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Journal of Experimental Biology, Vol 201, Issue 1 91-102, Copyright © 1998 by Company of Biologists

JOURNAL ARTICLES

Peripheral encoding of moving sources by the lateral line system of a sit-and-wait predator

JC Montgomery and S Coombs

Video-tape recordings of prey-capture behaviour were made to demonstrate that stargazers can detect and capture prey in the dark and to determine the range of prey movement velocities that resulted in prey capture. Electrophysiological recording techniques were then used to determine how an artificial source (a sphere), moving at speeds within the range of recorded prey movement velocities, was encoded by anterior lateral line nerve fibres innervating the preopercular-mandibular canals on the head. A vibrating sphere was also used to measure frequency-response characteristics to determine the bandwidth of response and fibre origin (type of neuromast and location). In order to measure the relevant stimulus parameters likely to govern neural responses, the pressure-gradient pattern produced by the moving sphere was characterised with a pair of miniature hydrophones separated by approximately the same distance as head lateral line canal pores on stargazers. At least four different features of neural response patterns, including direction-dependent changes in the overall envelope of the firing rate pattern, could be predicted on the basis of measured pressure-gradient patterns. The dominant features of both the pressure-gradient and neural response patterns were produced by the wake behind the moving sphere, but behavioural observations indicated that stargazers were responding to the bow of an approaching prey, rather than its wake. Although the form of the wake behind the moving sphere is unlikely to be a good match for the stimulus mediating prey detection, these results clearly establish that pressure-gradient patterns are good predictors of neural response patterns. Thus, similar measurements of pressure-gradient patterns produced by more biologically relevant sources can be used to predict peripheral lateral line responses and stimulus features likely to be of key importance.

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