Sensory Ecology and Neural Coding in Arthropods* Martin Egelhaaf, Roland Kern and Anne-Kathrin Warzecha Lehrstuhl für Neurobiologie, Fakultät für Biologie, Universität Bielefeld, Postfach 10 01 31, D-33501 Bielefeld, Germany Z. Naturforsch. 53c, 582-592 (1998); received April 9, 1998 Sensory Ecology, Behaviour, Neural Coding, Vision, Arthropods Arthropods live in almost any conceivable habitat. Accordingly, structural and functional specialisations have been described in many species which allow them to behave in an adap­ tive way with the limited computational resources of their small brains. These adaptations range from the special design of the eyes, the spectral sensitivities of their photoreceptors to the specific properties of neural circuits.

Introduction an adaptation, if it is necessary for solving a partic­ Organisms can be found in almost any habitat, ular task which can otherwise not be solved. This however harsh it may appear to humans. Since or­ is hardly ever the case, as there might be usually ganisms are the outcome of a long evolutionary other solutions to the task. We may only under­ process, they are generally conceived to be stand the significance of functional specialisations, adapted by natural selection to their respective en­ if we realise that no animal species can live every­ vironments. These adaptations manifest them­ where. Rather any environment is likely to be selves in all sorts of structural and functional spe­ structured in a characteristic way, thus constrain­ cialisations. Of course, also the behaviour of ing the sensory input an animal can expect to re­ animals as well as the underlying neuronal ma­ ceive during its lifetime. Moreover, since animals chinery are subject to evolution. The variety of be­ normally operate under closed-loop conditions, havioural specialisations might be particularly ob­ their own movements determine to a large extent vious in arthropods. Since there are so many more the dynamical properties of their sensory input. different arthropod species as compared with any Hence, at least in principle, it is possible for an other phylum - more than 3/t of all animal species animal to make reasonable predictions concerning are estimated to be arthropods! - arthropods can the structure and dynamical properties of its sen­ be found almost everywhere ranging from the sory input signals. With this in mind, we may con­ deep sea to the most lofty mountains. Accordingly, clude that a specialisation can be regarded as structural and functional specialisations are partic­ adaptive, if it makes use of the special features of ularly obvious in this phylum. a particular habitat to reach a solution which is Although it is quite easy to term a structural comparatively simple from a computational point characteristic of an animal or a particularly con­ of view, but which only works under special condi­ spicuous behavioural trait a ‘functional specialisa­ tions. Animals are usually no general purpose sys­ tion’, it is usually much harder to demonstrate that tems but have to operate only under a limited sub­ such a specialisation can really be regarded as an set of possible conditions. Hence, this so-called adaptation. Obviously, a specialisation represents ‘ecological constraint’ provides the chance to be able to do extraordinary things with even a small brain and thus, on the whole, quite limited compu­ * This communication is a contribution to the workshop tational resources. on “Natural Organisms, Artificial Organisms, and However, the behavioural performance of ani­ Their Brains” at the Zentrum für interdisziplinäre mals does not only depend on the specific charac­ Forschung (ZiF) in Bielefeld (Germany) on March 8 -1 2 , 1998. teristics of their habitat but also on constraints im­ posed by the neuronal hardware: Neurons have Reprint requests to Prof. M. Egelhaaf. Fax: (0521) 1066038. specific computational capabilities owing to their E-mail: [email protected] biophysical properties: Neurons receive their input

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Dieses Werk wurde im Jahr 2013 vom Verlag Zeitschrift für Naturforschung This work has been digitalized and published in 2013 by Verlag Zeitschrift in Zusammenarbeit mit der Max-Planck-Gesellschaft zur Förderung der für Naturforschung in cooperation with the Max Planck Society for the Wissenschaften e.V. digitalisiert und unter folgender Lizenz veröffentlicht: Advancement of Science under a Creative Commons Attribution Creative Commons Namensnennung 4.0 Lizenz. 4.0 International License. M. Egelhaaf et al. • Sensory Ecology and Neural Coding i i Arthropods 583 either directly from sensory cells or often from How to Make Efficient Use of a Predictable many interneurons. The synaptic input of a neuron Environment? is ‘integrated’ by the dendritic tree and then, possi­ Animals that live most of the time in basically bly, transformed into a sequence of action poten­ the same environment or perform particular tasks tials. Dendritic ‘integration’ has been regarded for only in certain situations can, at least in principle, long as a kind of passive summation of synaptic make use of this predictable environment to find input. Only recently voltage dependent ionic chan­ relatively low-level solutions to seemingly high- nels have been found in the dendritic membrane level tasks. We select only three relatively well- of neurons in almost all systems investigated in this analysed examples where this parsimonious com­ regard (see e.g. Koch, 1997; Regehr and Tank, putational strategy might be particularly obvious. 1994; Mel, 1994). Hence, complex computations can be accomplished even by individual nerve cells, Adaptive eye design to life in a flat world although there are only few examples where the functional significance of these complexities could Animals living in an absolutely flat world can be established (e.g. Sobel and Tank, 1994). Despite make various predictions about the outside world their complex computational capabilities, neurons from the geometry of the situation: (i) All objects are noisy elements as a consequence of stochastic that do not rise above the horizon, are smaller cellular processes, such as transmitter release and than the observing animal itself (and thus most the opening and closing of ionic channels (e.g. likely harmless), whereas objects which cross the Allen and Stevens, 1994; Hille, 1992). Conse­ line of horizon are larger (and, at least if moving, quently, the reliability of information processing is potentially dangerous), (ii) The ground surface is eventually limited by a host of noise sources. mapped onto the ventral part of the retina in such Finally, what can be achieved by nervous sys­ a way that objects are seen the more ventral in the tems is limited not just by the layout of the envi­ visual field the closer they are. Hence, the retinal ronment at a macroscopic scale but also by physics position of the base of the object relative to that at a microscopic scale. For instance, the spatio- of the horizon is thus a reliable, monocular cue to temporal resolution of visual systems is limited by the distance of an object (for review, see Zeil et al., the nature of light, which may impose severe con­ 1989). Since an object of a given size appears straints on the way visual systems are built as well under a smaller viewing angle if it is further away, as on the time scale on which behaviour is pos­ the angular resolution might be expected to sible. increase in those parts of the eye which look at The present paper will dwell upon all these as­ regions close to the horizon of the visual environ­ pects which need to be taken into account, if we ment. want to understand why animals process informa­ Certainly, the flattest of all environments is the tion in the way they do. Most of these aspects are water surface. There are various animals that live not exclusively relevant for arthropods but for ani­ at the water surface and make use of the specific mals quite generally. However, it is often in arthro­ geometry of this situation. Examples are water- pods that the significance of these aspects can be striders which live on the water surface (Dahmen, assessed particularly well. We do not intend to 1991) and water bugs which hang from the surface present a comprehensive review, but just present and look at it from below (Schwind, 1980). How­ selected examples to illustrate the general points ever, also land animals are known which live in a we want to make. All examples were chosen in the fairly flat world. A variety of crab species living realm of vision. We start by giving some examples on sandy beaches or in mudflats are particularly where animals appear to make use of the special well-analysed examples in this regard (Zeil et al., spatial layout and temporal properties of their 1989). Although amazing structural specialisations stimuli, in order to use them as efficiently as pos­ in eye design have been found which are charac­ sible to extract the behaviourally relevant infor­ teristic of each of the different animal species (see mation. Then we turn to those physical and neuro­ e.g. Land, 1990), all of them have one feature in nal constraints that eventually limit what can be common: The acuity is largest in those parts of the achieved at all by animals. eye which look at the horizon. From this acute 584 M. Egelhaaf et al. ■ Sensory Ecology and Neural Coding in Arthropods zone, the resolving power then gradually decreases displacements can be decomposed into a rota­ along the eye’s vertical axis (Schwind, 1980; Dah- tional as well as a translational component. The men, 1991; Zeil and Al-Mutairi, 1996). Especially translational component of the retinal image dis­ in crabs, comparative studies have shown that this placements induced by self-motion of the animal specialisation in eye design can be regarded as an strongly depends on the distance to objects in the adaptation to the life in a flat environment, as environment, whereas the rotational component there are no such pronounced acute zones in crab does not. This suggests that in normal feeding situ­ species which live in more complex visual environ­ ations of the hawk moth where objects in the lat­ ments, such as mangrove thickets or rocky shores eral part of the visual field are more distant than (Zeil et al., 1989). Finally, in the water bug Noto- in the frontal part, the rotational component is necta which hangs from the water surface, the spa­ much less contaminated by the translational one tial resolving power of the eye decreases from the in lateral parts of the visual field than in frontal region looking at the horizon in such a way that ones. Interestingly, the spatial sensitivity distribu­ an object of a given size, such as a prey, is viewed tion of the optomotor system of the hawk moth by approximately the same number of ommatidia helps to detect the rotational image displacements irrespective of its distance (Schwind, 1980). There­ without much interference from the translational fore, in those animals living for most of their lives components, because the optomotor system is in a flat world with its well-defined spatial charac­ most sensitive to rotational motion in the lateral teristics, eye design has been well adapted to make parts of the visual field. Likewise, translational ret­ particularly efficient use of this specific situation. inal image displacements can be detected better in the frontal visual field than in its lateral parts, which, in a typical feeding situation, is covered by Adaptive spatial sensitivity distribution in the nearby flower (Kern and Varjü, 1998). Neu­ compensatory optomotor systems rons have been found in the hawk moth’s nervous The diurnal hawk moth, Macroglossum stella- system that partly reflect these functional special­ tarum, feeds like hummingbirds. It hovers in front isations (Kern, 1998). In conclusion, the humming­ of flowers while sucking nectar. Due to its high bird hawk moth represents an example of an ani­ energy demand, the animal has to visit up to 1500 mal that takes advantage of the fact that its visual flowers a day, thus spending much of its time in environment is to some extent predictable in cer­ searching for appropriate food sources (Pfaff and tain behavioural contexts. Waterstriders are an­ Varjü, 1991). During every visit of a flower, the other example of animals which exploit specialised hawk moth is confronted with visual environments spatial sensitivity distributions of their control sys­ which are characterised by similar spatial layouts: tems compensating for translational and rotational The frontal part of the visual field is covered by self-motion, respectively, to stabilise their position the flower which is, due to the limited length of relative to their environment (Junger and Dah- the animal’s proboscis, relatively close to the ani­ men, 1991). mal - at least closer than most structures of the environment seen by the more lateral parts of Adaptive sensitivity distribution in systems detect­ the eye. ing the polarisiation pattern of the sky The spatial sensitivity distribution of the opto­ motor system that helps to stabilise the hawk Many arthropods can detect a basic property of moth’s position in front of the flower against light which normally remains invisible to us: the disturbances caused, for instance, by a gust of wind plane of polarisation. Polarised light is widespread appears to be specially adapted to cope with this in nature and provides an animal with a great deal situation. Displacements of the animal go along of additional visual information, if the plane of po­ with displacements of the retinal images of the en­ larisation can be sensed. It has been discovered vironment. These retinal image displacements can long ago for a variety of invertebrates, most nota­ be employed by the animal to control compensa­ bly for bees and ants, that these are not only able tory movements in order to stabilise its position to sense the plane of polarisation, but that they in front of the flower. In general, retinal image can use the global polarisation patterns in the sky M. Egelhaaf et al. • Sensory Ecology and Neural Coding i Arthropods 585 as a compass (Frisch, 1965). Subsequently in many as seen by the animal is symmetrical about the species photoreceptors were found to be highly solar/antisolar meridian. sensitive to the plane of polarisation: The visual pigment is a dipole and as such exhibits maximal What About Animals which Do Not Live absorption when the plane of polarisation of inci­ in a Very Predictable World? dent light is parallel to the long axis of the mole­ cule. When the visual pigment molecules are All the above mentioned adaptations to a pre­ aligned in parallel in the membranes of the micro­ dictable structure of the environment are indeed villi, as is the case in specialised photoreceptors in fascinating because they reveal how nature made certain insect species, the photoreceptor gets sen­ efficient use of this predictability and in doing so sitive to the plane of polarisation (for review, see found parsimonious solutions in terms of compu­ Waterman, 1981). However, the existence of pho­ tational expenditure to solve often quite complex toreceptors sensitive to the plane of polarisation tasks. However, there are many other animals does not explain how the global pattern of polari­ which appear to live in much less constrained envi­ sation in the sky can be evaluated and used for ronments - but, nevertheless, seem to perform visual navigation. It merely shows that the infor­ quite well. Since these animals cannot resort to mation is provided by the sensory system. the strategy to adapt their visual analysers to a Originally it was thought that insects could use predictable environment, one might envision that the knowledge about the polarisation pattern in these animals should rely, in some way, on more the sky to perform some kind of three-dimensional expensive computational strategies, thus, requiring geometrical construction and to derive from such larger nervous systems. As far as one can tell, constructions the position of the sun and, thus, there are no indications that this is the case. their orientation with respect to the sun. Since the Think, for instance, of the common Calliphorid polarisation pattern in the sky changes during the flies, which are widely used to study the neuronal day with the elevation of the sun, the animal mechanisms underlying visual orientation behavi­ would also have to know the time of day and year. our (for review, see Hausen and Egelhaaf, 1989; Such an all-inclusive solution to the problem of Egelhaaf and Borst, 1993a). Quite related Dipte- navigation by the polarisation pattern in the sky ran species can be found in often vast numbers all would be a daunting task for any system, not to around the world in habitats ranging from sheep- speak of insects with their tiny brains. Fortunately, walks in the Australian outback to apartments in there are simpler, though slightly imperfect ways European cities. Obviously, the spatial structures to solve the problem: Bees and ants use a simpli­ of these environments do not have much in com­ fied and stereotyped template of the celestial po­ mon with each other, and it is hard to see what larisation pattern. While the actual pattern features the animal should be able to rely upon changes with the elevation of the sun, the insect’s when trying to ‘make any prediction’ that can be internal representation of this pattern is 'hard used to reduce the computational expenditure of wired’ and stays in place (for review, see Rossel, the sensory mechanisms by which relevant infor­ 1989; Wehner, 1997). In a specialised region in the mation about the environment is gathered. In par­ dorsal part of the eye the photoreceptors are sen­ ticular, blowflies often appear in environments, sitive to the plane of polarisation of the incident such as the abovementioned apartment, which light and are aligned in a specific pattern. If the came only lately into existence and thus into the difference of the summated output of these retinal reach of flies. Hence, flies might have had hardly analysers of the two eyes is taken, a maximal over­ a chance to adapt phylogenetically to this particu­ all response is achieved when the animal is aligned lar sort of environment. Consequently, many Calli­ with the solar/antisolar meridian. As the animal phorid flies appear to be generalists which can well rotates about its vertical body axis, the match be­ survive in almost any kind of visual environment. tween the polarisation pattern and the sensory fil­ Nonetheless, their brains are not bigger nor more ter deteriorates systematically. In this way, no mis­ complex, at least on the basis of their gross mor­ takes in orientation are made, irrespective of the phology, than those of the above described special­ time of day, if the polarisation pattern in the sky ists. In this context, it should be noted, that apart 586 M. Egelhaaf al. ■ Sensory Ecology and Neural Coding in Arthropods from adaptations in the structure of the eye or the male-specific neurons at the output level of the most peripheral processing stages in the nervous visual system have their receptive fields in the dor­ systems, we hardly know, apart from exceptions, sal part of the visual field. Moreover, in a re­ anything about the computational principles in stricted region of the dorsal frontal eye there is a both specialists and generalists. Hence, all state­ zone of particularly high acuity (Hardie et al., ments in this regard are quite preliminary and ba­ 1981). Interestingly, chasing males fixate on their sically reflect our ignorance. target with just this acute zone (Land and Collett, 1974; Wagner, 1986). Since the female is seen Generating Predictable Sensory Input by against the sky, its contrast is much larger than if Active Behaviour it would be seen against the ground. A high con­ trast of the target might be particularly important In the examples given above, the visual input from a signal detection point of view, if it is taken was predictable, because of the specific and well- into account that, depending on the distance be­ defined geometrical layout of the respective visual tween male and female fly, the retinal image of the environment. However, this is not the only possi­ female may only cover few ommatidia and thus bility how a highly predictive visual input comes stimulate only a small number of photoreceptors. about. If the animal is not conceived as viewing The problem of detecting the female may get even the outside world passively, but is actively moving worse, as due to the high velocities both males and in a specific way, additional information may be females often assume during chases, the target available (for review, see Land and Collett, 1997). may spend only a few milliseconds within the re­ Only two, quite different examples will be given, ceptive field of a given photoreceptor. The specific where active behaviour of the animal is required arrangement of photoreceptors in the acute eye to allow it to acquire relevant information of the zone can also be interpreted to enhance the sensi­ outside world and, thus, to be able to solve a par­ tivity of the male for detecting small objects, be­ ticular computational task. cause here not only 6 but 8 photoreceptors with largely overlapping receptive fields and the same Adaptive design of a visual pathway designed to spectral sensitivity converge on the same second- chase after rapidly moving targets order neurons. From all these specialisations it ap­ The first example shows that it might be neces­ pears that male flies may be only able to perform sary to behave in a specific way in order to solve their rapid and virtuosic chasing behaviour, as a biologically highly relevant problem, i.e. the long as they fly below the chased female in order problem of finding a mate. Flies show virtuosic to keep its contrast high and thus detectable areal pursuits in their mating behaviour in which against the background. males chase and catch females (Land and Collett, 1974; Wagner, 1986). While chasing, males fly Active vision in order to extract information about underneath their target and keep it fixated in the the spatial layout of the environment dorsal part of the visual field. Since these pursuit manoeuvres belong to the fastest visual guided be­ Various insect species have been shown to haviours that can be observed, there must be an acquire information about the spatial structure of accurate and rapid system for piloting the chasing their environment by active, more or less periodic male. Sex-specific specialisations have been found movements. For instance, locusts perform periodic in male flies at various levels of the visual pathway, sidewise movements of their body, thereby view­ ranging from the retina (Hardie et al., 1981; Har- ing the world from a range of vantage points. They die, 1986) to the output level of the visual system were shown to use the information gained by these (Hausen and Strausfeld, 1980; Strausfeld, 1991; active movements to estimate the distance to a Gilbert and Strausfeld, 1991). The male-specific target before they accurately leap upon it (Sobel, specialisations are discussed to be part of the con­ 1990; Collett and Paterson, 1991). Different kinds trol system mediating chasing behaviour. of active movements are frequently observed in Most conspicuously, all these specialisations various hymenopteran species, such as bees and concern the dorsal part of the visual field: The wasps. They perform systematic flight manoeuvres M. Egelhaaf et al. ■ Sensory Ecology and Neural Coding i Arthropods 587 when they leave their nest or a newly discovered thus their spatial resolution as well as their dynam­ foodplace. They do not depart by taking a straight ical properties (for review, see Kirschfeld, 1976; flight course. Rather they turn around to face the Land, 1981). Mainly two properties of light are im­ place they are leaving and fly backwards in a series portant in this regard: of continually increasing arcs (Zeil, 1993a,b; Zeil • Light is quantal in nature, i.e. there is a mini­ et al., 1997). There is good evidence that the ani­ mum unit of energy capable of being detected. mals acquire through these systematic flight man­ The quanta emanating from a light source are oeuvres information about the location of the goal randomly distributed in time. The stochastic na­ in its environment. They store this information in ture of light is particularly obvious at low light some way and use it to recognise their goal when levels, since the signal-to-noise ratio of signals they return. Rather than performing sidewise decreases with a decreasing amount of available movements as locusts do to estimate their distance light. This requires that all computations such as to a target, bees and wasps tend to pivot around movement detection that involve the compari­ the goal, thereby fixating on the goal with roughly son of brightness differences sensed by different the same retinal area. In this way the objects in photoreceptors depend on the absorption of at the surround move relative to the goal in a well- least as many photons as are necessary to obtain defined way. Simple geometrical analysis of this a statistically reliable estimate of the average situation reveals that pivoting generates distance brightness in the receptive field of the different information relative to the goal rather than rela­ receptors. At low light levels, reliable estimates tive to the animal as sidewise movements do (Col­ can be obtained, at least in principle, by either lett and Zeil, 1996). Whereas, in the latter case, the spatial pooling of the output signal of a number movements of the animal are purely translational, of photoreceptors thereby sacrificing spatial res­ they also contain a rotational component in the olution, or by smoothing out the membrane po­ former case. tential fluctuations elicited by the absorption of While it is fairly obvious that these animals in­ single photons by temporal averaging, thereby duce quite specific spatio-temporal properties of reducing the temporal resolution of the visual the time-dependent retinal images, it is not clear system. Indeed, in motion vision systems quite so far, in which way the visual system and, in par­ commonly light is pooled from a larger area of ticular, the mechanisms evaluating these motion the eye when it gets darker (Pick and Buchner, patterns operate. In any case, information about 1979; Schuling et al., 1989). Moreover, the time various spatial aspects of the visual environment constants of photoreceptors tend to get larger of an animal appears to be acquired with relative with decreasing brightness, allowing for tempo­ ease, if an appropriate strategy of moving actively rally smoothing out the consequences of the is adopted. stochastic nature of light (Dubs, 1981; Howard et al., 1984; Kuster and French, 1985). These Constraints Imposed on Any Adaptation by changes in the spatio-temporal properties of Physics and by the Neuronal Hardware photoreceptors can be regarded as an adapta­ So far, we discussed examples of structural and tion to the prevailing conditions in a particular behavioural specialisations which might be re­ visual environment. Also in the above-discussed garded as adaptations to particular ecological chasing system of male flies, pooling of the out­ niches. It is important to note in this context that put of an increased number of photoreceptors is most of these adaptations are only required be­ presumably employed as a strategy to increase cause there are principal constraints set by the the sensitivity of the system in the retinal region physical nature of light as well as by the available which is involved in chasing. Since, in contrast to neuronal hardware. Some examples of such con­ the other eye regions where each ommatidium straints will be given here. houses photoreceptors with different spectral sensitivity, all photoreceptors in the acute zone Size limits o f eyes due to the physical nature of light of male flies have the same spectral sensitivity. The physical nature of light imposes constraints The adaptation of males to spot females effi­ with respect to both the minimal size of eyes and ciently has to be paid for: males sacrifice colour 588 M. Egelhaaf al. ■ Sensory Ecology and Neural Coding in Arthropods

vision in this part of the retina in order to con­ different ways, either by graded changes in their centrate all its photoreceptors on the biolo­ membrane potential or by sequences of action po­ gically important task of chasing potential mates tentials. Photoreceptors and their postsynaptic ele­ (Hardie, 1986). ments basically transmit information by graded • Light emanates from a light source as a wave. membrane potential changes. In neurons that re­ Waves show interference phenomena part of spond mainly with graded changes in their mem­ which are relevant with respect to eye design. brane potential, information about a stimulus This is particularly true for diffraction which oc­ might be signalled at any instant of time. In con­ curs at apertures, such as the pupils of eyes or trast, in spiking neurons no information is sig­ the boundaries of ommatidial lenses in the case nalled between the spikes. Here the information of compound eyes. Light passing through one resides only in the number of spikes per time in­ part of an aperture interferes with that passing terval, the timing of individual spikes relative to a through another part, resulting in an interfer­ stimulus or the temporal pattern of spikes (Perkel ence pattern which tends to degrade the quality and Bullock, 1968; Rieke et al., 1997). Since there of the retinal image. Diffraction is one reason is an upper limit for the rate at which spikes can why eyes cannot get arbitrarily small. Since the be generated, the bandwidth of spiking neurons is minimal diameter of photoreceptors is limited, principally limited. Thus, it might be expected that, a minimum area of retina is needed to resolve a for instance, it may take longer for a spiking neu­ given number of points in space or, in other ron to signal changes in the stimulus conditions words, a better spatial resolution requires a than for a neuron responding with graded changes larger eye. The above mentioned acute zones of in membrane potential. Interestingly, this expecta­ increased spatial resolution found in certain eye tion is not met by the experimental findings: A regions of animals living in a flat world or in spiking neuron and a neuron conveying informa­ male flies are only required because of these tion with graded membrane potential changes at physical constraints. If there were no physical the same level of integration in the fly’s motion limitations with respect to the size of photore­ pathway do perform quite similarly in coding the ceptors and aperture, there would be no reason, onset of a motion stimulus or in representing the why spatial acuity should not be very high for time course of pattern velocity (Warzecha et al., the whole retina. However, because apertures 1993; Warzecha, 1994; Haag and Borst, 1997). and, thus, ommatidial lenses need to have a min­ Only on a very short time scale below 10 ms does imum size, an eye with a given surface can house the neuron with graded potential changes perform only a limited number of ommatidia. If the area better than the spiking one (Warzecha et al., 1993; of the eye and the field of view is given, the Warzecha, 1994). spatial resolution can be only increased in parts The main difference why spiking neurons and of the eye by decreasing the interommatidial an­ neurons with graded membrane potentials do not gle. However, this measure, inevitably leads to perform as differently as one might expect, is likely a decrease in spatial resolution in other eye re­ to be neuronal noise. Both the membrane potential gions. Consequently, any specialisation has to be in cells with graded potentials as well as the inter­ paid for. Nonetheless, if the sensitivity distribu­ spike interval in spiking neurons fluctuate continu­ tion is adapted to the visual habitat of the ani­ ally even during constant stimulation. Moreover, mal, the overall performance of the system can when the same stimulus is presented repeatedly to be optimised in this way. a neuron, the responses may vary quite a lot. It is quite common that the variance of neuronal re­ sponses is almost as large as the average response Limitations of the accuracy of neural coding amplitude (Tolhurst et al., 1981; Vogels et al., 1989; There is another constraint which limits the time Miller et al., 1991; Britten et al., 1993). Neuronal scale on which information can be processed and noise is, thus, a major constraint which limits the transmitted in nervous systems. This constraint performance of neuronal computations. pertains to the way nervous systems encode infor­ The constraints imposed by the limited channel mation. They do this in either of two principally capacity of spiking neurons as well as by neuronal M. Egelhaaf et al. • Sensory Ecology and Neural Coding i , Arthropods 589 noise are particularly obvious in the time domain: changes and, thus, a much more precise time-lock­ As a consequence of stochastic signal fluctuations, ing of spikes to stimuli are found, for instance, in it is not clear when just looking at, for instance, neurons of the fish electrosensory system involved a spike train, whether changes in the interspike in object detection (Kawasaki, 1993), in the system interval are induced by some stimulus or are just mediating acoustic sound localisation of verte­ due to a noise source. This raises the question for brates (Carr, 1993) or the mechanosensory system the time scale on which stimulus-related informa­ of flies involved in coupling the activity of flight tion can be conveyed by neurons. In the following motor neurons to the temporal phase of wing beat we shall see that this time scale depends on three (Fayyazuddin and Dickinson, 1996). factors (i) the dynamics of the stimuli, (ii) the way Though in the latter systems very precise timing the stimuli are processed, and (iii) the dynamical of spikes to the sensory input is necessary for solv­ properties of stochastic signal fluctuations. Owing ing the computational tasks of the respective sys­ to a lack of consistent data, there is currently much tems (i.e. detecting an object, localising a sound controversy about the time scale on which neurons source or coupling the activity of flight motoneu­ process and transmit information (Shadlen and rons to the temporal phase of the wingbeat), there Newsome, 1994; Shadlen and Newsome, 1995; might be no computational requirements for such Softky, 1995; Rieke et al., 1997). The constraints precise time-locking of spikes to visual motion limiting the reliability of neural coding are known stimuli. Biological motion vision systems are particularly well for the motion pathway of the fly. either required to sense self-motion of the animal Therefore, we concentrate here on this system. or the motion of objects. Because of inertia and Most spikes of motion-sensitive neurons in the friction impeding rapid velocity changes of objects, fly visual system occur time-locked to visual mo­ virtually no behaviourally relevant motion stimuli tion with a precision in the range of only several change their direction at temporal frequencies tens of milliseconds, even when the direction of which would demand for their resolution a tempo­ motion changes rapidly (Warzecha et al., 1998). ral precision of spiking in the millisecond range. The relative imprecision in the timing of spikes is Whether this notion is true needs to be elucidated not the consequence of a particular imprecise in experiments where the dynamics of the natural spike generation mechanism in the motion sensi­ motion input of animals is analysed. There are al­ tive neurons. If the membrane potential changes most no studies where this has been done so far. of a neuron induced by its synaptic input are suffi­ On exception is optomotor position stabilisation ciently transient, spikes time-lock to these changes of the hummingbird hawk moth hovering in front with a temporal precision in the millisecond range. of flowers (see above). It has been shown that However, since the computations leading to a di- flowers, on which the hawk moth is feeding, may rectionally selective response to motion inevitably wiggle in the wind at frequencies between about 1 require time constants in the range of some tens and 2 Hz (Farina et al., 1994). In the context of to hundreds of milliseconds (for review, see Egel­ male chasing behaviour, up to ten turns per second haaf and Borst, 1993b), the stimulus-induced have been observed in certain fly species (Wagner, membrane potential fluctuations in motion sensi­ 1986; Land, 1993). Hence, neuronal representa­ tive neurons do not follow high-frequency velocity tions of even the fastest changes in the direction changes with a high gain. Consequently, in the mo­ of self-motion that may occur in nature do not re­ tion vision system of the fly the exact timing of quire a very precise timing of spikes. In the most action potentials is determined in the motion context of optomotor course stabilisation in flies, vision system by stochastic membrane potential first attempts have been made to analyse the neu­ fluctuations (Warzecha et al., 1998). Hence, mainly ronal coding of motion stimuli that were generated changes in spike activity on a coarser time scale in a flight simulator by the animal’s own actions provide in this system reliable information about and reactions. The resulting velocity fluctuations what is going on in the outside world. Different occuring during course stabilisation had most computational needs are imposed on neurons in­ power at frequencies below 5 Hz (Warzecha and volved in other tasks. Accordingly, much more Egelhaaf, 1996). Accordingly, on the basis of neu­ rapid stimulus-induced membrane potential ronal responses, these behaviourally generated 590 M. Egelhaaf et al. • Sensory Ecology and Neural Coding in Arthropods motion stimuli can be decoded most reliably at a them, we need to take at least the following three time scale of some tens of milliseconds, i.e. at a aspects into account: time scale where the timing of individual spikes • We need to know the natural operating condi­ does not matter (Warzecha and Egelhaaf, 1997). tions of the system. Hence, it might be not disadvantageous for an ani­ • We need to know the computational task which mal, that its motion pathway does not represent the system has to solve. stimuli with a precision in the millisecond range. • We need to know the limitations set by physics Obviously, motion information processing is just as well by the neuronal hardware that is available one computational task of the visual system the to solve a particular computational problem. underlying principles of which we understand to As we have seen, many of the structural und some extent. Other constraints are imposed on functional adaptations appear to be quite sophisti­ other tasks. In any case, if we want to understand cated, although they are simple in their basic prin­ specific adaptations of animals, invertebrates and ciples. Nonetheless, animals, and even arthropods, vertebrates, to their particular ecological niches, it often easily outperform any man-made devices in is very important to be aware of the constraints particular tasks, just to remind you of the chasing imposed not only by this niche but also of the neu­ behaviour in flies. The fascinating thing about all ronal machinery through which the task has to this is, that they do it often with brains as tiny as be solved. the head of a pin. This might be only possible, be­ cause neuronal circuits are subject to much longer testing than is possible for any technical system. Conclusion Shouldn’t some tens to hundreds of million years In order to fully understand the organisational be enough to lead to sophisticated and, at the principles of sensory systems and the neuronal ma­ same time, parsimonious solutions to even daunt­ chinery that exploits the information provided by ing tasks?

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