articles by Büschges, A.

Slow Temporal Filtering May Largely Explain the Transformation of Stick Insect (Carausius morosus) Extensor Motor Neuron Activity Into Muscle Movement

¹Department of Biological Sciences, Ohio University, Athens, Ohio; and ²Tierphysiologie, Zoologisches Institut, Universität zu Köln, Köln, Germany

Submitted 6 December 2006; accepted in final form 11 July 2007

Understanding how nervous systems generate behavior requires understanding how muscles transform neural input into movement. The stick insect extensor tibiae muscle is an excellent system in which to study this issue because extensor motor neuron activity is highly variable during single leg walking and extensor muscles driven with this activity produce highly variable movements. We showed earlier that spike number, not frequency, codes for extensor amplitude during contraction rises, which implies the muscle acts as a slow filter on the time scale of burst interspike intervals (5–10 ms). We examine here muscle response to spiking variation over entire bursts, a time scale of hundreds of milliseconds, and directly measure muscle time constants. Muscle time constants differ during contraction and relaxation, and contraction time constants, although variable, are always extremely slow (200–700 ms). Models using these data show that extremely slow temporal filtering alone can explain much of the observed transform properties. This work also revealed an unexpected (to us) ability of slow filtering to transform steadily declining inputs into constant amplitude outputs. Examination of the effects of time constant variability on model output showed that variation within an SD primarily altered output amplitude, but variation across the entire range also altered contraction shape. These substantial changes suggest that understanding the basis of this variation is central to predicting extensor activity and that the animal could theoretically vary muscle time constant to match extensor response to changing behavioral need.

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