J Neurophysiol (April 1, 2003). 10.1152/jn.00977.2002
Submitted on Submitted 29 October 2002; accepted in final form 10 December 2002

Nonspiking and Spiking Proprioceptors in the Crab: White Noise Analysis of Spiking CB-Chordotonal Organ Afferents

Neuroscience Program, Department of Biological Sciences, Ohio University, Athens, Ohio 45701

Gamble, E. Rolland and Ralph A. DiCaprio. Nonspiking and Spiking Proprioceptors in the Crab: White Noise Analysis of Spiking CB-Chordotonal Organ Afferents. J. Neurophysiol. 89: 1815-1825, 2003. The proprioceptors that signal the position and movement of the first two joints of crustacean legs provide an excellent system for comparison of spiking and nonspiking (graded) information transfer and processing in a simple motor system. The position, velocity, and acceleration of the first two joints of the crab leg are monitored by both nonspiking and spiking proprioceptors. The nonspiking thoracic-coxal muscle receptor organ (TCMRO) spans the TC joint, while the coxo-basal (CB) joint is monitored by the spiking CB chordotonal organ (CBCTO) and by nonspiking afferents arising from levator and depressor elastic strands. The response characteristics and nonlinear models of the input-output relationship for CB chordotonal afferents were determined using white noise analysis (Wiener kernel) methods. The first- and second-order Wiener kernels for each of the four response classes of CB chordotonal afferents (position, position-velocity, velocity, and acceleration) were calculated and the gain function for each receptor determined by taking the Fourier transform of the first-order kernel. In all cases, there was a good correspondence between the response of an afferent to deterministic stimulation (trapezoidal movement) and the best-fitting linear transfer function calculated from the first-order kernel. All afferents also had a nonlinear response component and second-order Wiener kernels were calculated for afferents of each response type. Models of afferent responses based on the first- and second-order kernels were able to predict the response of the afferents with an average accuracy of 86%.