By Amir Ayali
Neuromodulators orchestrate complex behavioral routines by their multiple and combined effects on the nervous system. Substantial progress in the study of neural mechanisms for behaviour has been made by investigating the ability of neuromodulators to cause central pattern generator (CPG) networks to produce a variety of different motor patterns, and thus a number of related behaviors. Traditionally, for such studies, consistent identification and characterization of all the CPG circuit members has been required. Yet many vertebrates and invertebrates preparations, though serving in many studies and providing important neuroethological insights, are far from being fully characterized.
In a recent study (Zilberstein et al., 2004) we introduced an advanced cross-correlation method for the analysis of rhythmic behavior in general, and specifically modulation of rhythmic motor patterns. This method could become very useful as a tool for visual representation of rhythmic motor patterns in different systems and in systems under different physiological states. Furthermore, it is a first step toward quantitatively investigating and comparing temporal properties of rhythmic patterns in which the elements of the CPG circuit have not been identified and activity is presented as nebulous extracellularly recorded bursts.
Briefly (for details see Zilberstein et al., 2004; Segev et al. 2004), peak detection is performed on each burst of action potentials. A time window is selected that included the entire burst duration. Smooth representation of the burst activity profile ( = the activity of all the neurons firing throughout the burst) is then convoluted with a normalized Gaussian. A matrix representing all recorded convoluted bursts is composed. Next, the cross-correlation between all pairs of bursts is computed using a standard algorithm under a MatLab environment (The MathWorks Inc. USA). A color code is then assigned to the maximum value of the cross-correlation. The correlation values of set of bursts (distinct physiological or experimental conditions) can be averaged and the significance of the results can be tested.
In the desert locust, Schistocerca gregaria, frontal ganglion (FG) neurons innervate foregut dilator muscles and play a key role in the control of foregut motor patterns in different physiological and behavioral states (Ayali, 2004). We have previously presented the locust FG as a central pattern generator (Ayali et al. 2002). We described frontal ganglion rhythmic patterns related to two fundamental behaviors in insect life: feeding and molting (Zilberstein and Ayali 2002). Both behaviors constitute a complex set of motor patterns that need to be carefully coordinated and controlled. Our reported results imply neuromodulation of the CPG. Unfortunately, identification and characterization of the neurons that comprise the locust FG CPG are yet in very early stages.
In our recent study (Zilberstein et al., 2004) we have provided a first report of a role for a member of the allatostatine family of neuropeptides as a neuromodulator in insects. Allatostatin, previously reported to be an inhibitor of insect gut muscles (e.g. Duve et al. 1995 ; 1997 ; 1999) and a neuromodulator in the crustacean stomatogastric ganglion (Skiebe and Schneider 1994), was found to have complex dose-dependent modulatory effects on the locust FG rhythmic pattern. Using our cross-correlation analysis technique, we could analyze the modulatory effects of different allatostatin concentrations on the FG rhythmic output. We showed that different concentrations have very different effects, not only on cycle period, but also on temporal characteristics of the rhythmic bursts of action potentials. The physiological significance of our results and the role of the modulator in locust behavior could now be discussed.
Ayali A, Zilberstein Y, Cohen N (2002) The locust frontal ganglion: a central pattern generator network controlling foregut rhythmic motor patterns. J Exp Biol 205: 2825–2832.
Ayali A (2004) The insect frontal ganglion and stomatogastric pattern-generator networks. Neurosignals 1–2: 20–36.
Duve H, Wren P, Thorpe A (1995) Innervation of the foregut of the cockroach Leucophaea maderae and inhibition of spontaneous contractile activity by callatostatine neuropeptides. Physiol entomol 20: 33–44.
Duve H, Johnsen AH, Maestro IL, Scott AG, Crook N, Winstanley D, Thorpe A (1997) Identification, tissue localisation and physiological effect in vitro of a neuroendocrine peptide identical to a dipteran Leu-callatostatin in the codling moth Cydia pomonella (Tortricidae: Lepidoptera). Cell Tissue Res 289: 73–83.
Duve H, East PD, Thorpe A (1999) Regulation of lepidopteran foregut movement by allatostatins and allatotropin from the frontal ganglion. J Comp Neurol 413: 405–416.
Segev R, Baruchi I, Volman V, Hulata E, Shapira Y, Ben-Jacob E. 2004. Hidden neuronal correlations in cultured networks. Phys. Rev. Lett., in press.
Skiebe P, Schneider H (1994) Allatostatin peptides in the crab stomatogastric nervous system: inhibition of the pyloric motor pattern and distribution of allatostatin-like immunoreactivity. J Exp Biol 194: 195–208.
Zilberstein Y, Ayali A. (2002) The role of the frontal ganglion in locust feeding and moulting related behaviours. J Exp Biol 205: 2833–2841.
Zilberstein Y., Fuchs E., Hershtik, L. and Ayali A. Neuromodulation for behavior in the locust frontal ganglion. J. Comp. Physiol. A. 2004, in press, on-line at SpringerLink.com