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 0939-5075/98/0700-0582 $ 06.00 © 1998 Verlag der Zeitschrift für Naturforschung, Tübingen • www.znaturforsch.com. D 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.