The Nonlinear Dynamics of the Crayfish Mechanoreceptor System

We review here the nonlinear dynamical properties of the crayfish mechanoreceptor system from the hydrodynamically sensitive hairs on the tailfan through the caudal photoreceptor neurons embedded in the 6th ganglion. Emphasis is on the extraction of low dimensional behavior from the random processes (noise) that dominate this neural system. We begin with stochastic resonance in the sensory root afferents and continue with a discussion of the photoreceptor oscillator and its instabilities. Stochastic synchronization, rectification and the generation of second harmonic responses in the photoreceptors are finally discussed.

Light enhances hydrodynamic signaling in the multimodal caudal photoreceptor interneurons of the crayfish

1. The caudal photoreceptor (CPR) interneurons in the sixth abdominal ganglion of the crayfish are complex, multi-modal interneurons. These cells respond directly to light with tonic spike discharges, and they integrate synaptic input from an array of fili-form mechanoreceptors on the tailfan. They also provide input to rostral command centers, inducing backward walking at high firing frequencies, and thus directly influence behavior. 2. We recorded CPR activity in response to weak hydrodynamic stimulation of the tailfan mechanoreceptors while under varying intensities of light shined on the sixth ganglion. Spike trains were characterized according to the mean discharge rate (MDR) and the power spectrum from which the signal-to-noise ratio (SNR) was calculated. 3. Illumination of the CPR enhances the efficiency of transmitting mechanosensory signals. It does so by increasing the SNR of mechanosensory input received from tailfan receptors. A sevenfold, nonlinear increase in the SNRs was observed with increasing light intensity, an effect especially pronounced for weak hydrodynamic stimuli. In comparison with the dark, illumination of the ganglion lowered the hydrodynamic threshold and heightened the response to suprathreshold stimulation. Unlike the SNR, the MDR is little affected by mechanosensory input. 4. These results are compared with simulated electronic activity from an analogue threshold model and are discussed with respect to the mechanism of stochastic resonance.

DETECTING LOW DIMENSIONAL DYNAMICS IN BIOLOGICAL EXPERIMENTS

We discuss the well-known problems associated with efforts to detect and characterize chaos and other low dimensional dynamics in biological settings. We propose a new method which shows promise for addressing these problems, and we demonstrate its effectiveness in an experiment with the crayfish sensory system. Recordings of action potentials in this system are the data. We begin with a pair of assumptions: that the times of firings of neural action potentials are largely determined by high dimensional random processes or “noise”; and that most biological files are non stationary, so that only relatively short files can be obtained under approximately constant conditions. The method is thus statistical in nature. It is designed to recognize individual “events” in the form of particular sequences of time intervals between action potentials which are the signatures of certain well defined dynamical behaviors. We show that chaos can be distinguished from limit cycles, even when the dynamics is heavily contaminated with noise. Extracellular recordings from the crayfish caudal photoreceptor, obtained while hydrodynamically stimulating the array of hair receptors on the tailfan, are used to illustrate the method.