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Progress in Neurobiology 63 (2001) 409 – 439 www.elsevier.com/locate/pneurobio Identified nerve cells and insect behavior Christopher M. Comer a,*, R. Meldrum Robertson b a Laboratory of Integrati6e Neuroscience, Department of Biological Sciences, Uni6ersity of Illinois at Chicago, Chicago, IL 60607, USA b Department of Biology, Queens Uni6ersity, Kingston Ont., Canada K7L 3N6 Abstract Studies of insect identified neurons over the past 25 years have provided some of the very best data on sensorimotor integration; tracing information flow from sensory to motor networks. General principles have emerged that have increased the sophistication with which we now understand both sensory processing and motor control. Two overarching themes have emerged from studies of identified sensory interneurons. First, within a species, there are profound differences in neuronal organization associated with both the sex and the social experience of the individual. Second, single neurons exhibit some surprisingly rich examples of computational sophistication in terms of (a) temporal dynamics (coding superimposed upon circadian and shorter-term rhythms), and also (b) what Kenneth Roeder called ‘neural parsimony’: that optimal information can be encoded, and complex acts of sensorimotor coordination can be mediated, by small ensembles of cells. Insect motor systems have proven to be relatively complex, and so studies of their organization typically have not yielded completely defined circuits as are known from some other invertebrates. However, several important findings have emerged. Analysis of neuronal oscillators for rhythmic behavior have delineated a profound influence of sensory feedback on interneuronal circuits: they are not only modulated by feedback, but may be substantially reconfigured. Additionally, insect motor circuits provide potent examples of neuronal restructuring during an organism’s lifetime, as well as insights on how circuits have been modified across evolutionary time. Several areas where future advances seem likely to occur include: molecular genetic analyses, neuroecological syntheses, and neuroinformatics — the use of digital resources to organize databases with information on identified nerve cells and behavior. © 2001 Elsevier Science Ltd. All rights reserved. Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410 1.1. The identified neuron approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410 2. Coding sensory information . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Historical perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Operating principles . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1. Group/individual differences in central circuitry . . . . . . . 2.2.2. The importance of temporal dynamics . . . . . . . . . . . . 2.2.3. The computational sophistication of individual neurons . . 2.2.4. Coarse coding and computational mapping. . . . . . . . . . 2.2.5. Neural parsimony and the decoding of central information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 411 411 411 411 413 413 415 418 Abbre6iations: 5HT, 5-hydroxytryptamine (serotonin); AN, ascending neuron; CN cercal nerve; CNS, central nervous system; DCMD, descending contralateral movement detector; DEP, depressor; DMI, descending mechanosensory interneuron; DN, descending neuron; DUM, dorsal unpaired median; EPSP, excitatory post synaptic potential; GABA, gamma amino butyric acid; GF, giant fiber; GI, giant interneuron; dGI, dorsal giant interneuron; vGI, ventral giant interneuron; int, interneuron; STIM, stimulation; TCG, tritocerebral commissural giant; TI, thoracic interneuron; T3, metathoracic ganglion; URL, universal resource locator; VM, ventromedial; VUM, ventral unpaired median; VCH, ventral centrifugal horizontal; WBF, wing beat frequency; WWW, world wide web. * Corresponding author. Tel.: + 1-312-9962992; fax: +1-312-4132435. E-mail addresses: [email protected] (C.M. Comer), [email protected] (R.M. Robertson). 0301-0082/01/$ - see front matter © 2001 Elsevier Science Ltd. All rights reserved. PII: S0301-0082(00)00051-4 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 410 3. Patterning of motor output. . . . . . . . . . . . 3.1. Historical perspective . . . . . . . . . . . . 3.2. Operating principles . . . . . . . . . . . . 3.2.1. Defined circuits . . . . . . . . . . . 3.2.2. Organization and reconfiguration 3.2.3. Neuromodulation. . . . . . . . . . 3.2.4. Afferent regulation . . . . . . . . . 3.3. Neuronal restructuring . . . . . . . . . . . 3.4. Evolution and homology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 421 421 422 422 423 425 426 426 428 4. Newer approaches . . . . . . . . . . . . . 4.1. Molecular/genetic approaches . . . 4.2. Neuroecology . . . . . . . . . . . . 4.3. Neuroinformatics and insect nerve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429 429 430 431 5. Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431 . . . . . . . . . cells . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 1. Introduction The control of insect behavior by uniquely identified nerve cells is a vast topic, so any review of the area must be selective. We will concentrate on cases where relationships between identified nerve cell properties and behavior have been convincingly established, or where experimental data highlight general principles of sensory processing or motor control. The organization of this review thus will reflect the spirit recommended to neuroethologists by Franz Huber (1988) when he stated, ‘‘Questions of principle should guide our research.’’ Each type of organism (or model system) tends to have advantages for answering certain types of neurobiological questions. For example, the crustacean stomatogastric system has provided some of the clearest information on mechanisms for generating rhythmic behavior and for the short-term reconfiguration of neural circuitry (e.g. Selverston et al., 1998); while studies of Mauthner-related startle and escape in fish have provided a model for the control of episodic behavior and have bridged the conceptual space between studies on identified neurons of invertebrates and work on neural pathways in the brains of vertebrates (Eaton et al., this issue). The question then becomes, what sort of general principles have been uncovered by the past 25 years of work on insects? The answer documented below is that analyses of insect identified neurons have provided some of the very best data on sensorimotor integration — tracing information from sensory to motor networks — collected in such a way that it can be related to the performance of behavior in intact organisms. There is, however, a most important related question: are there fundamental principles of neurobiology yet to be uncovered for which insect neuroethology could provide especially valuable input? The answer to that question is, we believe, related primarily to the diversity of insects and the detailed information that has been obtained about individual cells. First, there is enough information about specific cells in related insect species that meaningful comparative studies, and construction of evolutionary models of neural circuitry, are possible (see also Murphy, this issue). Second, biochemical and biophysical details are available for specific cells with known relationships to organismal behavior; this makes realistic studies of neural computation possible. We will highlight material that touches on evolutionary and computational neurobiology, and in our conclusion we will offer a brief guide to recently developed resources for comparing and synthesizing information on identified insect nerve cells; electronic databases and analytic software available on the world wide web (WWW). 1.1. The identified neuron approach The idea of a truly ‘identified’ nerve cell means one which can be uniquely recognized in every member of a species (see Kandel, 1976, for an especially lucid discussion of the concept). In insect research, cells have been described as identified under a number of different circumstances; for example when they were found to occupy a constant position in a ganglion and so could be assigned numbers (Cohen and Jacklet, 1967), or sometimes based purely on invariant physiological characteristics (see below). However, in insect neurobiology high resolution neuroanatomy is a tradition and so, typically, anatomical and physiological information are available simultaneously. In its most compelling form, an identified nerve cell means a unique cell that has been anatomically and physiologically characterized, and whose input and output connections are known (O’Shea and Rowell, 1977). C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 In some cases it has been possible only to assign a nerve cell to an identifiable class. While it is tempting to insist that such cells are not truly ‘identified’, the goal of neuroethology is simply to understand how behavior can be explained by the characteristics of neurons, so practicality demands that such cells not be ignored. Indeed, in some sections of the insect brain, e.g. the mushroom bodies, there are so many neurons with such intricate connections that establishing individual identities is problematic, while class identifiability may be enough to allow insights about sensory coding or motor programming to be made (e.g. Mizunami et al., 1993; Strausfeld et al., 1998). It would be easier to discuss identified neurons across insect species if there were a consistent and meaningful scheme for naming or numbering cells. The lack of such a system makes discussion of even one restricted neural system cumbersome (for example, see Hennig, 1988, with reference to well-known cricket auditory interneurons). A three digit system proposed for locust thoracic cells (Robertson and Pearson, 1983) has gained some acceptance, and has been adapted to other species (e.g. Westin et al., 1988). Wide adoption of some guidelines for assigning tags to cells would also facilitate the storage of cellular data in electronic formats (Rowell, 1988) — a process which is underway already (see below). 2. Coding sensory information 2.1. Historical perspecti6e Almost 35 years ago, Kenneth Roeder published the first edition of his monograph Nerve Cells and Insect Behavior (Roeder, 1963, second edition, 1967). In that volume he summarized general principles underlying the neural control of behavior using examples from several insect species. Roeder was quite emphatic that the importance of insects to behavioral neuroscience was due to what he usually termed ‘neural parsimony’: given consistently small body size, this very diverse group manages well-integrated behavioral responses with a relatively small number of (sometimes) large nerve cells (see especially, Roeder, 1959). His monograph was written just before the widespread use of micropipette recordings and single-cell staining techniques led to the accumulation of a significant body of data on individually identifiable neurons. Although Roeder did not use the term Identified Nerve Cells, it was embodied in his work and our chapter title represents, quite intentionally, an echo from his monograph. At the same time, Vincent Dethier published a comprehensive summary of insect senses (Dethier, 1963). Knowledge of primary sensory cells at that time included a considerable amount of cytology, but very 411 little physiology. Since then, studies of individual insect neurons have played a role in elucidating mechanisms of sensory transduction, particularly related to olfaction and vision (e.g. Boekhoff et al., 1993; Stengl, 1994; Hardie and Minke, 1993), and in analyzing stimulus encoding and adaptation processes in receptors (e.g. Basarsky and French, 1991; Torkkeli and French, 1995). In some cases, progress has been made on understanding behavior largely with information about the function of sensory receptors (in particular, see Dethier, 1976), but the greatest insights have come from cases where a group of truly identifiable interneurons that process sensory information can be studied along with organismal behavior. Therefore, we will concentrate on the interneuron level. 2.2. Operating principles The descriptions below are organized around several key concepts that seem to us the main themes that have emerged from work on identified neurons over the past several decades. They also are concepts that will be important foci for future work. 2.2.1. Group/indi6idual differences in central circuitry In vertebrates, some differences in neural structure and function have been described that represent sexual dimorphisms related to behavior. These dimorphisms have been documented in vertebrates only relatively recently (Breedlove, 1992). In insects there are profound differences in neuronal organization that are associated with both sex and social experience. In honeybee brains, the volume of the olfactory glomeruli, and the volume occupied by the Kenyon cells of the mushroom bodies varies systematically depending on whether bees are acting as nurses or foragers (Withers et al., 1993). While the difference between these two groups is normally accompanied by an age difference, the anatomical plasticity is not related in any simple way to age, but rather to the different roles of the individuals in the hive. That individual experience is important to the configuration of this part of the insect brain is consistent with studies on Drosophila indicating that sex and social living conditions influence mushroom body structure (Heisenberg et al., 1995). Other reports (on crickets) have shown that in adult mushroom bodies there is a definable cluster of undifferentiated cells that can give rise to new Kenyon cells under the influence of juvenile hormone (Cayre et al., 1994). This provides a basis for understanding plasticity in adult insect behavior, especially that related to sex-specific response patterns. There is ample information about sexual dimorphism in olfactory processing circuits. Insects respond behaviorally to both plant volatiles and pheromone signals from conspecifics. In fact, it seems that greater progress 412 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 has been made in understanding the sexually dimorphic parts of the CNS related to processing pheromones than to more generalized parts of the olfactory system. In a number of species, specific glomeruli within the antennal lobe are individually identifiable, and there is a male-specific glomerulus for processing information about female attractants (Rospars, 1983; see review in Homberg et al., 1989). (Subsequently, it has been reported that individual glomeruli can be uniquely identified in at least one vertebrate (Baier and Korschung, 1994), but the sexual dimorphisms found in insect olfaction have yet to be reported in vertebrates.) Interneurons of insect antennal lobes (and those projecting into the protocerebrum) are also sexually dimorphic (Matsumoto and Hildebrand, 1981; Burrows et al., 1982; Boeckh and Ernst, 1987). Another place where sexually dimorphic nerve cells have been reported is the visual system of flies. In both blowflies and houseflies, males possess some identifiable visual interneurons which are not present in females, and some visual interneurons that are found in both sexes show structural differences between them (Strausfeld, 1980, 1991; see Fig. 1). The particular differences suggested that the neurons of males selectively process visual motion information from a region of the retinal array related to binocular visual space and are important for precision aerial pursuit of a potential mate (a male-specific behavior). This prediction from anatomical work has been borne-out in subsequent studies with physiological recording (Gilbert and Strausfeld, 1991), and it has led to a demonstration that the appropriate visual information is passed to neck and wing muscula- Fig. 1. Sexual dimorphism at the gross and cellular level of the Calliphorid visual system. Top panel shows a frontal view of the head of male (left) and female (right) Calliphora erythrocephalia. Dotted line encloses area of the male-specific ‘acute’ zone which represents that area of visual space where males detect and follow females. Bottom panel is a drawing of a golgi-impregnated, male-specific interneuron with dendrite positioned in the lobula so as to receive input from the acute zone. Inset at bottom left shows approximate viewing angle for visual afference to the cell. For scale, diameter of soma is approximately 25 um. Taken with permission from Strausfeld (1991). C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 ture by a cluster of individually identifiable premotor interneurons (Gronenberg and Strausfeld, 1991). Thus there is abundant documentation that sexual and other group differences are significant both at the level of the neuropil and tract organization of the CNS, but also at the level of individual neurons — and especially in olfactory, visual, and association areas (mushroom bodies). Such differences are profound in the sense that they underlie fundamental differences in sensory capacity between females and males, and they are an important context within which future information about identified neurons and circuits must be evaluated. 2.2.2. The importance of temporal dynamics Rhythms are important to neural function on both the sensory and motor sides of the CNS. Rhythms related to identifiable cells have now been reported in several sensory systems and they occur across time scales ranging from milliseconds to hours. For example, far toward the visual periphery, the numbers of synapses between photoreceptors and optic interneurons, as well as the diameter of interneuron processes, have been reported to undergo daily fluctuations in flies (summary in Meinhertzhagen and Pyza, 1996). These are truly circadian changes that persist when animals are brought to constant lighting conditions. At a much finer time scale, the olfactory system processes sensory information within the context of rhythms. In locusts, olfactory interneurons that project from the antennal lobe (the initial CNS relay for olfaction) to the mushroom bodies encode information on odorant identity. Each interneuron responds with impulses to several specific odors or components of odor mixtures, and for each given odor a slightly different subset of the interneuron population responds (Laurent and Davidowitz, 1994). The activity of all interneurons responding to any odor are spread out in time and are superimposed on subthreshold electrical oscillations occuring throughout the cell population at 20 – 30 Hz. Some cells might respond early in the stimulus-induced oscillations, others late, or others at various odorantcharacteristic times. Thus the neuronal signature of any odorant is a time-varying ensemble code that is characterized by oscillatory synchronization of key interneurons (Laurent et al., 1996). In recent work with honeybees it has been shown that picrotoxin, which does not alter the odorant specific response of projection neurons but which disrupts oscillatory synchronization, abolishes behavioral discriminations that bees make between chemically similar compounds without abolishing discriminations for dissimilar odorants (Stopfer et al., 1997). This interesting study implicates oscillatory synchrony in fine sensory discriminations. The dynamically coded information of the projection neurons ultimately becomes represented as sequences of 413 (small numbers of) activated Kenyon cells within the very large population of Kenyon cells found in the mushroom bodies. The Kenyon cell population has been shown in flies to be necessary for odor based learning (e.g. deBelle and Heisenberg, 1994). It is currently not known why information about odorants must be encoded dynamically in time, but presumably it has to do with some fundamental aspects of olfactory recognition and learning — and this strategy may be a general one (see discussion in Laurent, 1996). Finally, the olfactory system is a place where cells may show particularly long-lasting temporal variations in activity patterns. In moths, pheromone related neuronal activity passes through the antennal lobes and mushroom bodies and ultimately activates brain cells with axons descending toward thoracic motor centers. These interneurons often produce trains of impulses which can outlast stimulus application by tens of seconds to minutes (Olberg, 1983; Kanzaki et al., 1991). In addition, some uniquely identifiable cells show state-dependent changes in activity: if they have little activity when a stimulus is applied, they markedly increase their rate of impulse production; but if an identical stimulus is applied when they are already active, they show a stimulus related drop in impulse activity (Olberg, 1983; Kanzaki et al., 1994; see Fig. 2, top). This state dependency has been called ‘flip-flopping’ — because such cells have been observed to change firing state spontaneously. There is some evidence that these changes in firing state correlate with the points at which animals change direction as they zig-zag up an odor plume (either walking or flying) toward the source of pheromone (e.g. Olberg, 1983; see Fig. 2, bottom). Consistent with the idea that such descending interneurons contain higher-level information to guide flight, they often are multimodal and respond to visual or mechanosensory input in addition to olfactory cues (see any of the papers cited above). 2.2.3. The computational sophistication of indi6idual neurons A considerable amount of research has been conducted on processing visual input and the relay of visual and mechanosensory information toward motor centers. Such work has highlighted the computational power that is present at the level of individual nerve cells. Sensory systems typically display ‘subsystems’ for processing different stimulus parameters that are biologically important. Thus, information derived from the insect retina is processed by separate interneuronal groups for extraction of such features as color and movement. Identified interneurons of flies have recently provided clear examples of how both intrinsic biophysical and synaptic features contribute to motion detection subsystems in vision (see Egelhaaf and Borst, 1993, for a digestible review). This analysis is particularly satisfy- 414 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Fig. 2. Temporal dynamics of olfactory interneurons and moth behavior. Top panel displays state dependent response of a single descending interneuron of Manduca sexta (recorded from the axon in the cervical connective) to puffs of pheromone blend on the ipsilateral antenna. In trace (a) stimulus caused excitation of the cell from low background activity. Trace (b) demonstrates that the same stimulus caused the cell to decrease firing if it was already highly active. Scale bar 1s, 40 mV. Bottom panel shows activity profile of descending interneuron from Bombyx mori in relation to turning behavior. Marker pulses at bottom indicate when puffs of pheromone were applied to one antenna, ipsilateral or contralateral as indicated. Spike frequency diagram above shows that this descending interneuron fired at a high rate for ipsilateral stimulation and a low rate for contralateral stimulation. The firing state of the interneuron correlates with antennal position as shown in the schematics, and also with turning behavior (i.e. the insect turns toward the side with the lower antenna). Bombyx males walk toward a source of female pheromone. Scale bar 10 s, 20 spikes per s. Taken with permission from Kanzaki et al. (1991) (top panel) and Olberg (1983) (bottom panel). ing since there is a long history of behavioral analysis of fly vision which led to some of the first formal models in neural computation (see Reichardt, 1987), and these are now being given cellular substance. A set of identified cells, referred to generally as tangential cells, collects information from local retinotopic movement detectors and generates signals that seem to be used in visual orientation tasks. Optomotor stabilization is an orientation response that depends on cells tuned to wide field motion, but this tuning carries with it an ‘automatic gain control’ so that the spatial tuning of the cells is sensitive to image velocity. This feature of tangential cell physiology can now be explained quantitatively as part of interactions between excitatory and inhibitory inputs to the dendrites of specific tangential cells that are the basis for direction selectivity (Borst and Egelhaaf, 1990; Kondoh et al., 1995; Single et al., 1997). Target orientation is a separate response that requires different interneuron characteristics — tuning for small moving objects. Tangential cells displaying this feature achieve it by synaptic interactions with other tangential cells (specifically a type which uses GABA to reduce responses to coherent large field motion-see Fig. 3) (Warzecha et al., 1993; Egelhaaf et al., 1993). For both of these computations, the fly visual pathway offers the possibility of directly observing where and how they happen. Many of the interneurons can be observed with intracellular recording electrodes, and Ca++ sensitive indicators; and they can be removed selectively from the circuit by photoinactivation (Warzecha et al., 1993; Egelhaaf et al., 1993; Egelhaaf and Borst, 1995; Borst, 1996; and see Fig. 3). With so much information about one functional subset of sensory interneurons, it will be possible to answer questions about the rationale for the circuit’s design (e.g. see Bialek et al., 1991; Haag and Borst, 1997). The visual motion information extracted from the retinal array ultimately is relayed to motor centers — primarily, but not exclusively, at thoracic levels — for guidance of locomotion and other behaviors. Large-caliber interneurons performing this function were actually the first sensory nerve cells studied as individuals (see Rowell, 1971 for a review), long before afferent networks in the distal optic neuropils of the brain were explored physiologically. Now that a number of major descending visual interneurons have been identified and characterized, a feature that is common among them is apparent: they typically display parallel encoding of information from several receptor types. For example, studies on dragonflies (Olberg, 1981), several dipteran species (Bacon and Strausfeld, 1986), and locusts (O’Shea et al., 1974; O’Shea and Rowell, 1977; and see below) have described individual interneurons that combine visual afference with mechanosensory signals from various hairs and proprioceptors on the head, or C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 415 Fig. 3. Dendritic contributions to the computation of visual motion in the fly, Calliphora erythrocephala. Bottom diagram shows the major branches of a VCH-cell in the right half of the brain. VCH is believed to provide inhibitory input to other tangential cells so as to give rise to tuning for small object motion. The main arborization on the right is located in the ventral part of the lobula plate, the small arbor on the left is in the ventrolateral brain. The cell was excited under two different stimulus conditions either by front-to-back motion in the ipsilateral visual field or back-to-front motion in the contralateral field, after the cell had been injected iontophoretically with the Ca2 + indicator fura-2 [illustrated schematically, top panel]. Color images in middle panels (128 × 100 pixels; 0.1 s exposure time) indicate the relative change in fluorescence (DF/F, without background subtraction) at 380-nm excitation wavelength induced by the two types of motion stimuli 7.5 s after stimulus onset. Negative changes in fluorescence indicate an increase in Ca2 + concentration. Ipsilateral motion leads to Ca2 + accumulation only in the lobula plate arbor. In contrast, contralateral motion leads to Ca2 + accumulation in both arbors in the lobula plate and ventrolateral brain. Labelled arbors are likely to be the postsynaptic sites of the corresponding ipsi and contralateral input elements. Taken with permission from Egelhaaf et al. (1993). associated with the antennae. It is clear that this parallel encoding of visual and mechanosensory information makes sense for efficient guidance of flight. At least two significant themes emerged from the work on descending visual-multimodal interneurons; one illustrates a concept of sensory organization at the cellular level better than almost any other example, and the other raises a cautionary note. First, a group of cells in locust, the ‘tritocerebral commissural giant’ (TCG) and three descending neurons (DNs), combine wind and visual information in behaviorally coherent ways (Bacon and Tyrer, 1978; Griss and Rowell, 1986; Rowell and Reichert, 1986). They clearly detect not just visual motion, or wind across the head, but rather meaningful combinations of directional wind and visual afference that would be associated with various types of course deviations during flight (see Reichert, 1989). This phasic feedback information is then interfaced with the flight motor to correct perturbations. As such, these identified interneurons provide one of the clearest and most elegant examples of single cells as feature detectors. Second, it is clear that large volumes of physiological data do not always translate into a satisfying understanding of a cell’s role in natural behavior. The ‘descending contralateral movement detector’ (DCMD) of locusts is probably the most-studied of any identified neuron. Its response to visual input was extensively described from extracellular and then from intracellular recordings, and it was described as responding to small novel objects entering a wide area of the visual field — presumably to arouse the animal, or trigger startle behavior such as a jump (e.g. citations above, or Pearson and O’Shea, 1984). However, in more recent work, it has become clear that DCMD is not necessarily tuned to small moving objects, but rather to objects expanding in the visual field that are on a collision course (Rind and Simmons, 1992; Simmons and Rind, 1992; Judge and Rind, 1997). This suggests that DCMD may be involved in crash-avoidance in flying locusts (e.g. Robertson and Reye, 1992; Gray and Robertson, 1997b) or triggering escape in stationary locusts (e.g. Holmqvist and Srinivasan, 1991, for flies), but the humbling truth is that its behavioral role is still not fully established. 2.2.4. Coarse coding and computational mapping Many insects possess a wind-sensory system that maps the world at several levels of the CNS. Its general function — localization of predators by way of wind cues — has been appreciated for several decades (e.g. 416 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Roeder, 1963), but the details of its sensorimotor transactions have been understood only recently. The cerci are paired sensory appendages found on the abdomen of insects from more than 10 different orders (Edwards and Palka, 1991). The types of cercal receptors vary by species, but most possess at least two types of mechanoreceptors: filiform hairs that detect wind or near-field acoustic signals (e.g. Edwards and Reddy, 1986; Boyan and Ball, 1990), and bristle hairs that are touch-sensory (e.g. Murphey, 1985). The numerous filiform hairs (e.g. about 200 – 2000 per adult cercus, depending on species) are each associated with a primary sensory neuron that is individually identifiable. This was initially obvious in cockroach where the hairs line up along the cercus in ordered columns (Nicklaus, 1965; Dagan and Camhi, 1979), but it was recently verified to be true in cricket (Landolfa and Jacobs, 1995). The issues that have been raised about sensory coding by cercal systems are seen dramatically in first instar cockroach nymphs. They possess only two filiform hairs per cercus. So the best directional information that the set of sensory receptors can display in the CNS is defined by the spatial tuning of the four hair afferents (Dagan and Volman, 1982). Basically, each of the hairs responds mostly to wind puffs from one of the four quadrants around the animal (Fig. 4). Although these nymphs possess fewer receptors than adults (by two orders of magnitude) they display behavioral responses to wind that are at least, as well directed as those of adults (Dagan and Volman, 1982). Obviously, this system displays ‘coarse coding’ — the overlap of a relatively few broadly tuned receptive fields — that is not inconsistent with accurate spatial resolution at the behavioral level. The usage of this sort of cercal information in adults involves keeping track of many more primary afferents and interneurons. The axons of the receptor cells associated with each filiform hair enter the terminal ganglion, where they project to a neuropil, the cercal glomerulus. The particular region of neuropil where a filiform afferent terminates in the adult cricket is based largely upon the direction of wind to which it is sensitive (Bacon and Murphey, 1984). High-resolution analysis of the territory occupied by uniquely identified cercal afferent projections has shown that the sensory field around the animal is represented as a map of wind directions along a spiral shaped contour within the cercal glomerulus (Jacobs and Theunissen, 1996; and see Fig. 5). This is an elegant example of a sensory pathway displaying information not by way of topographic projection (position on the cercus does not strictly determine where afferents project), but rather by functional criteria to produce a ‘computational map’. The widespread nature of computational maps has been recognized (Knudsen et al., 1987). Fig. 4. Identifiable filiform hair receptors and the encoding of directional wind-sensory information. Data are from first instar nymphs of the cockroach Periplaneta americana. Top (A): scanning electron micrograph shows a ventro-caudal view of the abdomen; arrows point to the two filiform hairs (‘lateral’ and ‘medial’) on the right cercus. Scale bar is 200 mm. Bottom [B]: polar plots give the average frequency of action potentials evoked in the sensory neuron associated with each of the four hair receptors as wind was delivered from different angles in the horizontal plane. Medial and lateral hair receptor response fields are indicated by dotted and solid lines as indicated. For scale, maximal response of the medial hair receptors to standard wind puffs was approximately 300 impulses per sec. Taken with permission from Dagan and Volman (1982). Extraction of information from the cercal map of wind-sensory space is performed by interneurons with cell bodies in the terminal ganglion. These cells have dendritic arborizations within the cercal glomerulus, and large caliber axons ascending the nerve cord. The axons of these second order cells have the largest C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 417 Fig. 5. Complexity of wind afferent map in adult crickets, and the directional information extracted by ascending ‘giant’ interneurons (GIs). Top panel (A) displays directional information encoded by two pairs of GIs. Polar plot on right gives response of Left and Right GIs 10 – 3a (dotted line) and left and right GIs 10–2a (solid line) to winds from different directions in the horizontal plane around the animal. As shown by schematic illustration at left, distance from the origin is equivalent to spike rate such that the maximal spike rate for each cell is scaled as a value of 1.0 and is at perimeter (for example, maximum average spike rate for 10 – 2a was 20 spikes per s). Bottom (panel B): outline of terminal abdominal ganglion as seen from a dorsal view. Cubic outline encloses the cercal glomerulus. Clouds of color within the glomerular region represent the probability density functions for the terminal varicosities of identified primary wind-afferent fibers. The color of each density cloud indicates its directional tuning with respect to the animal’s body axis (key to directions is shown by inset color wheel, yellow indicates stimuli directed toward animal’s head. Afferents from each cercus form a continuous hemi-map on one side of the ganglion and the hemi-maps are mirror images of each other across the midline. Bottom (panel C) shows somata and axons of the identified GIs as seen in dorsal view of terminal ganglion. For clarity, only GIs on one side of the nerve cord are shown. 8, 9= nerve roots; CN, cercal nerve; for scale, soma of 9 – 3a is approximately 50 um in diameter. Panel A adapted from Miller et al. (1991), Panel B taken from Jacobs and Theunissen (1996), Panel C adapted from Jacobs and Murphey (1987); all with permission. caliber in the CNS; Therefore, they are often called ‘giant interneurons’ (GIs), and they rapidly conduct impulses from cercal receptors to motor cells located in the thoracic ganglia. A reconstruction of the set of identified GIs in adult cricket is displayed in Fig. 5 (cockroaches and other orthopteroid species have similar sets of GIs but the exact number varies in each and the naming schemes differ). The connectivity between specific GIs and cercal afferents has been analyzed in several species (e.g. cricket — Bacon and Murphey, 1984; cockroach — Daley and Camhi, 1988; Hamon et al., 1994; locust — Boyan and Ball, 1989). While details are beyond the scope of this chapter, the net effect of cercal afferent input is to elaborate wind-sensory receptive fields, with most of the GIs responding to winds only from certain directions around the animal (cockroach - Westin et al., 1977; cricket — Tobias and Murphey, 1979). How then is information about wind location represented as it is sent to the thoracic level (closer to the motor system)? A recent, careful analysis of information coding by cricket GIs has revealed an interesting regularity to their receptive field organization (Miller et al., 1991). A subgroup of cricket GIs that responds to very low 418 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 velocity winds consists of two bilateral pairs of interneurons. As a group, these four cells have remarkably similar shaped receptive fields, and their points of peak sensitivity are uniformly distributed at 90° intervals around the horizontal plane. Thus, they monitor wind from each of the four quadrants around the animal (Fig. 5), and provide spatial sensory information by way of coarse coding (Theunissen and Miller, 1991) not dissimilar to that which was seen in the first instar nymph. There are other GIs (and ‘non-giants’ — Baba et al., 1991) that respond to wind in different velocity and/or acceleration ranges, so the adult system covers the full wind environment by having several subsets of cells that fractionate the spectrum of wind velocity (or acceleration) each coding basic directional information (Shimozawa and Kanou, 1984; Miller et al., 1991). A recent re-analysis of GI wind directionality in cockroach (Kolton and Camhi, 1995) has shown that each of two GI subsets (3 pairs of ‘dorsal’ GIs and 3 or 4 ‘ventral’ GIs) carries coarsely coded, parallel information about wind stimulus direction. One reason why there may be several subsets of GIs coding parallel spatial information is, as suggested above, to fractionate the spectrum of wind velocities or accelerations. However, there may be other reasons. In both cockroach and cricket the GI subgroups correlate with anatomy; GIs axons that ascend within ventral tracts of the nerve cord (vGIs) generally are larger in diameter than those that ascend in dorsal tracts (dGIs). Therefore, considering that reaction time is crucial for escape from predators, Camhi and Nolen (1981) proposed that an escape response triggered by wind is controlled in a sequential manner; initially by activity in the vGIs, and only subsequently by the more slowly conducting dGIs. Another possibility, is that control by the two GI subgroups differs depending upon locomotor status. In both cockroach (Daley and Delcomyn, 1980) and cricket (Kohstall-Schnell and Gras, 1994) the vGIs are inhibited during walking (especially during fast walking), whereas dGI responsiveness to wind is enhanced. Therefore, it may be that vGIs are important for escape in an animal that is standing or walking very slowly, but that the dGIs are a channel for evasive responses in an animal that is already running. Consistent with this idea, vGIs have been shown to be inhibited during flight, but dGIs retain sensitivity to wind puffs during flight, and display appropriate motor outputs to participate in evasive responses during flight (Ritzmann et al., 1982; Libersat, 1992; Ganihar et al., 1994). To arrive at a better understanding of why there may be multiple displays of sensory information within the GI system, as well as other basic questions, comparative studies of nymphal and adult interneurons might be especially valuable (both nymphs and adults walk, but only adults fly). 2.2.5. Neural parsimony and the decoding of central information In order for sensory information to become overt behavior, it must be delivered to a motor system. It is clear that in many cases — especially those studied so far in vertebrates — this requires decoding of information that is distributed across a large population of sensory interneurons. The computational mechanisms by which this occurs are not yet entirely clear (e.g. Georgopoulos, 1990; Groh et al., 1997). In insects these sorts of computations involve especially tractable numbers of interneurons. Two systems where identified interneurons are known to carry crucial information that directs motor activity are found in the auditory system of crickets and the wind and somatosensory systems of cockroaches. The auditory system may demonstrate the greatest neural parsimony of central elements controlling behavior. Acoustic orientation by crickets is a complex behavior and it is species specific (Huber et al., 1989; Boyan, 1993 are recommended sources of information on cricket auditory behavior and comparative auditory organization). Orientation requires that an animal identify and localize a sound source. The relationship between these two processes is controversial and may differ across the various insect species that use acoustic communication (e.g. crickets — Pollack, 1986; Stabel et al., 1989; Doherty, 1991; grasshoppers von Helversen and von Helversen, 1995). We will restrict our summary to the processes of sound localization. When crickets detect a sound, they face the task of choosing a direction in which to orient: if an acoustic signal is of low frequency (say 2–15 kHz, and with appropriate temporal structure for the song of a conspecific) a cricket usually will turn toward the signal source. The decision about where to turn may follow an algorithm as simple as ‘turn to the side of the ear more strongly stimulated’ (e.g. Horseman and Huber, 1994a). This computation is probably made by cells in the brain, based on signals received from several key interneurons that send information to the brain from thoracic auditory areas. In particular, paired ascending interneurons (usually referred to as AN1) are tuned to appropriately low frequencies, and faithfully copy the temporal pattern of a calling song (see Schildberger et al., 1989). When sound comes from one side, the AN1 on that side is more strongly activated than its contralateral homologue and the animal turns toward the sound source (the side of the more active AN1). If an AN1of the cricket Gryllus is hyperpolarized while song is delivered, animals reverse direction and turn away from the sound source (toward the side of the originally less-active AN1) (Schildberger and Hörner, 1988). In the cricket Acheta, animals with the equivalent cell unilaterally photoablated have difficulty reaching an attractive sound source (Atkins et al., 1984); and ani- C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 mals engage in phonotactic circling when the threshold of this interneuron is lowered unilaterally by application of hormone (Stout et al., 1991). These sorts of data suggest that the relative level of activity in the left vs. right AN1 determines turning direction. A second pair of cells, usually referred to as AN2, may also contribute, but seem to be less crucial for localizing calling song than the AN1 pair (see Horseman and Huber, 1994a,b). The AN2 cells may also be involved in predator evasion (see below). Nonetheless, positive phonotaxis can be modeled effectively by assuming a bilateral comparator in the brain that needs input from only one or two pairs of acoustic interneurons with broadly tuned spatial receptive fields (Huber et al., 1984; Pollack, 1986; Stabel et al., 1989; Horseman and Huber, 1994b). If some temporal filtering functions are added, (their exact placement is not agreed upon) then this simple comparator might explain the orienting component of important cricket behaviors such as mate finding, courtship, and intermale aggression. When presented with high frequency sounds (say 20 – 80 Khz) crickets more typically turn away from a sound source. This has most often been studied in flying insects and seems to be the mechanism by which predators emitting ultrasound (bats) are evaded. While in flight mode, tethered crickets respond to a source of ultrasound by producing motor responses that create contraversive turns (Moiseff et al. 1978). A pair of identified interneurons (called int-1 in Teleogryllus, and probably equivalent to AN2 in Gryllus) have been linked with evasive acoustic behavior. Once again, the origin of turning ‘commands’ is probably the brain, based upon inputs received from the pair of ascending AN2/int-1 cells. Evasive turning can be initiated by stimulating one member of the interneuron pair electrically (the animal turns away from the active int-1), and evasive turning from ultrasound can be blocked if this cell is inactivated (Nolen and Hoy, 1984). A bilateral comparator might also explain the orientation of this negative phonotactic response (see Hoy et al., 1989, for discussion of a general circuit model). Comparative studies have provided insights here, and may be useful for work in the future aimed at understanding the sensorimotor circuitry. For example, mantids contain a pair of identified ultrasound sensitive interneurons, but they receive input from a midline ‘cyclopean’ ear, and are non-directional (Yager and Hoy, 1989). Evasive responses of flying mantids do not display directionality (Yager et al., 1990). The escape system of cockroaches shows some formal similarities to the systems for phonotactic orientation in crickets, but displays control by a larger set of sensory interneurons, and shows multimodal control by at least two sensory systems. When a wind puff is directed at a stationary cockroach (Camhi and Tom, 419 Fig. 6. Thoracic circuitry identified in the cockroach for converting GI activity into leg movements that orient the escape response. Each neuronal component in this schematic summary represents a population of bilaterally paired neurons, many of which have been identified as individuals. For simplicity, only vGIs and TIs with axons on the right side of the nerve cord are shown. The expanded image of the metathoracic ganglion (T3) shows details of some established connections. TI, thoracic interneuron (those receiving input from ventral GIs-as shown-are referred to as ‘type A’: these TIs have ventromedial (VM) branches, where connections from GIs appear to be made). Taken from Ritzmann and Pollack (1990) with permission. 1978) or a cricket (Gras et al., 1994; Tauber and Camhi, 1995) the animal turns away from the direction of the incident wind, and then runs (crickets also may jump, and generally display a greater diversity of responses to wind than cockroaches — Baba and Shimozawa, 1997). Abundant evidence links turning behavior with the wind-sensory GIs that ascend within the nerve cord (see above) to activate premotor cells in the thoracic ganglia. In particular, the vGI subset of cockroach activates identified premotor interneurons which can support the leg movements that underlie turning (Ritzmann, 1981; Ritzmann and Pollack 1986; Ritzmann and Pollack, 1990; Figs. 6 and 7 for an example of wind-evoked escape behavior). Furthermore, specific enzymatic deletions of vGIs can cause the direction of escape turns to be altered, indicating that it is specifically the readout of vGI wind sensory information that is used to orient escape turns (Comer, 1985; Comer and Dowd, 1993). The vGI subset consists of four bilaterally paired interneurons. It is clear that the laterality of a wind puff is represented by the laterality of GI impulse activity in the CNS (e.g. Westin et al., 1977; Smith et al., 1991). Wind from one side of the animal activates the vGIs on the ipsilateral side of the nerve cord more strongly, and also at a shorter latency, than those on the contralateral side. The algorithm for choosing a turn direction may be as simple as ‘turn away from the side on which the vGIs display more wind-evoked activity’ (for example, see Dowd and Comer, 1988; Camhi and Levy, 1989). Consistent with this notion, specific unilateral vGI lesions can cause animals to turn inappropriately toward winds delivered from the same side as the lesion (see 420 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Comer and Dowd, 1993). More specifically, experimental tests with selective GI stimulation have shown that timing (relative latency) of GI activity cannot explain turn direction, but relative levels of spiking in left vs. right GIs can explain it (Liebenthal et al., 1994). It is far less clear how a specific turn angle is chosen, although it may depend upon the relative level of activity among the GIs with differing directional sensitivities (e.g. Levi and Camhi, 1994). The thoracic motor circuitry of cockroaches operates as if it compares not only the relative level of activity in the bilateral pairs of GIs, but also in other interneuron systems. When the GIs are completely removed, escape can be elicited via tactile sensory pathways that descend to thoracic ganglia from the antennae (Comer et al., 1988; Burdohan and Comer, 1990; Stierle et al., 1994). This is not a question of functional substitution; rather, this one particular motor response is normally under Fig. 7. Multiple GI systems can explain initiation of directed escape movements by cockroaches in response to multiple sensory modalities and types of predators. Panels on left show reconstructions of escape responses from videotapes, Panel on right shows two identified ‘giant’ interneurons that are involved in the control of these types of responses. (A) Escape triggered by the attack of a wolf spider (red). Spider’s position prior to movement is labeled 0, front of spider’s body and right foreleg are shown on frames 4 and 8. Cockroach (black) began turning between frames 8 and 9 subsequent to antennal contact. (B) Escape triggered by strike of a marine toad (green). Toad’s initial position is labeled 0, front of toad’s body and position of tongue (dotted outline) are shown on subsequent frames as noted. Cockroach (black) began moving between frames 4 and 5 prior to contact and tongue extension. Scale bar = 2 cm and it applies to panels A and B. (C) Reconstructions of two cells injected with cobalt hexamine. Descending mechanosensory interneuron (right DMIa-1; red) responds to antennal contact. Its activity, and that of other DMIs, is correlated with direction and angle of escape turns evoked by antennal contact (such as A; see Ye and Comer, 1996). DMIs have the largest caliber descending axons in the nerve cord, and are similar in size to the classic giants. Ascending giant interneuron (left GI-1; green) responds to wind. Its activity, and that of other ventral GIs, is necessary for properly oriented escape turns to wind stimuli (such as B, see for example Liebenthal et al., 1994; Comer and Dowd, 1993). Scale bar = 100 um. Panel A & B taken from Comer et al. (1994), panel C from Comer and Dowd (1993). C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 multisensory control. It is now known that there is a larger somatosensory system involved in eliciting escape (Comer et al., 1988; Ritzmann et al., 1991; Comer et al., 1994; Pollack et al., 1995). Studies with real predators indicate that under normal circumstances the windsensory pathway for escape is important to detection of large predators that generate wind cues by their movements (Camhi et al., 1978). However, the antennal touch-sensory system is particularly important for detecting smaller predators — such as spiders and other insects — that are able to approach cockroaches closely (Comer et al., 1994; Fig. 7). The system for touch evoked escape displays at least some of the cellular principles that have already been defined for the wind-sensory system. Two bilateral pairs of interneurons carrying antennal touch-sensory information from the head ganglia to the thoracic ganglia have been identified (Burdohan and Comer, 1990, 1996) and they have been called Descending Mechanosensory Interneurons (DMIs). Together they possess the largest diameter axons in the cervical connectives, making them, in effect, descending ‘giants’ (Fig. 7). Touching one antenna activates the DMIs on the contralateral side of the nerve cord more strongly, and also at a shorter latency, than those on the ipsilateral side. So an algorithm that might explain touch evoked escape would be ‘turn toward the side of the DMIs with more, or earlier, touch-evoked neural activity’. Section of a cervical connective to block this system unilaterally causes animals to turn typically toward, rather than away from, abrupt stimuli touching the antenna contralateral to the lesion (Comer et al., 1994) — supporting the idea that the relative level of DMI activity might determine turn direction. This notion has been tested more directly, since the DMIs can be recorded in behaving animals during the performance of escape turns (Ye and Comer, 1996). These recordings have revealed that the relative number of impulses in the DMIs on each side of the CNS, not their relative timing, is correlated with the direction, and specific angle, of escape turns evoked by touching an antenna (Ye and Comer, 1996). This makes a bilateral comparator model particularly suitable for explaining DMI control of escape. While it is clear that the thoracic premotor interneurons previously shown to receive wind-sensory vGI input also receive some tactile sensory input (Ritzmann et al., 1991; Ritzmann and Pollack, 1994), the interneurons providing that input have not yet been determined. If the DMIs and GIs converge upon the exact same thoracic premotor cells, then there will be some interesting issues raised about coordination between tactile and wind-sensory control of behavior; The DMI pathway represents antennal touch information with a contralateral bias, and animals turn ipsiversively with respect to the most active DMIs; however the GI 421 pathway displays an ipsilateral bias and animals turn contraversively with respect to the side of the more active GIs (see Comer et al., 1994). Thus if there is one readout network for both the ascending (GI) and descending (DMI) system, then it must switch its operating logic depending upon which input it is handling. This remains to be determined, but the DMIs and GIs should provide some interesting tests of movement control by very small populations of sensory interneurons and of principles underlying multisensory integration. 3. Patterning of motor output 3.1. Historical perspecti6e The investigation of the role of identified neurons in generating the motor patterns that underlie behavior of insects has a history at least as long as that of the general field of the neuronal control of behavior. This history has been recounted, at least in part, in several reviews (e.g. Hoyle, 1983; Robertson, 1987b; see also Burrows, 1996) and is not the major focus of the current chapter. Suffice it to say that soon after the development of intracellular microelectrode techniques, recordings were taken from insect motor neurons (e.g. Hagiwara and Watanabe, 1956) and some of the first intracellular recordings taken from neurons during expression of behavior in any organism were made from cricket neurons during singing and the generation of flight-like rhythms (Bentley, 1969a,b). The original difficulty with this approach was the problem of identification which was only truly solved with the development and sophistication of intracellular staining techniques (e.g. Pitman et al., 1972; Stewart, 1978). Nevertheless, neurons can be identified by their physiological characteristics alone (e.g. much of the work on the stomatogastric system of lobsters, Selverston et al., 1998). In insects this approach limits the investigator, for the most part, to intracellular studies of motor neurons which can be identified according to the muscle they innervate; an identification made easier with invertebrates because of the low number of motor neurons innervating each muscle. Significant in this regard was the pioneering work of Hoyle and Burrows (1973) on the motor supply of the locust hindleg which laid the groundwork for intracellular investigations of the control of the locust jump (Heitler and Burrows, 1977a,b) and a rich subsequent literature on the control of jumping, walking and posture in locusts (see Burrows, 1996). In a similar fashion, for the control of locust flight, detailed descriptions of the motor patterns (Wilson and Weis-Fogh, 1962) were followed by intracellular recordings from motor neurons identified on physiological grounds (Kendig, 1968) and subsequent 422 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 anatomical descriptions of the motor neurons (Bentley, 1970; Burrows, 1973; Tyrer and Altman, 1974). Although information on the firing pattern of interneurons could be inferred from motor neuron recordings (see Burrows, 1977), in both cases the premotor circuitry remained a mystery until techniques improved such that interneurons could be identified reliably and with relative ease (e.g. for flight, Robertson and Pearson, 1982, 1983). 3.2. Operating principles We have chosen to illustrate the following discussion with particular but not exclusive reference to the locomotion of locusts (including walking, jumping and flight) simply because the study of these motor activities is well advanced and features prominently in the literature. We note in passing, however, that rivals for attention are increasing in number. As one example, insect stridulation is a behavior that has a respectable pedigree in the field of neuroethology (see Elsner and Popov, 1978; Elsner, 1983; von Helversen and von Helversen, 1994; for reviews). It also exhibits characteristics that lend themselves to an identified neuron approach in that the behavior is rhythmic, primarily generated by central circuits, and resistant to the manipulations necessary to enable intracellular recording. Numerous interneurons in different species of grasshopper have now been described that are involved in stridulatory rhythm generation (Hedwig, 1986a,b, 1992a,b, 1994; Gramoll and Elsner, 1987; Lins and Lakes-Harlan, 1994; Ocker and Hedwig, 1996). Similarly, interneurons involved in cricket stridulation, which is generated by rhythmical movements of the wings rather than the legs, as is the case in grasshoppers, have been described (Hennig, 1990a,b; Otto and Hennig, 1993). A safe prediction would be that more detailed descriptions of neuronal mechanisms underlying this motor activity will not be long in appearing. 3.2.1. Defined circuits One of the primary advantages of the identified neuron approach is the ability to accumulate data from the same neurons and synapses in different individuals and thus to reconstruct faithfully a circuit that explains how information is coded and/or how motor patterns are generated. For motor patterning in a variety of invertebrates there has been considerable success in this venture (see Selverston et al., 1998; Calabrese and De Schutter, 1992; Marder and Calabrese, 1996) because the circuits contain few neurons and one can be confident that most, if not all, of the neuronal participants have been identified. In vertebrates the notable success has been necessarily confined, in all but a few cases (see e.g. Eaton, this issue; Buchanan, ibid), to the investigation of classes of neurons (e.g. Grillner et al., 1991; Grillner, 1996; Marder and Calabrese, 1996). In insects the success in defining completely circuits that generate motor patterns is limited. For a detailed review of the neuronal and circuit properties underlying insect motor activity there is a recent book that does the topic justice (Burrows, 1996). If there is a single message to be taken from this review, with reference to insect motor pattern generation, it is that a focus on single identified neurons and attempts to ascribe to them particular functions, has yielded little of lasting value. The original, apparently complete, descriptions of the locust jumping circuit (see e.g. Pearson and O’Shea, 1984) were flawed (Gynther and Pearson, 1986, 1989). The description for the locust flight circuit (Robertson and Pearson, 1985a,b; Robertson, 1986) is woefully incomplete, even though a computer model of the known circuit can produce rhythmic activity similar to the deafferented flight rhythm (Grimm and Sauer, 1995). Moreover there have been no significant additions to this circuit since its first description, and there is little information on the possible role of local neurons. The latter is deemed surprising (Burrows, 1996) given the prominent role of local interneurons in the control of insect leg movements (e.g. for walking, Pearson and Fourtner, 1975; Schmitz et al., 1991; Wolf and Laurent, 1994; Büschges et al., 1994; Büschges, 1995; Wolf and Büschges, 1995). There may be good reasons, functional or otherwise, for a negligible role for local interneurons in the control of wing movements, but until our knowledge of the circuitry is improved no conclusions can be drawn. The complexity of motor circuits and the allure of identified neurons (Robertson, 1989) may to some extent explain the failure to define completely a unitary circuit for any insect motor act. The problem may also lie in the fact that the circuits fall in the middle of a continuum of complexity from the stomatogastric system to the lamprey swimming system, and probably closer to the lamprey. For the locust flight circuit, interneurons can be individually identified, encouraging a circuit-breaking approach, yet the numbers of neurons involved is several hundred at a very conservative estimate. There are around 80 motor neurons for the wing muscles. A partial catalog of only flight steering neurons in the mesothoracic ganglion contains 28 neurons (Rowell and Reichert, 1991). Unpublished catalogs in several laboratories contain descriptions of many more interneurons whose activity is modulated with the flight rhythm. Finally, circuit-breaking by paired intracellular recordings from the neuropil segments of flight neurons is time-consuming, difficult and to a large extent arbitrary. The successes in insect locomotor systems lie, therefore, not with defined circuits of identified neurons which, even if complete, would be idiosyncratic (Robertson, 1989), but with more general concepts (e.g. C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 for flight, Robertson, 1995) that are developed, or are supported, using the identified neurons as tools to gain access to the systems. The current areas of most intense research interest in motor systems include the organization and reconfiguration of functional circuitry, the role and mechanisms of neuromodulation and the afferent regulation of output (Kristan, 1992; Pearson, 1993; Morton and Chiel, 1994; Katz, 1996). 3.2.2. Organization and reconfiguration The locust flight system has been described as a single operating circuit with neuronal elements distributed throughout six serially homologous, segmental neuromeres (Robertson et al., 1982). Outputs from this single central source of rhythmicity are thought to activate the sets of motor neurons for all four of the wings. The evidence for this is based on the location and postsynaptic targets of interneurons that drive motor neurons and of those that can be shown to participate in rhythm generation using standard tests (Robertson and Pearson, 1983). There is very little evidence of strict serial homology of patterning elements and experiments to surgically isolate sections of the ventral nerve cord have supported the original description (Wolf and Pearson, 1987a). It is important to note that whereas the central element is conceived of as a rhythmical unit driving the motor neurons for all four wings this does not indicate a single mechanism for rhythm generation in the system. Indeed, there is evidence for multiple oscillatory mechanisms and stimulation of different single interneurons recruits different subsets of interneurons to evoke flight-like rhythms with different characteristics (Robertson, 1987b). The point is that there is currently no evidence for wing-specific oscillators in the deafferented system. This type of organization is unusual for a motor system that controls bilateral and serially repeated appendages. Such systems are most often organized as coupled central oscillators (see Marder and Calabrese, 1996, for a discussion of segmental oscillators in lamprey and leech swimming). In insects, hemisegmental oscillators (or unit burst generators, Grillner, 1985) have been demonstrated or suggested for locust walking (Ryckebusch and Laurent, 1994), locust grooming (Berkowitz and Laurent, 1996), stick insect walking (Bässler, 1993), grasshopper stridulation (Ronacher, 1989), and tymbal sound production by tiger moths (Dawson, 1995). The most telling pieces of evidence against the adequacy of the described flight circuitry and its interpretation have come from lesion experiments designed to demonstrate the existence of hemiganglionic oscillators for wingbeating (Ronacher et al., 1988; Wolf et al., 1988), though these were unable to demonstrate conclusively the existence of hemiganglionic oscillators (Wolf et al., 1988). In animals with afferents intact, flight and 423 rhythmical motor activity are remarkably resistant to longitudinal hemisections of the segmental ganglia that would damage the interneurons in the described flight circuit. This is true also for deafferented preparations under the influence of octopamine. Most interestingly, a mesothoracic hemiganglion separated from the majority of the flight circuitry by hemisection and transection of the ipsilateral meso-metathoracic connective could still produce robust rhythmical motor neuron activity to muscle 99 though this was poorly coordinated with the rhythm supplying other wing muscles (Ronacher et al., 1988; Fig. 8). The rhythmical drive for this motor neuron could be derived from a putative hemiganglionic oscillator, however it could also be a result of timing information from residual flight circuitry being relayed through the prothoracic ganglion and down the intact pro-mesothoracic connective. A further possibility is that the intact afferents serve to generate the rhythm in a chain-reflex fashion. Nevertheless, there is very suggestive evidence for hemiganglionic oscillators in flight preparations prior to deafferentation but relatively weak evidence after deafferentation (Figs. 8 and 9). It is an interesting possibility that the capacity for the flight circuit to be reconfigured by proprioceptive input (Wolf and Pearson, 1989) and the short-term plasticity evident during tethered flight (Möhl, 1988, 1993) are sufficient to enable a profound reorganization such that wing-specific oscillators are created by the afferent input. Flight rhythms produced by deafferented preparations in the absence of octopamine rarely last longer than a few seconds. Thus the central component (the unitary oscillator of the deafferented preparation) could act like a starter motor that is then converted to the running engine (putative coupled oscillators of the intact system) by proprioceptive feedback. The relevance of the described flight circuitry (derived from deafferented preparations) for generation of the motor patterns of intact animals is also challenged by information on the reconfiguration of the flight circuit by proprioceptive afferents. A significant advance in the investigation of the neuronal control of flight was the development of a preparation with which it is possible to record from neuronal somata of tethered flying locusts that have intact afferents (Wolf and Pearson, 1987b). This preparation involves tethering the locust upside down and has drawn criticism for this reason (Stevenson and Kutsch, 1987). However, the original findings and interpretations have been confirmed by making electromyographic and intracellular recordings of the motor activity before and after inversion of the same preparation (Pearson and Wolf, 1989). With this preparation it became feasible to investigate directly the contribution made by afferent input in the generation of the rhythm. Several interneurons with weak, and often subthreshold, membrane potential os- 424 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Fig. 8. Rhythmical motor activity recorded from hemisected mesothoracic ganglion in the locust. (A) Electromyographic activity recorded from right and left forewing depressor muscles (M97r and M99l) and from a left hindwing depressor (M128l) in a preparation with a hemisected mesothroacic ganglion and a transected left meso-metathoracic connective. Note the generation of a flight-like rhythm although there is poor coordination between M99l and the other wing muscles. (B) Rhythmical membrane potential oscillations recorded intracellularly from an elevator motor neuron in a deafferented preparation after the application of octopamine. Note that only two cycles are recorded and the presumed rhythm has a very low frequency. Taken with permission from Ronacher et al. (1988) and Wolf et al. (1988) cillations in deafferented preparations showed robust bursting activity in intact animals, and at least one interneuron behaved in the opposite fashion with bursting activity in deafferented preparations but weak oscillations in intact animals (Wolf and Pearson, 1989). These results indicate that the circuit of active interneurons is different in deafferented and intact animals. This is to say that afferent input reconfigures the circuit rather than simply regulating the timing of elements within a central pattern generator that can be considered as a defined unit (or black box) contributing to the output. Similar results have been seen in the ventilatory system of locusts in which the number of active neuronal elements is dependent upon the vigor of ventilation with more elements recruited as ventilation becomes more vigorous (Ramirez and Pearson, 1989). Another aspect of reconfiguration concerns the circuitry for the control of appendages (or muscle sets) that are used in different motor acts (Morton and Chiel, 1994). Interneurons can be dedicated to function in the production of a particular behavior or they can participate in the production of more than one. In insects it has been possible to identify both types of organization: interneurons for the control of bifunctional leg muscles seem to be divided into separate sets for the production of flight or walking of locusts (Ramirez and Pearson, 1988) and flight or stridulation of crickets (Hennig, 1990a), whereas other neurons can participate in the control of both ventilation and flight in locusts (Ramirez and Pearson, 1989) ventilation and stridulation in locusts (Otto and Hennig, 1993) and leg and wing stridulation in grasshoppers (Elsner, 1974). A mechanism underlying the reconfiguration of circuits controlling two behaviors has recently been described in locusts (Jellema and Heitler, 1997). The different behaviors (kicking and thrusting of the hindleg) are differentially characterized by the flexion angle of the tibia when they occur (full-flexed for kicking; around 90% for thrusting). Interestingly, it is feedback from the femoral chordotonal organ monitoring this joint angle that mediates the reconfiguration by biasing synaptic connections. During thrusting of the leg this afferent activity modulates the gain of connections from strain detectors in the leg cuticle and central connections between leg motor neurons to prevent the co-activation of flexors and extensors that is necessary to produce the stored energy required for a kick. 3.2.3. Neuromodulation It is now the accepted wisdom that pattern generating circuitry is under continuous modulatory control via neuroactive substances circulating in the blood (or hemolymph) or released locally in the neuropil (for reviews see Harris-Warrick and Marder, 1991; Pearson, 1993). The functions of such neuromodulation include activating and/or priming the circuitry, and reconfiguring the ensemble of participating neurons. C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Insect nervous tissue contains the usual complex cocktail of neuroactive substances (e.g. Nässel, 1996) that have been localized in specific neurons using immunocytochemical techniques. It is to be anticipated that these have roles to play in controlling the flexibility of motor pattern generators, among other things. In most cases the studies have progressed little further than identification and detailed description of immunoreactive neurons (most useful for comparison across taxa). With reference to motor patterning, most information about neuromodulation concerns octopamine which has multiple roles as a transmitter, neuromodulator and hormone (see Orchard et al., 1993). Octopamine is widespread in insect nervous systems (Stevenson and Spörhase-Eichmann, 1995). There has been considerable interest in the role of octopamine ever since the suggestion by Hoyle (1975) and confirmation by Evans and O’Shea (1978) that dorsal unpaired median (DUM) neurons used octopamine as a transmitter to modulate a myogenic rhythm of the extensor tibiae muscle of the locust leg. More recently it has been demonstrated that the injection of octopamine into specific regions of flight neuropil in the metathoracic ganglion can activate flight rhythms (Sombati and Hoyle, 1984; Stevenson and Kutsch, 1987). The mechanism underlying this is likely to be the induction of plateau potentials in specific locust flight interneurons (Ramirez and Pearson, 1991a,b) in combination with a more generalized arousal of the system (Fig. 9). Octopamine has also been shown to modulate the spiking activity of a wing-hinge proprioceptor in the locust (Ramirez and Orchard, 1990), a leg proprioceptor in stick insects and locusts (Ramirez et al., 1993; 425 Matheson, 1997), synaptic interactions between interneurons in escape circuitry of the cockroach (Casagrand and Ritzmann, 1992), leg motor neurons in locusts (Parker, 1996) and flight muscle in locust (Whim and Evans, 1991; Stevenson and Meuser, 1997) indicating a modulatory role throughout the behavioral machine from sensory neurons through to muscle. It has been suggested that the local release of octopamine by specific subsets of DUM neurons could tune particular regions of neuropil for the generation of different behaviors (the orchestration hypothesis, Sombati and Hoyle, 1984; reviewed in Bicker and Menzel, 1989; Burrows, 1996) though there is currently little evidence for such an overarching coordinating role (but see Burrows and Pflüger, 1995). Alternatively there are suggestions that octopamine mediates arousal. This interpretation is supported by the observation that octopamine dishabituates the response of DCMD when it is released from identified octopamine immunoreactive neurons in the optic lobe of locusts (Bacon et al., 1995). In addition, olfactory reward learning in honeybees is enhanced by octopamine and depolarization of an identified ventral unpaired neuron (VUMmx1, containing octopamine) can substitute for the reward in olfactory conditioning (see Hammer, 1997). The role of acetylcholine as a neuromodulator acting via an influence on muscarinic receptors is a topic with some relevance to the control of motor activity (for review see Trimmer, 1995). The application of pilocarpine (or other muscarinic agonists) to several different insect preparations can induce the generation of rhythmical motor patterns (walking — Ryckebusch and Laurent, 1993; Büschges et al., 1995; stridulation — Fig. 9. Hyperexcitability of the flight rhythm generated by locust thoracic ganglia after perfusion with octopamine. [Ai] Structure of identified flight interneuron 401. [Aii] Brief electrical stimulation (STIM) of interneuron 401 induces a flight- like rhythm recorded intracellularly in 401 and a contralateral depressor motor neuron (DEP). [B] Injection of a long pulse of depolarizing current into interneuron 566 evokes tonic activity before (i) and flight like rhythmical activity after (ii) the application of octopamine. Taken with permission from Ramirez and Pearson, 1991a and Ramirez and Pearson, 1991b. 426 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Heinrich et al., 1997; see also Trimmer, 1995; crawling in moth larvae — Johnston and Levine, 1996; mandibular rhythms — Rast and Bräunig, 1997). Much of this effect is likely attributable to the increase in excitability of identified neurons when treated with muscarinic agonists (Trimmer, 1994; David and Pitman, 1995, 1996), but other effects cannot be ruled out. Indeed, it has been demonstrated that muscarinic antagonists can augment the amplitude of postsynaptic potentials from the forewing stretch receptor in locusts and it is proposed that this represents self-regulation at this cholinergic synapse via presynaptic autoreceptors (Leitch and Pitman, 1995). The studies on the activation of motor patterns require the usual caveats for investigations of neuromodulatory agents given that it is difficult to know precisely what the treatment is doing. The problems of interpretation are only slightly mitigated when the agents are injected into neuropil (e.g. Heinrich et al., 1997) rather than bath-applied (e.g. Ryckebusch and Laurent, 1993). In spite of this, the ability to induce walking motor rhythms in reduced preparations of insects is a significant advance and will allow the control of this behavior to be addressed by the identified neuron approach. tic terminals of the afferent reduces the efficacy of action potentials in the afferent and this can serve a variety of important functions such as to prevent saturation in the pathway (Burrows and Matheson, 1994), to reduce hysteresis (Hatsopoulos et al., 1995) and to mitigate the effects of reafference (Hedwig and Burrows, 1996). During the generation of motor patterns for locomotion, rhythmical presynaptic inhibition of proprioceptive afferents occurs to modulate phase-dependent reflexes and, whereas other afferents may be involved, it is clear that centrally generated signals must contribute to the presynaptic depolarization (Wolf and Burrows, 1995). An interesting idea has been proposed that a general role for presynaptic inhibition is to reduce the efficacy of feedback from predicted movements (predicted by the output of a central pattern generator) and to allow the feedback from unexpected perturbations of movement to have greater efficacy (Burrows, 1996). Presynaptic inhibition is a critical process for efficient motor control (in humans the modulation of presynaptic inhibition is affected by the defects associated with spasticity — Stein, 1995). This process is eminently accessible to cellular investigations in insect motor systems. 3.2.4. Afferent regulation Motor patterns in insects are generated by a combination of central and peripheral mechanisms. The futile (in retrospect) debate over the relative contribution of each to pattern generation is largely over and the focus has rightly shifted to a consideration of the precise role of proprioceptive feedback in structuring the pattern. From research with the locust flight system it is evident that proprioceptive input can reconfigure the central circuit of active neurons (see above). Notwithstanding this there is strong evidence that rhythmic proprioceptive discharges have a prime role in regulating the timing of phase transitions and that this role is mirrored in other systems including those of vertebrates (see Pearson, 1993, 1995). In the locust flight system wing-hinge stretch receptors monitor elevations and the tegulae monitor depressions. Activity of the stretch receptors promotes an earlier onset of depressor motor neuron bursts by reducing the degree of hyperpolarization between bursts, whereas activity of the tegulae recruits elevator interneurons and advances the timing of elevator motor neuron bursts (see Pearson and Ramirez, 1992). Other proprioceptors exist and are likely to be involved in patterning the motor output but their roles are incompletely understood at present (e.g. Pearson et al., 1989; Stevenson, 1997). The gain of the connections made by afferents with identified postsynaptic targets is under presynaptic inhibitory control (cricket — Levine and Murphey, 1980; locust — Pearson and Goodman, 1981; cockroach — Hue and Callec, 1983). Depolarization of the presynap- 3.3. Neuronal restructuring The ability to investigate the properties of identified neurons and identified synapses has considerable advantages for investigations of structural plasticity and its consequences in the nervous system. Such changes are associated with long-term reorganization of circuits during the processes of maturation, metamorphosis, learning and memory, and recovery from peripheral injury. Insects have provided several model systems with which to pursue an understanding of these phenomena (e.g. Weeks et al., 1997; Kämper and Murphey, 1994) and it is now accepted that results from these systems have general relevance across different taxa [including vertebrates] (Murphey, 1986). An interesting feature of the development and maturation of insects is that they exhibit age-specific behaviors associated with new or modified body parts and new control circuits. For example the hemimetabolous locust attains wings only at the final molt and, although flight rhythms can be generated immediately after molting, it takes two weeks of maturation before an animal is able to generate a flight motor pattern that has an appropriate frequency to sustain lift and thrust (see Kutsch, 1989). The phenomena underlying this increase in wingbeat frequency are incompletely understood for it has proved resistant to a variety of experimental manipulations. There is a correlation with growth of identified interneurons although several parameters of identified synaptic potentials in these interneurons are unaffected by maturation (Gee and Robertson, 1994). C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 The axonal branching of the stretch receptor afferent shows heteromorphic growth (Gray and Robertson, 1996). The conduction velocity and sensitivity of the stretch receptor increases (Gray and Robertson, 1994) and its ability to modify an ongoing flight rhythm increases (Gray and Robertson, 1997a). These changes seem independent of the levels of circulating ecdysone (Kutsch, 1989) or of juvenile hormone although this may have a role in the switch from a larval rhythm to the adult rhythm (Kutsch and Stevenson, 1984). During larval development other identified afferents in this system show structural alterations indicating changes in connectivity and this change is activity-dependent, not hormonally-mediated, and likely to be regulated by competition for synaptic sites (Pflüger et al., 1994). The evidence suggests that the flight circuitry is in a dynamic state throughout maturation and able to react to external influences so that the final form of the circuit is appropriate for an individual’s morphology. That the profoundly dynamic nature of the locust flight circuit continues into the fully mature adult stage is well demonstrated by the effect of peripheral lesions on the system. The tegulae are proprioceptors that monitor wing position during the downstroke and have a significant role in the generation of aerodynamically appropriate wing movements (Wolf, 1993). Removal of the hindwing tegulae causes a reduction in wingbeat frequency that recovers during the subsequent 2 weeks (Büschges and Pearson, 1991) although in most animals the recovery is not sufficient to enable free flight (Gee and Robertson, 1997). This recovery appears to be mediated by growth of the forewing tegulae afferents and the formation of new and more reliable connections with flight interneurons (Büschges et al., 1992a,b). The extent and speed of recovery are not affected by the maturational stage (post imaginal molt) of the animal (Gee and Robertson, 1996). Interestingly, removal of a single hindwing tegula (which projects to only one side of the thoracic ganglia) has structural and synaptic consequences for connections on the contralateral (uninjured) side indicating a role for retrograde signals and competitive interactions in the restructuring of these afferent pathways (Wolf and Büschges, 1997; Fig. 10). These changes are reminiscent of the competitive interactions and retrograde signals that have been elegantly demonstrated in the cercal system of crickets during development (Murphey and Lemere, 1984; Chiba et al., 1988; Davis and Murphey, 1994a,b; Murphey and Davis, 1994). It is becoming quite clear from these studies that insect circuits are in a dynamic state, continually able to restructure neurites and modify synaptic connectivity as a consequence of competitive interactions. This occurs throughout development and is retained into adult stages. The similarity with mammalian systems (Kaas, 1991) is striking and perhaps 427 Fig. 10. Diagrams illustrating the change in connectivity from tegulae afferents onto a generalized flight interneuron in the metathoracic ganglion after recovery from unilateral hindwing tegula removal. (A) shows normal organization and site of lesion (scissors). Lines traveling down the meso metathoracic connectives indicate afferents from the forewing tegulae. One synapse from an afferent to an interneuron indicates 10% frequency of connection and the size of the terminals indicate the strength of the connections as measured by the amplitude of compound EPSPs. Note that the reliability and strength of connections from the forewing tegula on the side ipsilateral to the lesion increase (B), and that there is also a retrograde effect on the connections from the forewing tegula on the side opposite the lesion. Taken with permission from Wolf and Büschges (1997). insects will afford one of the best opportunities to study the underlying mechanisms of this form of plasticity at the level of identified neurons. A more dramatic restructuring of motor circuits occurs during the metamorphosis of holometabolous insects such as Manduca and Drosophila (Truman, 1990; Weeks and Levine, 1992; Levine et al., 1995). In these systems the peripheral structures change dramatically to support a completely different life-style: a nervous system appropriate for larvae requires disassembly prior to construction of a nervous system appropriate for adults. The processes that are involved in this transformation include targeted cell death, postembryonic neurogenesis, restructuring of neuronal arbors, synaptic remodeling, and changes in the expression of voltagedependent currents of identified neurons. One of the most significant features of this research is that the remodeling is under the control of steroid hormones allowing a fine-grained, cellular investigation of important phenomena that may be difficult to address at this level in mammalian systems. This is a well-advanced field that has been amply reviewed in recent years (Weeks and Levine, 1995; Levine et al., 1995; Kent et al., 1995; Weeks and Wood, 1996; Weeks et al., 1997). 428 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 3.4. E6olution and homology It is a truism to say that the current design of circuitry is a result of inexorable evolutionary mechanisms acting on pre-existing circuits to adapt them such that organisms are better suited to their particular niches. The effects of evolution are clearly recognizable in the nervous system (Arbas et al., 1991). The consequences of evolution in the context of this article are at least two-fold. First, current design may owe more to history than to functional necessity and this complicates the interpretation of the neuroethological utility of specific features of neuronal structure and operation. This point has been made previously (Dumont and Robertson, 1986) and need not concern us further here. Second, closely related species are likely to be more similar in the characteristics of their identified neurons than more distantly related species. This being true it should be possible to recognize neuronal homologs across species and perhaps determine how evolutionary processes mold circuitry (e.g. Mizunami, 1994; Edwards, 1997; Tierney, 1995 for a discussion of the effects of evolution on neural circuits). Moreover, information on neuronal homology can be applied by taxonomists to confirm or refute different evolutionary scenarios (see Osorio and Bacon, 1994; Osorio et al., 1995). The large number and diversity of insect species, the known sexual dimorphisms of structure and behavior (see Hoy, 1990), the fact that insects lend themselves particularly well to neuroanatomical study, and the fact that the organization of insect ganglia bestows upon their neurons distinctive and beautiful structures, all contribute to making insects arguably the best animal group with which to pursue such an endeavor. Establishing neuronal homology across species is notoriously difficult especially when the functions of the neurons may be different. Normally it requires the demonstration of a common lineage from an identified neuroblast during development (e.g. Boyan and Ball, 1993, for segmental homologs). When neurons are particularly distinctive, structurally and functionally, however, it is possible to make the conclusion with confidence (e.g. Bacon, 1980). In the orthopteran flight system there is evidence in locusts and crickets for similar organization of interneurons (Robertson et al., 1982; Robertson, 1987a) and for homologous interneurons with roles in pattern generation (Robertson, 1987b; Hennig, 1990b). Nevertheless, possibly the best system with which to investigate these sorts of questions is the visual system of the Diptera which can provide answers even at the level of synaptic ultrastructure (Shaw and Meinertzhagen, 1986). Specific neurons in the optomotor system are quite distinctive (e.g. Hausen, 1982) and evolution of the visual system has been relatively conservative. Moreover, numerous species of closely related Diptera occupy a variety of different visual niches providing an opportunity to dissect differences related to adaptation from similarities related to a common origin. Recent detailed neuranatomical studies in a large number of Diptera demonstrate that whereas the retinotopically arranged elementary motion detectors are conserved across different species (Buschbeck and Strausfeld, 1996) there exist functionally and ecologically relevant differences in the structure and organization of the output elements of the lobula plate (the vertical and horizontal motion sensitive neurons) (Buschbeck and Strausfeld, 1997). The idea that conserved circuitry is tuned to produce species-relevant behavior is confirmed in the control of the leg during predator evasion of stick insects and locusts (Büschges and Wolf, 1995). Typically stick insects become cataleptic on detection of a predator and locusts generate jumps or kicks. The components and operation of the motor circuits of the leg in these two organisms are relatively well known, though certainly far from completely described, and they exhibit much similarity. Putative homologs exist at all levels of the circuit (motor neurons, non-spiking interneurons, sensory neurons) and their interconnections are qualitatively the same. Interneurons, but not motor neurons, show a difference in the velocity sensitivity of the processing of information from the femoral chordotonal organ (velocity-dependent in stick insects but not in locusts) and this can be attributed to the functional demands imposed by different evasion strategies. Thus, the characteristics of identified neurons in insects can be used to answer questions about evolutionary relationships among taxa and also can help in parsing out functional vs. phylogenetic features. Central nervous circuits are relatively conserved, which is not surprising given the difficulty of constructing the nervous system during development and the phylogenetic conservation of the mechanisms for neurogenesis and growth cone guidance (Goodman, 1994; Reichert and Boyan, 1997). Fine-tuning of cellular and synaptic properties overlies a common circuitry to fit an organism for an individual life-style, at a given developmental stage (Edwards, 1977), and in an individual ecological niche. 4. Newer approaches 4.1. Molecular/genetic approaches While the 1980s saw a burgeoning of the cellular approach to understanding neural operating principles, the 1990s have witnessed the flowering of various molecular approaches; thanks to the increasing sophistication of techniques. It has been demonstrated that identified neurons in the lobster stomatogastric system have unique genetic identities (Baro et al., 1996) and C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 the same is without doubt true for insect neurons. The organism par excellence with which to perform molecular and genetic manipulations is the fruit fly, Drosophila. This insect has the usual repertoire of complex behaviors but its small size, and consequently the small size of its neurons (diameter of motor neuron somata 8 mm, Koenig and Ikeda, 1983), has prevented sustained intracellular investigation of identified circuitry. One notable success was the investigation of connectivity from the descending giant fiber (GF) that mediates escape jumping and flight (see Wyman et al., 1984). The effects of mutations that impaired escape could be traced to defects in the GF circuit (see Thomas and Wyman, 1983). Much molecular dissection of synaptic operation is now performed using the larval neuromuscular junction (see Keshishian et al., 1996) and genetic and behavioral experiments with Drosophila combined with intracellular investigations in larger flies (e.g. Musca) is advancing the genetic dissection of the neuronal basis of visuomotor flight control in flies (see above). Now another central synapse, and one that is involved in the control of flight, can be added to the GF circuit as one accessible to modern techniques. Intracellular recording from adult motor neurons has allowed the demonstration that the shaking-B2 mutation disrupts synaptic connectivity between haltere afferents and flight motor neurons (Trimarchi and Murphey, 1997; Fig. 11). It is to be hoped that contin- 429 ued efforts in this direction will lead to more complete descriptions of functional circuits of identified neurons. The particular advantages of Drosophila have meant that efforts to use molecular and genetic techniques to study behavioral circuits in adult animals continue unabated. One area where these approaches are just beginning to yield exciting results concerns the mushroom bodies (and see Strausfeld, this volume). This area contains an enormous population of Kenyon cells which appear homogeneous by morphological criteria. However, use of enhancer trap techniques has made it possible to describe the developmental lineage of mushroom body cells (Ito et al., 1997) and provided the realization that the adult mushroom bodies are composed of definable cellular subsets that differ in gene expression (Yang et al., 1995). Such techniques may spur studies of mushroom body involvement in sensory integration, motor programming, and learning. 4.2. Neuroecology In some respects to say that an organism’s ecology constrains the nature of its neuronal circuits is simply to restate the concept that evolution has matched the design of the circuitry to the functional demands of a particular ecology. It is this awareness that underpins the discipline of neuroethology-control systems can only properly be investigated in the context of the natural behavior of the animal and this implies a con- Fig. 11. The shaking B2 mutation disrupts synaptic connectivity between haltere afferents and flight motor neurons in Drosophila. (A) Comparison in wild-type [Ai] and shaking-B2 [Aii] animals of the latencies of action potentials recorded intracellularly in motor neuron B1 after stimulation of haltere afferents with increasing stimulus intensities. Note the irregular latencies and the unreliability of the connection in the mutant. (B) Effects of electrical stimulation of haltere afferents on electromyographic activity recorded from muscle B1. [Bi] Stimulus at 70V, comparison of five traces in each of a normal and a mutant animal. [Bii] Summary of latencies recorded with a variety of stimulus intensities. Note the longer and variable latencies in the mutant animals. Taken with permission from Trimarchi and Murphey (1997). 430 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Fig. 12. The visual ecology of voltage-gated K+ conductances in insect photoreceptors recorded with single electrode voltage clamp. In Diptera [top panel] non-inactivating outward currents are typically found in diurnal, rapidly flying insects (fast) where as in crepuscular, slow flying insects (slow) the outward s currents are found to inactivate thus minimizing the energy required to maintain normal K+ concentrations when the ecology dictates that high frequency responses are not necessary. In the locust Schistocerca the inactivation properties of the outward currents are dependent on the time of day [middle panel] and can be converted from the day state to the night state by the application of 5HT [bottom panel]. Taken with permission from Weckström and Laughlin (1995). sideration, if not a deep understanding, of the animal’s ecology. Excellent recent demonstrations of the idea that neural properties are matched to ecology concern the visual system of flying insects. The distribution of voltage-gated ion channels in photoreceptors of different insects (locust, fly, bee) has been shown to be associated with the flight speed of the insect and the time when it is most active (i.e. nocturnal, diurnal) (Weckström and Laughlin, 1995; Fig. 12). Indeed, potassium channels in locust photoreceptor membranes are modulated on a daily basis to balance the goals of increasing performance while active and decreasing metabolic demands while inactive (Weckström and Laughlin, 1995). Similarly, the tuning of visual motion sensitive neurons in a variety of insects is correlated with their flight speeds and hovering ability (O’Carroll et al., 1996). On the other hand it is increasingly likely that the ecology of an organism could have longer term effects that condition the circuits in such a way that their operating mechanisms are different. For example, diet has been shown to modify the ionic content of the hemolymph and the activity of cockroaches (Pichon and Boistel, 1963). Temperature is arguably the most potent environmental variable for a poikilotherm, espe- cially for the migratory locust whose native habitat includes semiarid regions of equatorial Africa (Uvarov, 1966). In a flying locust thoracic temperature can exceed environmental temperature by around 10°C (WeisFogh, 1956, 1964) and in hot environments thoracic temperatures of flying insects have been recorded as high as 48°C (Coelho, 1991). Increasing thoracic temperature has effects on both the output of the locust flight circuit (Foster and Robertson, 1992), on properties of identified neurons (Xu and Robertson, 1994) and on synaptic parameters within the circuit (Robertson, 1993). These effects can be interpreted as mechanisms to compensate for changes in temperature and thus maintain a relatively stable output (Xu and Robertson, 1996). Interestingly, prior heat shock (exposure to 45°C for 3 h) alters the thermosensitivity of flight behavior (wingbeat frequency during tethered flight) and that of the flight circuit (deafferented rhythm frequency) in profound ways (Robertson et al., 1996; Fig. 13). The thoracic temperature at which flight rhythm generation fails is 6–7°C higher in heat-shocked animals and the frequency of flight rhythms (intact or deafferented) becomes insensitive to temperature in the 30–45°C range (Robertson et al., 1996). Similar reductions of thermosensitivity can be observed for the conduction velocity and extracellularly recorded amplitude of the stretch receptor action potential (Gray and Robertson, Fig. 13. Prior heat shock affects the temperature sensitivity of flight rhythms in the locust Locusta. [A] Wing beat frequency (WBF) recorded electromyographically from intact tethered flying locusts shows minimal thermosensitivity after heatshock (ii) compared with control animals [i], and the temperature at which flight rhythms fail is significantly higher after heat shock (iii). (B) Flight rhythm frequency recorded from deafferented preparations is reduced in thermosensitivity at temperatures above 35°C after heat shock (ii) compared with control preparations [i], and the temperature at which flight rhythms fail is significantly higher after heatshock (iii). Modified from Robertson et al. (1996). C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 1997c) and for parameters of synaptic potentials in the flight circuit (Dawson-Scully and Robertson, unpublished). The effects of heat shock on thermotolerance last for at least one week (Robertson et al., 1996). It is not yet clear how heat shock causes these effects, but a working hypothesis is that heat shock proteins (expressed in locusts, Whyard et al., 1986) protect the operation, and change the thermosensitivity, of membrane proteins. The significant feature of all of the above is not just that environmental conditions alter circuit properties, but also that the history of environmental conditions affects how the circuit operates at any future time. This is neuroecology; the study of features of neural structure and function that are constrained by the ecology of an organism. Table 1 Web sites with information on identified nerve cellsa Organism-based 1 Molluscs 2 Arthropods 3 4 5 6 In the space of this review it was only possible to cover a small portion of the work on insect model systems where identified nerve cells have been related to the control of behavior. Furthermore, we did not consider the importance of using identified insect cells in studies of: neuronal differentiation (e.g. Doe, 1992), learning (e.g. Mauelshagen, 1995), or regeneration (e.g. Spira et al., 1987), and we only touched briefly on the development of synaptic connections (e.g. Blagburn and Thompson, 1990). Thus it can be appreciated that the total amount of published information on identified nerve cells of insects is enormous. The data management problem that a neuroscientist faces when trying to marshal complete information about one specific identified cell, to make a comparison of potentially homologous cells across species, or to obtain design features of different cells for modeling studies, can be daunting. The same data management situation arose in genomics at least a decade ago when the number of published sequences was rising rapidly (Smith, 1990). The solution for geneticists and molecular biologists was to rely on electronic databases (Aldhous, 1993). Searching a sequence database allows one to quickly compare nucleotide or protein structures and this can suggest functions for molecules where this was previously unknown, or it may point to evolutionary relationships. The importance of storing neurobiological data in digital formats has not escaped the attention of neurobiologists. The ability to tag molecular, developmental and physiological information to the structure of uniquely identified neurons, such as those reviewed in this chapter, will make it possible for the same broad questions to be answered for neural circuits, that are now being asked for the genome of higher animals. This point was persuasively argued in an article by Rowell (1988) which seems to have been widely read, but acted upon very little until the last three or four years. Fruitfly (3 mirror sites) Cockroach Bee Moth Software/tools 7 Structural 8 4.3. Neuroinformatics and insect ner6e cells 431 Physiological ganglion.med.cornell.edu/ web.neurobio.arizona.edu/Evolbrain/index.h tml flybrain.neurobio.arizona.edu/ flybrain.uni-freiburg.de/ flybrain.nibb.ac.jp/ n002bsel.bios.uic.edu/ beebrain.neurobio.arizona.edu/ mothbrain.neurobio.arizona.edu/ www.nervana.montana.edu/projects/NeuroS ys/ soma.npa.uiuc.edu/isnpa/isnpa.html a All URL identification tags should be preceded by ‘‘http://’’. Some sites (listed first) are concentrated primarily on collections of data related to a given organism, while others (at bottom) are devoted primarily to development and dissemination of software for visualizing neuronal structures or physiological data Electronic resources initially were implemented for databases of images related to clinical and mammalian neurobiology (e.g. Fox et al., 1993; Swanson, 1995). The recent heavy usage of world wide web resources by researchers has catalyzed the development of neurobiological tools, and several electronic databases related to identified neurons in insects have now appeared. The most extensive at this point is a collection of sites devoted to the Drosophila CNS (Armstrong et al., 1995; Heisenberg and Kaiser, 1995), but others are beginning to emerge (see Table 1) and a federation of insect databases has already been envisioned (see links at Flybrain site). We believe that WWW resources will prove to be particularly useful for precisely those areas where insect neural studies have their brightest future: comparative, evolutionary, and computational neuroscience. 5. Concluding remarks There is no doubt in our minds that research using identified neurons in insects is alive, well, and will make significant contributions in a wide variety of sub-disciplines within the general enterprise of understanding how neurons and their interactions generate appropriate behaviors. The growing realization of the computational power of single neurons and dendrites in mammalian circuits (Koch, 1997; Sejnowski, 1997) comes as no surprise to those who follow the literature on identified neurons in insects (see references above on Dipteran visual cells to provide examples from but a single system) and in the Dipteran examples this computational ability can be directly related to the functional demands of the neurons. 432 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 A theme which has emerged numerous times in this chapter, with respect to both sensory processing and motor programming, is the value of comparative study. This is quite obvious in the case of evolutionary questions, but even with respect to computational questions, comparisons of identified circuit elements in related species, and especially between adults and larval forms of the same species offer many opportunities. Reviews like this chapter are likely to become obsolete as the mass of information becomes too unwieldy to manage in a single chapter. Possibly the present review will be taken as strong evidence by some readers that we have already passed that point. This, in itself, argues for the importance of readily accessible databases of identified neurons to future research that would seek to define the interaction between evolutionary processes and identified circuits. References Aldhous, P., 1993. Managing the genome data deluge. Science 262, 502 – 503. Arbas, E.A., Meinhertzhagen, I.A., Shaw, S.R., 1991. Evolution in nervous systems. Ann. Rev. Neurosci. 14, 9–38. Armstrong, D.J., Kaiser, K., Müller, A., Fischbach, K.-F., Merchant, N., Strausfeld, N., 1995. Flybrain, an on-line atlas and database of the Drosophila nervous system. Neuron 15, 17–20. Atkins, G., Ligman, S., Burghardt, F., Stout, J.F., 1984. Changes in phonotaxis by the female cricket Acheta domesticus after killing identified acoustic interneurons. J. Comp. Physiol. 154, 795 – 804. Baba, Y., Shimozawa, T., 1997. Diversity of motor responses initiated by a wind stimulus in the freely moving cricket, Gryllus bimaculatus. Zool. Sci. 14, 587–594. Baba, Y., Hirota, K., Yamaguchi, T., 1991. Morphology and response properties of wind-sensitive non-giant interneurons in the terminal abdominal ganglion of crickets. Zool. Sci. 8, 437 – 445. Bacon, J.P., 1980. An homologous interneuron in a locust, a cricket and a mantid. Verh. Dtsch. Zool. Ges. 73, 300. Bacon, J.P., Murphey, R.K., 1984. Receptive fields of cricket (Acheta domesticus) interneurons are related to their dendritic structure. J. Physiol. (London) 352, 601–623. Bacon, J.P., Strausfeld, N.J., 1986. The dipteran ‘giant fibre’ pathway: neurons and signals. J. Comp. Physiol. 158, 529–548. Bacon, J.P., Tyrer, M., 1978. The tritocerebral commissure giant: a bimodal interneuron in the locust, Schistocerca gregaria. J. Comp. Physiol. 126, 317 – 325. Bacon, J.P., Thompson, K.S.J., Stern, M., 1995. Identified octopaminergic neurons provide an arousal mechanism in the locust brain. J. Neurophysiol. 74, 2739–2743. Baier, H., Korschung, S., 1994. Olfactory glomeruli in the zebrafish form an invariant pattern and are identifiable across animals. J. Neurosci. 14, 219 – 230. Baro, D.J., Coniglio, L.M., Cole, C.L., Rodriguez, H.E., Lubell, J.K., Kim, M.T., Harris-Warrick, R.M., 1996. Lobster shal: comparison with Drosophila shal and native potassium currents in identified neurons. J. Neurosci. 16, 1689–1701. Basarsky, T.A., French, A.S., 1991. Intracellular measurements from a rapidly adapting sensory neuron. J. Neurophysiol. 65, 49 – 56. Bässler, U., 1993. The walking- (and searching-) pattern generator of stick insects, a modular system composed of reflex chains and endogenous oscillators. Biol. Cybernet. 69, 305–317. Bentley, D., 1970. A topological map of the locust flight system motor neurons. J. Insect Physiol. 16, 905 – 918. Bentley, D.R., 1969a. Intracellular activity in cricket neurons during the generation of behaviour patterns. J. Insect Physiol. 15, 677– 699. Bentley, D.R., 1969b. Intracellular activity in cricket neurons during generation of song patterns. Z. vergl. Physiol. 62, 267 – 283. Berkowitz, A., Laurent, G., 1996. Central generation of grooming motor patterns and interlimb coordination in locusts. J. Neurosci. 16, 8079 – 8091. Bialek, W., Rieke, F., deRuytervan Stevenick, R.R., Warland, D., 1991. Reading a neural code. Science 252, 1854 – 1857. Bicker, G., Menzel, R., 1989. Chemical codes for the control of behavior in arthropods. Nature (London) 337, 33 – 39. Blagburn, J.M., Thompson, K.S.J., 1990. Specificity of filiform hair afferent synapses onto giant interneurons in Periplaneta americana: anatomy is not a sufficient determinant. J. Comp. Neurol. 302, 255 – 271. Boeckh, J., Ernst, K.-D., 1987. Contribution of single unit analysis in insects to an understanding of olfactory function. J. Comp. Physiol. 161, 549 – 565. Boekhoff, I., Seifert, E., Göggerle, S., Lindemann, M., Krüger, B.-W., Breer, H., 1993. Pheromone-induced second-messenger signalling in insect antennae. Insect Biochem. Mol. Biol. 23, 757 – 762. Borst, A., 1996. How do nerve cells compute? Dendritic integration in fly visual interneurons. Acta Physiol. Scand. 157, 403 – 407. Borst, A., Egelhaaf, M., 1990. Direction selectivity of fly motion-sensitive neurons is computed in a two-stage process. Proc. Nat. Acad. Sci. 87, 9363 – 9367. Boyan, G.S., 1993. Another look at insect audition: the tympanic receptors as an evolutionary specialization of the chordotonal system. J. Insect Physiol. 39, 187 – 200. Boyan, G.S., Ball, E.E., 1989. The wind-sensitive cercal receptor/giant interneuron system of the locust, Locusta migratoria. II. Physiology of giant interneurons. J. Comp. Physiol. 165, 511–521. Boyan, G.S., Ball, E.E., 1990. Neuronal organization and information processing in the wind-sensitive cercal receptor/giant interneuron system of the locust and other orthopteroid insects. Prog. Neurobiol. 35, 217 – 243. Boyan, G.S., Ball, E.E., 1993. The grasshopper, Drosophila and neuronal homology (advantages of the insect nervous system for the neuroscientist). Prog. Neurobiol. 41, 657 – 682. Breedlove, S.M., 1992. Sexual dimorphism in the vertebrate brain. J. Neurosci. 12, 4133 – 4142. Burdohan, J.A., Comer, C.M., 1990. An antennal-derived mechanosensory pathway in the cockroach: descending interneurons as a substrate for evasive behavior. Brain Res. 535, 347–352. Burdohan, J.A., Comer, C.M., 1996. Cellular organization of an antennal mechanosensory pathway in the cockroach, Periplaneta americana. J. Neurosci. 16, 5830 – 5843. Burrows, M., 1973. The morphology of an elevator and depressor motoneuron of the hindwing of a locust. J. Comp. Physiol. 83, 165 – 178. Burrows, M., 1977. Flight mechanisms of the locust. In: Identified Neurons and Behavior of Arthropods, pp. 339 – 356. Burrows, M., 1996. The Neurobiology of an Insect Brain. Oxford University Press, Oxford, UK, p. 682. Burrows, M., Matheson, T., 1994. A presynaptic gain control mechanism among sensory neurons of a locust leg proprioceptor. J. Neurosci. 14, 272 – 282. Burrows, M., Pflüger, H.-J., 1995. Action of locust neuromodulatory neurons is coupled to specific motor patterns. J. Neurophysiol. 74, 347 – 357. Burrows, M., Boeckh, J., Esslen, J., 1982. Physiological and morphological properties of interneurons in the deuterocerebrum of male cockroaches which respond to female pheromone. J. Comp. Physiol. 145, 447 – 457. C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Buschbeck, E.K., Strausfeld, N.J., 1996. Visual motion-detection circuits in flies: small-field retinotopic elements responding to motion are evolutionarily conserved across taxa. J. Neurosci. 16, 4563 – 4578. Buschbeck, E.K., Strausfeld, N.J., 1997. The relevance of neural architecture to visual performance: phylogenetic conservation and variation in dipteran visual systems. J. Comp. Neurol. 383, 282 – 304. Büschges, A., 1995. Role of local nonspiking interneurons in the generation of rhythmic motor activity in the stick insect. J. Neurobiol. 27, 488 – 512. Büschges, A., Pearson, K.G., 1991. Adaptive modifications in the flight system of the locust after the removal of wing proprioceptors. J. Exp. Biol. 157, 313–333. Büschges, A., Wolf, H., 1995. Nonspiking local interneurons in insect leg motor control. I. Common layout and species-specific response properties of femur – tibia joint control pathways in stick insect and locust. J. Neurophysiol. 73, 1843–1860. Büschges, A., Ramirez, J.-M., Pearson, K.G., 1992a. Reorganization of sensory regulation of locust flight after partial deafferentation. J. Neurobiol. 23, 31 –43. Büschges, A., Ramirez, J.-M., Driesang, R., Pearson, K.G., 1992b. Connections of the forewing tegulae in the locust flight system and their modification following partial deafferentation. J. Neurobiol. 23, 44 – 60. Büschges, A., Kittmann, R., Schmitz, J., 1994. Identified nonspiking interneurons in leg reflexes and during walking in the stick insect. J. Comp. Physiol. 174, 685–700. Büschges, A., Schmitz, J., Bässler, U., 1995. Rhythmic patterns in the thoracic nerve cord of the stick insect induced by pilocarpine. J. Exp. Biol. 198, 435 – 456. Calabrese, R.L., De Schutter, E., 1992. Motor-pattern-generating networks in invertebrates: modeling our way toward understanding. Trends Neurosci. 15, 439–445. Camhi, J.M., Tom, W., 1978. The escape behavior of the cockroach Periplaneta americana. I. Turning response top wind puffs. J. Comp. Physiol. 128, 193–201. Camhi, J.M., Levy, A., 1989. The code for stimulus direction in a cell assembly in the cockroach. J. Comp. Physiol. 165, 83–97. Camhi, J.M., Nolen, T., 1981. Properties of the escape system of cockroaches during walking. J. Comp. Physiol. 142, 339–346. Camhi, J.M., Tom, W., Volman, S., 1978. The escape behavior of the cockroach Periplaneta americana. II. Detection of natural predators by air displacement. J. Comp. Physiol. 128, 203–212. Casagrand, J.L., Ritzmann, R.E., 1992. Biogenic amines modulate synaptic transmission between identified giant interneurons and thoracic interneurons in the escape system of the cockroach. J. Neurobiol. 23, 644 – 655. Cayre, M., Strambi, C., Strambi, A., 1994. Neurogenesis in an adult insect brain and its hormonal control. Nature 368, 57–59. Chiba, A., Shepherd, D., Murphey, R.K., 1988. Synaptic rearrangement during postembryonic development in the cricket. Science 240, 901 – 905. Coelho, J.R., 1991. The effect of thorax temperature on force production during tethered flight in honeybee (Apis mellifera) drones, workers, and queens. Physiol. Zool. 64, 823–835. Cohen, M.J., Jacklet, J.W., 1967. The functional organization of motor neurons in an insect ganglion. Phil. Trans. R. Soc. London B252, 561 – 572. Comer, C.M., 1985. Analyzing cockroach escape behavior with lesions of individual giant interneurons. Brain Res. 335, 342 – 346. Comer, C.M., Dowd, J.P., 1993. Multisensory processing for movement: antennal and cercal mediation of escape turning in the cockroach. In: Beer, R.D., Ritzmann, R.E., McKenna, T. (Eds.), Biological Neural Networks in Invertebrate Neuroethology and Robotics. Academic Press, New York, pp. 89–112. 433 Comer, C.M., Dowd, J.P., Stubblefield, G., 1988. Escape responses following elimination of the giant interneuron pathway in the cockroach, Periplaneta americana. Brain Res. 445, 370 –375. Comer, C.M., Mara, E., Murphy, K.A., Getman, M., Mungy, M.C., 1994. Multisensory control of escape in the cockroach Periplaneta americana II. Patterns of touch-evoked behavior. J. Comp. Physiol. 174, 13 – 26. Dagan, D., Camhi, J.M., 1979. Responses to wind recorded from the cercal nerve of the cockroach Periplaneta americana. II. Directional selectivity of the sensory neurons innervating single columns of filiform hairs. J. Comp. Physiol. 133, 103 – 110. Dagan, D., Volman, S., 1982. Sensory basis for directional wind detection in first instar cockroaches, Periplaneta americana. J. Comp. Physiol. 147, 471 – 478. Daley, D.L., Delcomyn, F., 1980. Modulation of excitability of cockroach giant interneurons during walking I. Simultaneous excitation and inhibition. J. Comp. Physiol. 138, 231 – 239. Daley, D.L., Camhi, J.M., 1988. Connectivity pattern of the cercalto-giant interneuron system of the American cockroach. J. Neurophysiol. 60, 1350 – 1368. David, J.A., Pitman, R.M., 1995. Muscarinic agonists modulate calcium-dependent outward currents in an identified insect motoneurone. Brain Res. 669, 153 – 156. David, J.A., Pitman, R.M., 1996. Modulation of Ca++ and K+ conductances in an identified insect neurone by the activation of an alpha-bungarotoxin-resistant cholinergic receptor. J. Exp. Biol. 199, 1921 – 1930. Davis, G.W., Murphey, R.K., 1994a. Long-term regulation of shortterm transmitter release properties: Retrograde signaling and synaptic development. Trends Neurosci. 17, 9 – 13. Davis, G.W., Murphey, R.K., 1994b. Retrograde signaling and the development of transmitter release properties in the invertebrate nervous system. J. Neurobiol. 25, 740 – 756. Dawson, J.W., 1995. A neurophysiological description of the cpg underlying sound production in two species of tiger moths (Lepidoptera: Arctiidae). Abstract. deBelle, S., Heisenberg, M., 1994. Associative odor learning in Drosophila abolished by chemical ablation of the mushroom bodies. Science 263, 692 – 695. Dethier, V.G., 1963. The Physiology of Insect Senses. Wiley, New York, p. 266. Dethier, V.G., 1976. The Hungry Fly. Harvard University Press, Cambridge, p. 489. Doe, C., 1992. Molecular markers for identified neuroblasts and ganglion mother cells in the Drosophila central nervous system. Development 116, 855 – 864. Doherty, J.A., 1991. Song recognition and localization in the phonotaxis behavior of the field cricket, Gryllus bimaculatus. J. Comp. Physiol. 168, 213 – 222. Dowd, J.P., Comer, C.M., 1988. The neural basis of orienting behavior: a computational approach to the escape turn of the cockroach. Biol. Cybernet. 60, 37 – 48. Dumont, J.P.C., Robertson, R.M., 1986. Neuronal circuits: an evolutionary perspective. Science 233, 849 – 853. Edwards, J.S., 1977. One organism, several brains: evolution and development of the insect central nervous system. Ann. NY Acad. Sci. 299, 59 – 71. Edwards, J.S., 1997. The evolution of insect flight: implications for the evolution of the nervous system. Brain Behav. Evol. 50, 8–12. Edwards, J.S., Reddy, R., 1986. Mechanosensory appendages and giant interneurons in the firebrat (Thermobia domestica, Thysanura): a prototype system for predator evasion. J. Comp. Neurol. 243, 535 – 546. Edwards, J.S., Palka, J., 1991. Insect neural evolution — a fugue or an opera? Sem. Neurosci. 3, 391 – 398. Egelhaaf, M., Borst, A., 1993. A look into the cockpit of the fly: visual orientation, algorithms, and identified neurons. J. Neurosci. 13, 4563 – 4574. 434 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Egelhaaf, M., Borst, A., 1995. Calcium accumulation in visual interneurons of the fly: stimulus dependence and relationship to membrane potential. J. Neurophysiol. 73, 2540–2552. Egelhaaf, M., Borst, A., Warzecha, A.-K., Flecks, S., Wildemann, A., 1993. Neural circuit tuning fly visual neurons to motion of small objects II. Input organization of inhibitory circuit elements revealed by electrophysiological and optical recording techniques. J. Neurophysiol. 69, 340–351. Elsner, N., 1974. Neural economy: bifunctional muscles and common central pattern elements in leg and wing stridulation of the grasshopper Stenobothrus ribicundus. J. Comp. Physiol. A 89, 227 – 236. Elsner, N., 1983. A neuroethological approach to the phylogeny of leg stridulation in gomphocerine grasshoppers. In: Huber, F., Markl, H. (Eds.), Neuroethology and Behavioural Physiology. Springer, Berlin, pp. 54–68. Elsner, N., Popov, A.V., 1978. Neuroethology of acoustic communication. Adv. Insect Physiol. 13, 229–355. Evans, P.D., O’Shea, M., 1978. The identification of an octopaminergic neurone and the modulation of a myogenic rhythm in the locust. J. Exp. Biol. 73, 235–260. Foster, J.A., Robertson, R.M., 1992. Temperature dependency of wing-beat frequency in intact and deafferented locusts. J. Exp. Biol. 162, 295 – 312. Fox, P.T., Mitiken, S., Davis, G., Lancaster, J.L., 1993. Brainmap: a database of human functional brainmapping. In: Thatcher, R.W., Hallet, M., Zeffiro, T., John, E.R., Huerta, M. (Eds.), Advances in Functional Neuroimaging: Technical Foundations. Academic Press, Orlando. Ganihar, D., Libersat, F., Wendler, G., Camhi, J.M., 1994. Windevoked escape responses in flying cockroaches. J. Comp. Physiol. 175, 49 – 65. Gee, C.E., Robertson, R.M., 1994. Effects of maturation on synaptic potentials in the locust flight system. J. Comp. Physiol. A 175, 437 – 447. Gee, C.E., Robertson, R.M., 1996. Recovery of the flight system following ablation of the tegulae in immature adult locusts. J. Exp. Biol. 199, 1395 –1403. Gee, C.E., Robertson, R.M., 1997. Free-flight ability in locusts recovering from peripheral injury. Naturwissenschaften, in press. Georgopoulos, A., 1990. Neural coding of the direction of reaching and a comparison with saccadic eye movements. Cold Spring Harbor Symposium. Quant. Biol. 55, 849–859. Gilbert, C., Strausfeld, N.J., 1991. The functional organization of male-specific visual neurons in flies. J. Comp. Physiol. 169, 395 – 411. Goodman, C.S., 1994. The likeness of being: phylogenetically conserved molecular mechanisms of growth cone guidance. Cell 78, 353 – 356. Gramoll, S., Elsner, N., 1987. The morphology of local ‘stridulation’ interneurons in the metathoracic ganglion of the acridid grasshopper Omocestus 6iridulus. J. Comp. Physiol. 263, 593–606. Gras, H., Hörner, M., Schürmann, F.-W., 1994. A comparison of spontaneous and wind-evoked running modes in crickets and cockroaches. J. Insect Physiol. 40, 373–384. Gray, J.R., Robertson, R.M., 1994. Activity of the forewing stretch receptor in immature and mature adult locusts. J. Comp. Physiol. A 175, 425 – 435. Gray, J.R., Robertson, R.M., 1996. Structure of the forewing stretch receptor axon in immature and mature adult locusts. J. Comp. Neurol. 365, 268 – 277. Gray, J.R., Robertson, R.M., 1997a. Co-ordination of the flight motor pattern with forewing stretch receptor stimulation in immature and mature adult locusts. Comp. Biochem. Physiol. A: Comp. Physiol. 118, 125–130. Gray, J.R., Robertson, R.M., 1997b. Discrimination of looming object trajectory by a right/left pair of movement detector interneurons in the locust. Bull. Can. Soc. Zool. 28, 77. Gray, J.R., Robertson, R.M., 1997c. Effects of heat stress on axonal conduction in the locust flight system. Comp. Biochem. Physiol., in press. Grillner, S., 1985. Neurobiological bases of rhythmic motor acts in vertebrates. Science 228, 143 – 149. Grillner, S., 1996. Neural networks for vertebrate locomotion. Sci. Am. 274, 64 – 69. Grillner, S., Wallen, P., Brodin, L., Lansner, A., 1991. Neuronal network generating locomotor behavior in lamprey. Annu. Rev. Neurosci. 14, 169 – 199. Grimm, K., Sauer, A.E., 1995. The high number of neurons contributes to the robustness of the locust flight-CPG against parameter variation. Biol. Cybernet. 72, 329 – 335. Griss, C., Rowell, C.H.F., 1986. Three descending interneurons reporting deviation from course in the locust I. Anatomy. J. Comp. Physiol. 158, 765 – 774. Groh, J.M., Born, R.T., Newsome, W.T., 1997. How is a sensory map read out? Effects of microstimulation in visual area MT on saccades and smooth pursuit eye movements. J. Neurosci. 17, 4312 – 4330. Gronenberg, W., Strausfeld, N.J., 1991. Descending pathways connecting the male-specific visual system of flies to the neck and flight motor. J. Comp. Physiol. 169, 413 – 426. Gynther, I.C., Pearson, K.G., 1986. Intracellular recording from interneurons and motoneurones during bilateral kicks in the locust: implications for mechanisms. J. Exp. Biol. 122, 323–343. Gynther, I.C., Pearson, K.G., 1989. An evaluation of the role of identified interneurons in triggering kicks and jumps in the locust. J. Neurophysiol. 61, 45 – 57. Haag, J., Borst, A., 1997. Encoding of visual motion information and reliability in spiking and graded potential neurons. J. Neurosci. 17, 4809 – 4819. Hagiwara, S., Watanabe, A., 1956. Discharges in motoneurons of cicadas. J. Cell Comp. Physiol. 47, 415 – 428. Hammer, M., 1997. The neural basis of associative reward learning in honeybees. Trends Neurosci. 20, 245 – 252. Hamon, A., Guillet, J.C., Callec, J.J., 1994. Patterns of monosynaptic input to the giant interneurons 1 – 3 in the cercal system of the adult cockroach. J. Comp. Physiol. 174, 91 – 102. Hardie, R.C., Minke, B., 1993. Novel Ca+ + channels underlying transduction in Drosophila photoreceptors: implications for phosphoinositide-mediated Ca + + mobilization. Trends Neurosci. 16, 371 – 376. Harris-Warrick, R.M., Marder, E., 1991. Modulation of neural networks for behavior. Annu. Rev. Neurosci. 14, 39 – 57. Hatsopoulos, N.G., Burrows, M., Laurent, G., 1995. Hysteresis reduction in proprioception using presynaptic shunting inhibition. J. Neurophysiol. 73, 1031 – 1042. Hausen, K., 1982. Motion sensitive interneurons in the optomotor system of the fly. I. Horizontal cells: structure and signals. Biol. Cybernet. 45, 143 – 156. Hedwig, B., 1986a. On the role in stridulation of plurisegmental interneurons of the acridid grasshopper Omocestus 6iridulus I. Anatomy. J. Comp. Physiol. 158, 413 – 427. Hedwig, B., 1986b. On the role in stridulation of plurisegmental interneurons of the acridid grasshopper Omocestus 6iridulus II. Physiology. J. Comp. Physiol. 158, 429 – 444. Hedwig, B., 1992a. On the control of stridulation in the acridid grasshopper Omocestus 6iridulus. II. Shaping of hindleg movements by spiking and non-spiking interneurons. J. Comp. Physiol. A 171, 129 – 140. Hedwig, B., 1992b. On the control of stridulation in the acridid grasshopper Omocestus 6iridulus. I. Interneurons involved in rhythm generation and bilateral coordination. J. Comp. Physiol. A 171, 117 – 128. Hedwig, B., 1994. A cephalothoracic command system controls stridulation in the acridid grasshopper Omocestus 6iridulus. J. Neurophysiol. 72, 2015 – 2025. C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Hedwig, B., Burrows, M., 1996. Presynaptic inhibition of sensory neurons during kicking movements in the locust. J. Neurophysiol. 75, 1221 – 1232. Heinrich, R., Hedwig, B., Elsner, N., 1997. Cholinergic activation of stridulatory behaviour in the grasshopper Omocestus 6iridulus. J. Exp. Biol. 200, 1327 –1337. Heisenberg, M., Kaiser, K., 1995. The Flybrain project. Trends Neurosci. 18, 481 – 483. Heisenberg, M., Heusipp, M., Wanke, C., 1995. Structural plasticity in the Drosophila brain. J. Neurosci. 15, 1951–1960. Heitler, W.J., Burrows, M., 1977a. The locust jump. I. The motor programme. J. Exp. Biol. 66, 203–219. Heitler, W.J., Burrows, M., 1977b. The locust jump. II. Neural circuits of the motor programme. J. Exp. Biol. 66, 221–241. Hennig, R.M., 1988. Ascending auditory interneurons in the cricket Teleogryllus commodus: comparative physiology and direct connections with afferents. J. Comp. Physiol. 163, 135–143. Hennig, R.M., 1990a. Neuronal control of the forewings in two different behaviours. J. Comp. Physiol. A 167, 617–627. Hennig, R.M., 1990b. Neuronal organization of the flight motor pattern in the cricket Teleogryllus commodus. J. Comp. Physiol. A 167, 629 – 639. Holmqvist, M.H., Srinivasan, M.V., 1991. A visually evoked escape response of the housefly. J. Comp. Physiol. A 169, 451–459. Homberg, U., Christiansen, T.A., Hildebrand, J.G., 1989. Structure and function of the deutocerebrum in insects. Ann. Rev. Entomol. 34, 477 – 501. Horseman, G., Huber, F., 1994a. Sound localization in crickets I. Contralateral inhibition of an ascending auditory interneuron (AN1) in the cricket Gryllus bimaculatus. J. Comp. Physiol. 175, 389 – 398. Horseman, G., Huber, F., 1994b. Sound localization in crickets II. Modelling the role of a simple neural network in the prothoracic ganglion. J. Comp. Physiol. 175, 399–413. Hoy, R., 1990. Evolutionary innovation in behavior and speciation: opportunities for behavioral neuroethology. Brain Behav. Evol. 36, 141 – 153. Hoy, R., Nolen, T., Brodfuehrer, P., 1989. The neuroethology of acoustic startle and escape in flying insects. J. Exp. Biol. 146, 287 – 306. Hoyle, G., 1975. Evidence that insect dorsal unpaired median (DUM) neurons are octopaminergic. J. Exp. Zool. 189, 425–431. Hoyle, G., 1983. On the way to neuroethology: the identified neuron approach. In: Huber, F., Markl, H. (Eds.), Neuroethology and Behavioral Physiology. Springer, Berlin, pp. 9–25. Hoyle, G., Burrows, M., 1973. Neural mechanisms underlying behavior in the locust Schistocerca gregaria. I. Physiology of identified motoneurons. J. Neurobiol. 4, 3–41. Huber, F., 1988. Invertebrate neuroethology: guiding principles. Experientia 44, 428 – 431. Huber, F., Moore, T.E., Loher, W., 1989. Cricket Neurobiology and Behavior. Comstock Publishing, Cornell University Press, Ithaca, p. 565. Huber, F., Kleindienst, H.-U., Weber, T., Thorson, J., 1984. Auditory behavior of the cricket. III. tracking of male calling song by surgically and developmentally one-eared females, and the curious role of the anterior tympanum. J. Comp. Physiol. 155, 725 – 738. Hue, B., Callec, J.J., 1983. Presynaptic inhibition in the cercal-afferent giant interneuron synapse of the cockroach Periplaneta americana. J. Insect Physiol. 29, 741–748. Ito, K., Awano, W., Suzuli, K., Hiromi, Y., Yamamoto, D., 1997. The Drosophila mushroom body is a quadruple structure of clonal units each of which contains a virtually identical set of neurones and glial cells. Development 124, 761–771. Jacobs, G.A., Murphey, R.K., 1987. Segmental origins of the cricket giant interneuron system. J. Comp. Neurol. 265, 145–157. 435 Jacobs, G.A., Theunissen, F.E., 1996. Functional organization of a neural map in the cricket cercal sensory system. J. Neurosci. 16, 769 – 784. Jellema, T., Heitler, W.J., 1997. Adaptive reconfiguration of a reflex circuit during different motor programmes in the locust. J. Comp. Physiol. 180, 659 – 669. Johnston, R.M., Levine, R.B., 1996. Crawling motor patterns induced by pilocarpine in isolated larval nerve cords of Manduca sexta. J. Neurophysiol. 76, 3178 – 3195. Judge, S.J., Rind, F.C., 1997. The locust DCMD, a movement-detecting neurone tightly tuned to collision trajectories. J. Exp. Biol. 200, 2209 – 2216. Kaas, J.H., 1991. Plasticity of sensory and motor maps in adult mammals. Annu. Rev. Neurosci. 14, 137 – 167. Kämper, G., Murphey, R.K., 1994. Maturation of an insect nervous system: constancy in the face of change. Comp. Biochem. Physiol. A 109, 23 – 32. Kandel, E., 1976. Cellular Basis of Behavior. In: An introduction to Behavioral Neurobiology. W.H. Freeman, San Francisco, p. 727. Kanzaki, R., Arbas, E.A., Hildebrand, J.G., 1991. Physiology and morphology of descending neurons in pheromone-processing olfactory pathways in the male moth Manduca sexta. J. Comp. Physiol. 169, 1 – 14. Kanzaki, R., Ikeda, A., Shibuya, T., 1994. Morphological and physiological properties of pheromone triggered flip-flopping descending interneurons of the male silkworm moth, Bombyx mori. J. Comp. Physiol. 175, 1 – 14. Katz, P.S., 1996. Neurons, networks and motor behavior. Neuron 16, 245 – 253. Kendig, J.J., 1968. Motor neurone coupling in locust flight. J. Exp. Biol. 48, 389 – 404. Kent, K.S., Consoulas, C., Duncan, K., Johnston, R.M., Luedeman, R., Levine, R.B., 1995. Remodelling of neuromuscular systems during insect metamorphosis. Am. Zool. 35, 578 – 584. Keshishian, H., Broadie, K., Chiba, A., Bate, M., 1996. The Drosophila neuromuscular junction: a model system for studying synaptic development and function. Annu. Rev. Neurosci. 19, 545 – 575. Knudsen, E.I., duLac, S., Esterly, S.D., 1987. Computational maps in the brain. Ann. Rev. Neurosci. 10, 41 – 65. Koch, C., 1997. Computation and the single neuron. Nature (London) 385, 207 – 210. Koenig, J.H., Ikeda, K., 1983. Characterization of the intracellularly recorded response of identified flight motor neurons in Drosophila. J. Comp. Physiol. 150, 295 – 303. Kohstall-Schnell, D., Gras, H., 1994. Activity of giant interneurons and other wind-sensitive elements of the terminal ganglion in the walking cockroach. J. Exp. Biol. 193, 157 – 181. Kolton, L., Camhi, J.M., 1995. Cartesian representation of stimulus direction: parallel processing by two sets of giant interneurons in the cockroach. J. Comp. Physiol. 176, 691 – 702. Kondoh, Y., Hasegawa, Y., Okuma, J., Takahashi, F., 1995. Neural computation of motion in the fly visual system: quadratic nonlinearity of responses induced by picrotoxin in the HS and CH cells. J. Neurophysiol. 74, 2665 – 2684. Kristan, W.B., Jr, 1992. Neuronal basis of behavior. Curr. Opin. Neurobiol. 2, 781 – 787. Kutsch, W., 1989. Development of the flight motor pattern. In: Goldsworthy, G.I., Wheeler, C.H. (Eds.), Insect Flight. CRC Press, Boca Raton, FL, pp. 51 – 73. Kutsch, W., Stevenson, P., 1984. Manipulation of the endocrine system of Locusta and the development of the flight motor pattern. J. Comp. Physiol. 155, 129 – 138. Landolfa, M., Jacobs, G.A., 1995. Direction sensitivity of the filiform hair population of the cricket cercal system. J. Comp. Physiol. 177, 759 – 766. 436 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Laurent, G., 1996. Dynamical representation of odors by oscillating and evolving neural assemblies. Trends Neurosci. 19, 489– 497. Laurent, G., Davidowitz, H., 1994. Encoding of olfactory information with oscillating neural assemblies. Science 265, 1872– 1875. Laurent, G., Wehr, M., Davidowitz, H., 1996. Temporal representations of odors in an olfactory network. J. Neurosci. 16, 3837 – 3847. Levi, R., Camhi, J.M., 1994. Testing for a population vector code for wind direction in the cockroach giant interneurons. Soc. Neurosci. (Abstract) 20, 1025. Levine, R.B., Morton, D.B.and, Restifo, L.L., 1995. Remodeling of the insect nervous system. Curr. Opin. Neurobiol. 5, 28–35. Levine, R.B., Murphey, R.K., 1980. Pre-and postsynaptic inhibition of identified giant interneurons in the cricket (Acheta domesticus). J. Comp. Physiol. 135, 269–282. Libersat, F., 1992. Modulation of flight by giant interneurons of the cockroach. J. Comp. Physiol. 170, 379–392. Liebenthal, E., Uhlmann, O., Camhi, J.M., 1994. Critical parameters of the spike trains in a cell assembly: coding of turn direction by the giant interneurons of the cockroach. J. Comp. Physiol. 174, 281 – 296. Lins, F., Lakes-Harlan, R., 1994. Interneurons with inhibitory effects on stridulation in grasshoppers exhibit GABA-like immunoreactivity. Brain Res. 635, 103–112. Marder, E., Calabrese, R.L., 1996. Principles of rhythmic motor pattern generation. Physiol. Rev. 76, 687–717. Matheson, T., 1997. Octopamine modulates the responses and presynaptic inhibition of proprioceptive sensory neurones in the locust Schistocerca gregaria. J. Exp. Biol. 200, 1317–1325. Matsumoto, S.G., Hildebrand, J.G., 1981. Olfactory mechanisms in the moth Manduca sexta: response characteristics and morphology of central neurons in the antennal lobe. Proc. R. Soc. Lond. B 213, 249 – 277. Mauelshagen, J., 1995. Neural correlates of olfactory learning paradigms in an identified neuron in the honeybee brain. J. Neurophysiol. 69, 609–625. Meinhertzhagen, I.A., Pyza, E., 1996. Daily rhythms in cells of the fly’s optic lobe: taking time out from the circadian clock. Trends Neurosci. 19, 285 – 291. Miller, J.P., Jacobs, G.A.and, Theunissen, F.E., 1991. Representation of sensory information in the cricket cercal sensory system I. Response properties of the primary interneurons. J. Neurophysiol. 66, 1680 – 1689. Mizunami, M., 1994. Information processing in the insect ocellar system: comparative approaches to the evolution of visual processing and neural circuits. Adv. Insect Physiol. 25, 151–265. Mizunami, M., Weibrecht, J.M., Strausfeld, N.J., 1993. A new role for the insect mushroom bodies: place memory and motor control. In: Beer, R.D., Ritzmann, R.E., McKenna, T. (Eds.), Biological Neural Networks in Invertebrate Neuroethology and Robotics. Academic Press, New York, pp. 199–225. Moiseff, A., Pollack, G.S., Hoy, R.R., 1978. Steering responses of flying crickets to sound and ultrasound: mate attraction and predator avoidance. Proc. Natl. Acad. Sci. USA 75, 4052– 4056. Möhl, B., 1988. Short-term learning during flight control in Locusta migratoria. J. Comp. Physiol. 163, 803–812. Möhl, B., 1993. The role of proprioception for motor learning in locust flight. J. Comp. Physiol. 172, 325–332. Morton, D.W., Chiel, H.J., 1994. Neural architectures for adaptive behavior. Trends Neurosci. 17, 413–420. Murphey, R.K., 1985. A second cricket cercal sensory system: bristle hairs and the interneurons they activate. J. Comp. Physiol. 156, 357 – 367. Murphey, R.K., 1986. The myth of the inflexible invertebrate: competition and synaptic remodelling in the development of invertebrate nervous systems. J. Neurobiol. 17, 585–591. Murphey, R.K., Davis, G.W., 1994. Retrograde signaling at the synapse. J. Neurobiol. 25, 595 – 598. Murphey, R.K., Lemere, C.A., 1984. Competition controls the growth of an identified axonal arborization. Science 224, 1353– 1354. Nässel, D.R., 1996. Neuropeptides, amines and amino acids in an elementary insect ganglion: functional and chemical anatomy of the unfused abdominal ganglion. Prog. Neurobiol. 48, 325–331. Nicklaus, R., 1965. Die Erregung einzellner Fadenhaare von Periplaneta americana in Abhangigkeit von der Grosse und Richtung der Auslenkung. Z. Vergl. Physiol. 50, 331 – 362. Nolen, T.G., Hoy, R.R., 1984. Initiation of behavior by single neurons: the role of behavioral context. Science 226, 992–994. O’Carroll, D.C., Bidwell, N.J., Laughlin, S.B., Warrant, E.J., 1996. Insect motion detectors matched to visual ecology. Nature (London) 382, 63 – 66. Ocker, W.G., Hedwig, B., 1996. Interneurons involved in stridulatory pattern generation in the grasshopper Chorthippus mollis. J. Exp. Biol. 199, 653 – 662. Olberg, R.M., 1981. Parallel encoding of direction of wind, head, abdomen, and visual pattern movement by single interneurons in the dragonfly. J. Comp. Physiol. 142, 27 – 41. Olberg, R.M., 1983. Pheromone triggered flip-flopping interneurons in the ventral nerve cord of the silkworm moth, Bombyx mori. J. Comp. Physiol. 152, 297 – 307. Orchard, I., Ramirez, J.-M., Lange, A.B., 1993. A multifunctional role for octopamine in locust flight. Annu. Rev. Entomol. 38, 227 – 249. O’Shea, M., Rowell, C.H.F., Williams, J.L.D., 1974. The anatomy of a locust visual interneuron: the descending contralateral movement detector. J. Exp. Biol. 60, 1 – 12. O’Shea, M., Rowell, C.H.F., 1977. Complex neural integration and identified interneurons in the locust brain. In: Hoyle, G. (Ed.), Identified Neurons and Behavior of Arthropods. Plenum, New York, pp. 307 – 328. Osorio, D., Averof, M., Bacon, J.P., 1995. Arthropod evolution: great brains, beautiful bodies. Trends Ecol. Evol. 10, 449–454. Osorio, D., Bacon, J.P., 1994. A good eye for arthropod evolution. BioEssays 16, 419 – 424. Otto, D., Hennig, R.M., 1993. Interneurons descending from the cricket subesophageal ganglion control stridulation and ventilation. Naturwissenschaften 80, 36 – 38. Parker, D., 1996. Octopaminergic modulation of locust motor neurones. J. Comp. Physiol. 178, 243 – 252. Pearson, K.G., 1993. Common principles of motor control in vertebrates and invertebrates. Annu. Rev. Neurosci. 16, 265 –297. Pearson, K.G., 1995. Proprioceptive regulation of locomotion. Curr. Opin. Neurobiol. 5, 786 – 791. Pearson, K.G., Fourtner, C.R., 1975. Non-spiking interneurons in the walking system of the cockroach. J. Neurophysiol. 38, 33–52. Pearson, K.G., Goodman, C.S., 1981. Presynaptic inhibition of transmission from identified interneurons in locust central nervous system. J. Neurophysiol. 45, 501 – 515. Pearson, K.G., O’Shea, M., 1984. Escape behavior of the locust. The jump and its initiation by visual stimuli. In: Eaton, R.C. (Ed.), Neural Mechanisms of Startle Behavior. Plenum Press, pp. 163– 178. Pearson, K.G., Ramirez, J.-M., 1992. Parallels with other invertebrate and vertebrate motor systems. In: Harris-Warrick, R.M., Marder, E., Selverston, A.I., Moulins, M. (Eds.), Dynamic Biological Networks. MIT Press, Cambridge, MA, pp. 263–281. Pearson, K.G., Wolf, H., 1989. Timing of forewing elevator activity during flight in the locust. J. Comp. Physiol. A 165, 217–227. Pearson, K.G., Hedwig, B., Wolf, H., 1989. Are the hindwing chordotonal organs elements of the locust flight pattern generator. J. Exp. Biol. 144, 235 – 255. C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Pflüger, H.-J., Hurdelbrink, S., Czjzek, A., Burrows, M., 1994. Activity-dependent structural dynamics of insect sensory fibers. J. Neurosci. 14, 6946 – 6955. Pichon, Y., Boistel, J., 1963. Modifications of the ionic content of the haemolymph and of the acitivity of Periplaneta americana in relation to diet. J. Insect Physiol. 9, 887–891. Pitman, R.M., Tweedle, C.D., Cohen, M.J., 1972. Branching of central neurons: intracellular cobalt injection for light and electron microscopy. Science 176, 412–414. Pollack, A.J., Ritzmann, R.E., Watson, J.T., 1995. Dual pathways for tactile sensory information to thoracic interneurons in the cockroach. J. Neurobiol. 26, 33–46. Pollack, G.S., 1986. Discrimination of calling song models by the cricket, Teleogryllus oceanicus: the influence of sound direction on neural encoding of the stimulus temporal pattern and on phonotactic behavior. J. Comp. Physiol. 158, 549–561. Ramirez, J., Orchard, I., 1990. Octopaminergic modulation of the forewing stretch receptor in the locust Locusta migratoria. J. Exp. Biol. 149, 255 – 279. Ramirez, J.-M., Pearson, K.G., 1988. Generation of motor patterns for walking and flight in motoneurons supplying bifunctional muscles in the locust. J. Neurobiol. 19, 257–282. Ramirez, J.-M., Pearson, K.G., 1989. Distribution of intersegmental interneurons that can reset the respiratory rhythm of the locust. J. Exp. Biol. 141, 151 – 176. Ramirez, J.-M., Pearson, K.G., 1991a. Octopaminergic modulation of interneurons in the flight system of the locust. J. Neurophysiol. 66, 1522 – 1537. Ramirez, J.-M., Pearson, K.G., 1991b. Octopamine induces bursting and plateau potentials in insect neurons. Brain Res. 549, 332 – 337. Ramirez, J.-M., Büschges, A., Kittmann, R., 1993. Octopaminergic modulation of the femoral chordotonal organ in the stick insect. J. Comp. Physiol. 173, 209–219. Rast, G.F., Bräunig, P., 1997. Pilocarpine-induced motor rhythms in the isolated locust suboesophageal ganglion. J. Exp. Biol. 200, 2197 – 2207. Reichardt, W., 1987. Evaluation of optical information by movement detectors. J. Comp. Physiol. 161, 533–547. Reichert, H., 1989. Neural mechanisms underlying axial/appendicular steering reactions in locust flight. Am. Zool. 29, 161–169. Reichert, H., Boyan, G., 1997. Building a brain: developmental insights in insects. Trends Neurosci. 20, 258–264. Rind, F.C., Simmons, P.J., 1992. Orthopteran DCMD neuron: a reevaluation of responses to moving objects. I. Selective responses to approaching objects. J. Neurophysiol. 68, 1654–1666. Ritzmann, R.E., 1981. Motor responses to paired stimulation of giant interneurons in the cockroach Periplaneta americana II. The ventral giant interneurons. J. Comp. Physiol. 143, 71–80. Ritzmann, R.E., Pollack, A.J., 1986. Identification of thoracic interneurons that mediate giant interneuron-to-motor pathways in the cockroach. J. Comp. Physiol. 159, 639–654. Ritzmann, R.E., Pollack, A.J., 1990. Parallel motor pathways from thoracic interneurons of the ventral giant interneuron system of the cockroach, Periplaneta americana. J. Neurobiol. 21, 1219 – 1235. Ritzmann, R.E., Pollack, A.J., 1994. Responses of thoracic interneurons to tactile stimulation in the cockroach, Periplaneta americana. J. Neurobiol. 25, 1113–1128. Ritzmann, R.E., Tobias, M.L., Fourtner, C.R., 1982. Flight activity initiated via giant interneurons of the cockroach: evidence for bifunctional trigger interneurons. Science 210, 443–445. Ritzmann, R.E., Pollack, A.J., Hudson, S.E., Hyvonen, A., 1991. Convergence of multi-modal sensory signals at thoracic interneurons of the escape system of the cockroach, Periplaneta americana. Brain Res. 563, 175–183. Robertson, R.M., 1986. Neuronal circuits controlling flight in the locust: central generation of the rhythm. Trends Neurosci. 9, 278 – 280. 437 Robertson, R.M., 1987a. Interneurons in the flight system of the cricket Teleogryllus oceanicus. J. Comp. Physiol. A 160, 431–445. Robertson, R.M., 1987b. Insect neurons: synaptic interactions, circuits and the control of behavior. In: Ali, M.A. (Ed.), Nervous Systems of Invertebrates. Plenum Publishing, New York, pp. 393 – 442. Robertson, R.M., 1989. Idiosyncratic computational units generating innate motor patterns: neurones and circuits in the locust flight system. In: Durbin, R., Miall, R.C., Mitchison, G. (Eds.), The Computing Neurone. Addison-Wesley, London, pp. 262–277. Robertson, R.M., 1993. Effects of temperature on synaptic potentials in the locust flight system. J. Neurophysiol. 70, 2197 – 2204. Robertson, R.M., 1995. Locust flight: components and mechanisms in the motor. In: Arbib, M.A. (Ed.), The Handbook of Brain Theory and Neural Networks. MIT Press, Cambridge, MA, pp. 556 – 560. Robertson, R.M., Pearson, K.G., 1982. A preparation for the intracellular analysis of neuronal activity during flight in the locust. J. Comp. Physiol. 146, 311 – 320. Robertson, R.M., Pearson, K.G., 1983. Interneurons in the flight system of the locust: distribution, connections, and resetting properties. J. Comp. Neurol. 215, 33 – 50. Robertson, R.M., Pearson, K.G., 1985a. Neural circuits in the flight system of the locust. J. Neurophysiol. 53, 110 – 128. Robertson, R.M., Pearson, K.G., 1985b. Neural networks controlling locomotion in locusts. In: Selverston, A.I. (Ed.), Model Neural Networks and Behavior. Plenum Press, New York, pp. 21–35. Robertson, R.M., Reye, D.N., 1992. Wing movements associated with collision avoidance maneuvers during flight in the locust Locusta migratoria. J. Exp. Biol. 163, 231 – 258. Robertson, R.M., Pearson, K.G., Reichert, H., 1982. Flight interneurons in the locust and the origin of insect wings. Science 217, 177 – 179. Robertson, R.M., Xu, H., Shoemaker, K.L., Dawson-Scully, K., 1996. Exposure to heat shock affects thermosensitivity of the locust flight system. J. Neurobiol. 29, 367 – 383. Roeder, K.D., 1959. A physiological approach to the relation between prey and predator. Smithson. Misc. Coll. 137, 287–306. Roeder, K.D., 1963. Nerve Cells and Insect Behavior. Harvard University Press, Cambridge, USA, p. 238 second edn., 1967. Ronacher, B., 1989. Stridulation of acridid grasshoppers after hemisection of thoracic ganglia: evidence for hemiganglionic oscillators. J. Comp. Physiol. 164, 723 – 736. Ronacher, B., Wolf, H., Reichert, H., 1988. Locust flight behavior after hemisection of individual thoracic ganglia: evidence for hemiganglionic premotor centers. J. Comp. Physiol. 163, 749– 759. Rospars, J.P., 1983. Invariance and sex-specific variations of the glomerular organization in the antennal lobes of a moth and a butterfly. J. Comp. Neurol. 220, 80 – 96. Rowell, C.H.F., 1971. The orthopteran descending movement detector (DMD) neurones: a characterization and review. Z. Vergl. Physiol. 73, 167 – 194. Rowell, C.H.F., 1988. The taxonomy of invertebrate neurons: a plea for a new field. Trends Neurosci. 12, 169 – 174. Rowell, C.H.F., Reichert, H., 1986. Three descending interneurons reporting deviation from course in the locust II. Physiology. J. Comp. Physiol. 158, 775 – 794. Rowell, C.H.F., Reichert, H., 1991. Mesothoracic interneurons involved in flight steering in the locust. Tissue Cell 23, 75–139. Ryckebusch, S., Laurent, G., 1993. Rhythmic patterns evoked in locust leg motor neurons by the muscarinic agonist pilocarpine. J. Neurophysiol. 69, 1583 – 1595. Ryckebusch, S., Laurent, G., 1994. Interactions between segmental leg central pattern generators during fictive rhythms in the locust. J. Neurophysiol. 72, 2771 – 2785. 438 C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 Schildberger, K., Huber, F., Wohlers, D.W., 1989. Central auditory pathway: neuronal correlates of phonotactic behavior. In: Huber, F., Moore, T.E., Loher, W. (Eds.), Cricket Behavior and Neurobiology. Cornell University Press, Ithaca, pp. 423–458. Schildberger, K., Hörner, M., 1988. The function of auditory neurons in cricket phonotaxis. I. Influence of hyperpolarization of identified neurons on sound localization. J. Comp. Physiol. 163, 621 – 631. Schmitz, J., Büschges, A., Kittmann, R., 1991. Intracellular recordings from nonspiking interneurons in a semiintact, tethered walking insect. J. Neurobiol. 22, 907–921. Sejnowski, T.J., 1997. The year of the dendrite. Science 275, 178 – 179. Selverston, A., Elson, R., Rabinovich, M., Huerta, R., Abarbanel, H., 1998. Basic principles for generating motor output in the stomatogastric ganglion. Ann. NY Acad. Sci. 860, 35–50. Shaw, S.R., Meinertzhagen, I.A., 1986. Evolutionary progression at synaptic connections made by identified homologous neurones. Proc. Natl. Acad. Sci. USA 83, 7961–7965. Shimozawa, T., Kanou, M., 1984. Varieties of filiform hairs: range fractionation by sensory afferents and cercal interneurons of a cricket. J. Comp. Physiol. 155, 485–493. Simmons, P.J., Rind, F.C., 1992. Orthopteran DCMD neuron: a reevaluation of responses to moving objects. II. critical cues for detecting approaching objects. J. Neurophysiol. 68, 1667– 1682. Single, S., Haag, J., Borst, A., 1997. Dendritic computation of direction selectivity and gain control in visual interneurons. J. Neurosci. 17, 6023 – 6030. Smith, T.F., 1990. The history of genetic sequence databases. Genomics 6, 701 – 707. Smith, S.R., Wheeler, B.C., Dowd, J.P., Comer, C.M., 1991. Investigation of a multicellular neural code for directed movement. In: Proceedings 13th IEEE Conf. Engr. Med. Biol. pp. 457–459. Sombati, S., Hoyle, G., 1984. Generation of specific behaviours in a locust by local release into neuropil of the natural neuromodulator octopamine. J. Neurobiol. 15, 481–506. Spira, M.E., Zeldes, D., Hochner, B., Dorfmann, A., 1987. The effects of microenvironment on the redifferentiation of regenerating neurones: neurite architecture, acetylcholine receptors, and Ca + + channel distribution. J. Exp. Biol. 132, 111–131. Stabel, J., Wendler, G., Scharstein, H., 1989. Cricket phonotaxis: localization depends on recognition of the calling song pattern. J. Comp. Physiol. 165, 165–177. Stein, R.B., 1995. Presynaptic inhibition in humans. Prog. Neurobiol. 47, 533 – 544. Stengl, M., 1994. Inositol-triposphate-dependent calcium currents precede cation currents in insect olfactory receptor neurons in vitro. J. Comp. Physiol. 174, 187–194. Stevenson, P.A., 1997. Reflex activation of locust flight motoneurones by proprioceptors responsive to muscle contractions. J. Comp. Physiol. 180, 91 – 98. Stevenson, P.A., Kutsch, W., 1987. A reconsideration of the central pattern generator concept for locust flight. J. Comp. Physiol. 161, 115 – 129. Stevenson, P.A., Meuser, S., 1997. Octopaminergic innervation and modulation of a locust flight steering muscle. J. Exp. Biol. 200, 633 – 642. Stevenson, P.A., Spörhase-Eichmann, U., 1995. Localization of octopaminergic neurones in insects. Comp. Biochem. Physiol. 110A, 203 – 215. Stewart, W.W., 1978. Functional connections between cells, as revealed by dye-coupling with a highly fluorescent naphthalimide tracer. Cell 14, 741 – 759. Stierle, I.E., Getman, M., Comer, C.M., 1994. Multisensory control of escape in the cockroach Periplaneta americana I. Initial evidence from patterns of wind-evoked behavior. J. Comp. Physiol. 174, 1 – 11. Stopfer, M., Bhagavan, S., Smith, B.H.and, Laurent, G., 1997. Impaired odour discrimination on desynchronization of odour-encoding neural assemblies. Nature 390, 70 – 74. Stout, J., Atkins, G., Zacharias, D., 1991. Regulation of cricket phonotaxis through hormonal control of the threshold of an identified auditory neuron. J. Comp. Physiol 169, 765 – 772. Strausfeld, N.J., 1980. Male and female visual neurones in dipterous insects. Nature 283, 381 – 383. Strausfeld, N.J., 1991. Structural organization of male-specific visual neurons in Calliphorid optic lobes. J. Comp. Physiol. 169, 379– 393. Strausfeld, N.J., Hansen, L., Li, Y., Gomez, R.S., 1998. Evolution, discovery and interpretation of arthropod mushroom bodies. Learn. Mem. 5, 11 – 37. Swanson, L.W., 1995. Mapping the human brain: past, present, future. Trends Neurosci. 18, 471 – 474. Tauber, E., Camhi, J.M., 1995. The wind-evoked escape behavior of the cricket Gryllus bimaculatus: integration of behavioral elements. J. Exp. Biol. 198, 1895 – 1907. Theunissen, F.E., Miller, J.P., 1991. Representation of sensory information in the cricket cercal sensory system II. Information theoretic calculation of system accuracy and optimal tuning-curve widths of four primary interneurons. J. Neurophysiol. 66, 1690– 1703. Thomas, J.B., Wyman, R.J., 1983. Normal and mutant connectivity between identified neurons in Drosophila. Trends Neurosci. 6, 214 – 219. Tierney, A.J., 1995. Evolutionary implications of neural circuit structure and function. Behav. Processes 35, 173 – 182. Tobias, M., Murphey, R.K., 1979. The response of cercal receptors and identified interneurons in the cricket (Acheta domesticus) to airstreams. J. Comp. Physiol. 129, 51 – 59. Torkkeli, P.H., French, A.S., 1995. Slowly inactivating outward currents in a cuticular mechanoreceptor neuron of the cockroach (Periplaneta americana). J. Neurophysiol. 74, 1200 – 1211. Trimarchi, J.R., Murphey, R.K., 1997. The shaking-B2 mutation disrupts electrical synapses in a flight circuit in adult Drosophila. J. Neurosci. 17, 4700 – 4710. Trimmer, B.A., 1994. Characterization of a muscarinic current that regulates excitability of an identified insect motoneuron. J. Neurophysiol. 72, 1862 – 1873. Trimmer, B.A., 1995. Current excitement from insect muscarinic receptors. Trends Neurosci. 18, 104 – 111. Truman, J.W., 1990. Metamorphosis of the central nervous system of Drosophila. J. Neurobiol. 21, 1072 – 1084. Tyrer, N.M., Altman, J.S., 1974. Motor and sensory flight neurones in a locust demonstrated using cobalt chloride. J. Comp. Neurol. 157, 117 – 138. Uvarov, B., 1966. Grasshoppers and Locusts: Anatomy, Physiology, Development, Phase Polymorphism, Introduction to Taxonomy. Cambridge University Press, London, UK. von Helversen, O., von Helversen, D., 1994. Forces driving evolution of song and song recognition in grasshoppers. In: Schildberger, K., Elsner, N. (Eds.), Neural Basis of Behavioural Adaptations. Fischer, Stuttgart, pp. 253 – 284. von Helversen, D., von Helverson, O., 1995. Acoustic pattern recognition and orientation in orthopteran insects: parallel or serial processing? J. Comp. Physiol. 177, 767 – 774. Warzecha, A.-K., Egelhaaf, M., Borst, A., 1993. Neural circuit tuning visual interneurons to motion of small objects. I. Dissection of the circuit by pharmacological and photoinactivation techniques. J. Neurophysiol. 69, 329 – 339. Weckström, M., Laughlin, S.B., 1995. Visual ecology and voltagegated ion channels in insect photoreceptors. Trends Neurosci. 18, 17 – 21. Weeks, J.C., Levine, R.B., 1992. Endocrine influences on the postembryonic fates of identified neurons during insect metamorphosis. C.M. Comer, R.M. Robertson / Progress in Neurobiology 63 (2001) 409–439 In: Shankland, M., Macagno, E.R. (Eds.), Determinants of Neuronal Identity. Academic Press, San Diego, pp. 293–322. Weeks, J.C., Levine, R.B., 1995. Steroid hormone effects on neurons subserving behavior. Curr. Opin. Neurobiol. 5, 809–815. Weeks, J.C., Wood, E.R., 1996. Short- and long-term modification of reflex function during learning and metamorphosis in Manduca. Biol. Bull. 191, 62 – 69. Weeks, J.C., Jacobs, G.A., Pierce, J.T., Sandstrom, D.J., Streichert, L.C., Trimmer, B.A., Wiel, D.E.and, Wood, E.R., 1997. Neural mechanisms of behavioral plasticity: metamorphosis and learning in Manduca sexta. Brain Behav. Evol. 50, 69–80. Weis-Fogh, T., 1956. Biology and physics of locust flight-II. Flight performance of the desert locust (Schistocerca gregaria). Philos. Trans. R. Soc. Lond. (Biol.) 239, 459–510. Weis-Fogh, T., 1964. Biology and physics of locust flight. VIII. Lift and metabolic rate of flying locusts. J. Exp. Biol. 41, 257– 271. Westin, J., Langberg, J.J., Camhi, J.M., 1977. Responses of giant interneurons of the cockroach Periplaneta americana to wind puffs of different directions and velocities. J. Comp. Physiol. 121, 307 – 324. Westin, J., Ritzmann, R.E., Goddard, D.J., 1988. Wind-activated thoracic interneurons of the cockroach: I. Responses to controlled wind stimulation. J. Neurobiol. 19, 573–588. Whim, M.D., Evans, P.D., 1991. The role of cyclic AMP in the octopaminergic modulation of flight muscle in the locust. J. Exp. Biol. 161, 423 – 438. Whyard, S., Wyatt, G.R., Walker, V.K., 1986. The heat shock response in Locusta migratoria. J. Comp. Physiol. A B156, 813 – 817. Wilson, D.M., Weis-Fogh, T., 1962. Patterned activity of co-ordinated motor units, studied in flying locusts. J. Exp. Biol. 39, 643 – 667. Withers, G.S., Fahrbach, S.E., Robinson, G.E., 1993. Selective neuroanatomical plasticity and division of labour in the honeybee. Nature 364, 238 – 240. Wolf, H., 1993. The locust tegula: significance for flight rhythm generation, wing movement control and aerodynamic force production. J. Exp. Biol. 182, 229–253. Wolf, H., Burrows, M., 1995. Proprioceptive sensory neurons of a locust leg receive rhythmic presynaptic inhibition during walking. J. Neurosci. 15, 5623–5636. . 439 Wolf, H., Büschges, A., 1995. Nonspiking local interneurons in insect leg motor control. II. Role of nonspiking local interneurons in the control of leg swing during walking. J. Neurophysiol. 73, 1861– 1875. Wolf, H., Büschges, A., 1997. Dynamic synaptic arrangement in sensory-motor pathways of the adult locust flight system. Naturwissenschaften 84, 234 – 237. Wolf, H., Laurent, G., 1994. Rhythmic modulation of the responsiveness of locust sensory local interneurons by walking pattern generating networks. J. Neurophysiol. 71, 110 – 118. Wolf, H., Pearson, K.G., 1987a. Flight motor patterns recorded in surgically isolated sections of the ventral nerve cord of Locusta migratoria. J. Comp. Physiol. 161, 103 – 114. Wolf, H., Pearson, K.G., 1987b. Comparison of motor patterns in the intact and deafferented flight system of the locust. II. Intracellular recordings from flight motoneurons. J. Comp. Physiol. 160, 269 – 279. Wolf, H., Pearson, K.G., 1989. Comparison of motor patterns in the intact and deafferented flight system of the locust. III. Patterns of interneuronal. J. Comp. Physiol. 165, 61 – 74. Wolf, H., Ronacher, B., Reichert, H., 1988. Patterned synaptic drive to locust flight motoneurons after hemisection of thoracic ganglia. J. Comp. Physiol. 163, 761 – 769. Wyman, R.J., Thomas, J.B., Salkoff, L., King, D.G., 1984. The Drosophila giant fiber system. In: Eaton, R.C., Ritzmann, R.E. (Eds.), Neural Mechanisms of Startle Behavior. Plenum Press, New York, pp. 133 – 161. Xu, H.J., Robertson, R.M., 1994. Effects of temperature on properties of flight neurons in the locust. J. Comp. Physiol. 175, 193– 202. Xu, H.J., Robertson, R.M., 1996. Neural parameters contributing to temperature compensation in the flight CPG of the locust, Locusta migratoria. Brain Res. 734, 213 – 222. Yager, D.D., Hoy, R.R., 1989. Audition in the praying mantis: identification of an interneuron mediating ultrasonic hearing. J. Comp. Physiol. 165, 471 – 493. Yang, M.Y., Armstrong, J.D., Vilinsky, I., Strausfeld, N.J., Kaiser, K., 1995. Subdivision of the Drosophila mushroom bodies by enhancer-trap expression patterns. Neuron 15, 45 – 54. Ye, S., Comer, C.M., 1996. Correspondence of escape-turning behavior with activity of descending mechanosensory interneurons in the cockroach, Periplaneta americana. J. Neurosci. 16, 5844–5853.