Integrative and Comparative Biology Advance Access originally published online on September 7, 2006
Integrative and Comparative Biology 2006 46(6):871-879; doi:10.1093/icb/icl037
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Advances in the neural bases of orientation and navigation
* Department of Biology, 156 Lewis Science Center, University of Central Arkansas Conway, AR 72035, USA
620 University Road, Friday Harbor Labs, Friday Harbor, WA 98250, USA
Correspondence: 1E-mail: tritoniadiomedea{at}mac.com
Correspondence: 2E-mail: crabboy{at}u.washington.edu
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Synopsis |
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The ability to locomote in one direction (oriented movement), and the ability to navigate toward a distant goal are related behaviors that are phylogenetically widespread. Orientation behaviors include finding the source of an odor or acoustic signal, using a sun-compass for guidance, and moving relative to fluid-dynamic cues. Such abilities might require little more than directionally selective sensors coupled to a turning mechanism. This type of behavior, therefore, can be implemented by relatively simple circuits. In contrast, navigation involves both the ability to detect direction, as well as a map-sense that provides position. Navigation is less common and arguably requires greater brain computation than does simple orientation, but may be present in arthropods as well as in vertebrates. Great progress has been made in exploring the biophysical and sensory bases for these behaviors, and in recent years the locations and the identity of the cellular transducers of the sensory stimuli (for example, geomagnetic fields) have been narrowed in some taxa. Similarly, neurons within the central nervous that most likely function in higher order computational processes have been identified. For example, direction-selective and position-responsive brain cells have been located in the brains of mammals and birds, and these cells might contribute to a cognitive map that can enable navigation. One model organism in which orientation and navigation has been extensively studied is the sea slug Tritonia diomedea. This animal orients its crawling to chemical, hydrodynamic, and geomagnetic cues. The brain of Tritonia has
7000 relatively large neurons that facilitate circuit analysis. Recent work has characterized both peripheral and central neural correlates of orientation signals, as well as the control of thrust and turning, and studies of their field behavior have suggested how these disparate orientation systems may be integrated. These findings provide the basis for future studies to determine how the nervous system combines multiple sensory cues into a complex hierarchy of signals that can direct motor output and therefore guide navigational tasks. |
Introduction |
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SynopsisIntroductionKinesisTaxisHomingMigrationUse of multiple sensory...Behavioral and neural components...TRITONIA DIOMEDEA AS A...REFERENCES |
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Both navigation and orientation comprise a diverse set of behaviors exhibited by animals possessing a wide spectrum of neural complexity. These diverse behaviors are not likely to be derived from a common ancestral ability, but have probably evolved multiple times as a result of integration of sensory and locomotory systems. Although these neural circuits have evolved in the context of various sensory and motor systems, we may expect them to be organized in a common manner, because they address similar navigational tasks. The neural circuits responsible for oriented goal-seeking and navigation have been identified in only a few species (but for oriented escape turning see Levi and Camhi 2000
; Jing and Gillette 2003), so this expectation has not been tested rigorously.
Because our expectation is that more complex navigational tasks evolve from combining less complex-oriented behaviors, we must define different types of orientation and navigation. Orientation and navigation can be divided into several categories (Fraenkel and Gunn 1961), and here we use a hierarchy organized in a manner consistent with the minimal degree of neural complexity thought to be necessary to accomplish each type of task. It is important, however, to realize that each behavior can serve as a stand-alone system, or might be coupled with 1 or more other types of behavior to perform a given navigational task.
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Kinesis |
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SynopsisIntroductionKinesisTaxisHomingMigrationUse of multiple sensory...Behavioral and neural components...TRITONIA DIOMEDEA AS A...REFERENCES |
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Kinesis involves varying the rate of locomotion and frequency of turning, resulting in movement toward a signal, even though the direction of the signal is unknown and the body is not always oriented with respect to the signal source. An example is the movement of a bacterium up a chemical gradient. The single cell cannot detect the direction of the chemical gradient, but can swim longer when the chemical intensity is low, and (randomly) turn more when the intensity is high. At minimum, all that is required for this behavior is an ability to discriminate absolute signal intensities, and to vary the speed of locomotion and/or frequency of turning accordingly. This could be accomplished with a minimal amount of neural computation, such as a single sensory element connected to a single motor-control element for locomotion and/or turning. This kinesis could be further enhanced by the addition of a "memory" of the previously detected signal intensity, so that the organism could better distinguish changes in relative intensity, without having to preprogram which intensity levels would trigger high or low speeds of locomotion.
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Taxis |
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SynopsisIntroductionKinesisTaxisHomingMigrationUse of multiple sensory...Behavioral and neural components...TRITONIA DIOMEDEA AS A...REFERENCES |
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Taxis involves movement while orienting the body to a directional cue. This behavior could involve a single receptor (detecting relative signal intensity), if the body can bend back and forth enough to detect a change in the directional cue (klinotaxis); this would require a sequential comparator and a form of short-term memory (the minimum neural substrates for this type of orientation). Tropotaxis involves paired receptors that are simultaneously compared to maintain a constant relative level of activity. This allows the animal to maintain a constant body-axis orientation while moving with respect to a directional cue. This cue could be a signal source that is in principle attainable (for example, chemical source, bioluminescence), or a directional field such as the geomagnetic field, laminar flow, or sunlight. The use of paired receptors would at minimum require a means of comparing their relative activities, and a way of relaying their relative activities to the motor system to produce an oriented response. The presence of the stimulus may also trigger or stimulate locomotion.
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Homing |
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SynopsisIntroductionKinesisTaxisHomingMigrationUse of multiple sensory...Behavioral and neural components...TRITONIA DIOMEDEA AS A...REFERENCES |
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Homing behavior involves a round-trip, a fixed goal, and a complex series of behaviors, moving from mere orientation to navigational (movement towards a known destination) behavior. Path integration might be employed, in which the animal measures the distance and direction traveled on the outbound trip, and can thus "integrate" the multiple vectors and derive the distance and direction of home, allowing a direct pathway (a.k.a. dead reckoning). This technique requires a directional sense ("compass"), as well as a measure of distance traveled ("odometer") and has been studied mostly in insects (Labhart and Meyer 2002
). The sensory basis of the directional sense is a time-compensated celestial compass, and the sensory basis of the odometer can be locomotion-induced optic flow, or can be measured by counting steps when walking. This method is susceptible to cumulative errors in measuring distances, so it is most accurate over relatively short distances. Animals could also use rotation sensors to integrate directional changes over time, instead of an objective compass, but this could also introduce cumulative errors.
In addition to path integration, homing often involves some form of memory of the local environment. Desert ants use retinal matching when returning to the nest after a foraging bout (Wehner and others 1996). The ant maintains a "snapshot" memory of the local environment and moves in the direction that will optimize the match between the image on the retina and the memorized snapshot. This requires a long-term memory storage, short-term memory storage, and a mechanism for comparing the current retinal image with the stored image.
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Migration |
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SynopsisIntroductionKinesisTaxisHomingMigrationUse of multiple sensory...Behavioral and neural components...TRITONIA DIOMEDEA AS A...REFERENCES |
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Although small-scale homing can use both internal reference cues (idiothetic) or external reference cues (allothetic), longer distance (for example, global) homing and migratory behaviors require cues that are allothetic in order to avoid the effects of cumulative errors. The most cognitively simple type of migratory behavioral requires only an external reference source (compass) and a way to measure either distance or time. In essence the nervous system would use the compass to maintain movement in a given direction for a predetermined time or distance (for example, inexperienced migrating Starlings, Perdeck 1958
). In contrast to this relatively simple type of migration, other animals are thought to perform "map and compass" orientation. This highly complex behavior requires the use of a compass sense as well as a cognitive representation of space that allows the animal to determine its current position relative to a goal location. The animal uses the map to determine the appropriate heading and the compass to maintain this heading while traveling.
At present, little is known about the neural substrates that provide an animal with a map sense. To date, much research into the neurobiology of the map sense and indeed migratory behavior has been conducted on mammals and birds (McNaughton and others 1996; Bingman and others 2005; Mizumori and others 2005; Wiltschko and Wiltschko 2005). These animals possess hundreds of millions of tiny neurons, making it difficult to investigate and understand the neural circuitry and cellular mechanisms underlying the computation of navigational parameters. This type of navigation may also be present in invertebrates (for example, spiny lobsters) with fewer and larger neurons (Boles and Lohmann 2003), and thus might facilitate a cellular analysis of the neural circuits underlying navigation.
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Use of multiple sensory cues during orientation and navigation behavior |
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In many cases, an oriented behavior is not directed by a single directional cue. In these cases, the different cues could be concordant or discordant. When concordant, the direction-detecting mechanisms of each system could be used to mutually enhance one another, or they may be used serially, with some cues being used as the distance to the goal is reduced, or as one cue is lost. Such may be the case in animals like pigeons that appear to employ multiple cues during their homing behaviors (Walcott 1996
), or desert-forager ants that use serial cues when returning to the nest (Wehner and others 1996). When cues are discordant, the animal might employ circuits that balance the effects of the 2 sensory cues upon the motor system, or it might possess circuits that can essentially "decide" which cues will affect direction of locomotion, depending on the sensory or behavioral context. In either concordant or discordant cases, as a navigational strategy is developed more neural capacity is likely involved. There must be circuit components that compare cues, time behaviors, or suppress one type of cue while focusing attention on a different cue. |
Behavioral and neural components of compass orientation and navigation |
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How are individual-oriented behaviors combined to produce more complex behavior strategies and have we identified any of the neural substrates controlling these behaviors? Several significant advances have been made recently in elucidating the mechanisms of "compass sense" in both the geomagnetic and celestial compass. The beach sandhopper (amphipod) generally orients its hops to the land–sea axis, which keeps it in the ideal intertidal zone. Although the animal has been shown to use a sun-compass, the sun's azimuth is ambiguous at noon near the equator. They also orient to the geomagnetic field, and engage in full body "scans," rotating their body clockwise and counterclockwise before settling on one direction, then hopping (Ugolini 2006
). Scanning behavior increases when the horizontal component of the field is canceled. This scanning behavior resembles the head-scanning behavior observed in migratory birds, and Ugolini suggests that scanning may be an example of klinotactic orientation to the geomagnetic field expected when a single, effective field detector is used to detect the magnetic field vector by moving the body back and forth.
Mouritsen, Feenders and colleagues (2004) observed that caged migratory garden warblers performed head scanning behavior, which may be used by the birds to detect the reference compass direction of the geomagnetic field. The authors argue that the primary magnetic compass detector is located in the head region, and that the magnetic compass sense of birds relies on relative measures to detect the magnetic reference compass direction. It is difficult to rule out the possibility that increased rate of head scans are not an arousal response to the canceled magnetic field unrelated to detecting geomagnetic direction. Mouritsen, Janssen-Bienhold and colleagues (2004) suggested that cryptochromes in displaced ganglion cells in the eye may mediate this ability to orient to the geomagnetic field vector by modulating their visual sense. Mouritsen and colleagues (2005) identified an area in the brains of migratory songbirds that are active during night-vision, which is when they propose the birds calibrate their magnetic compass with celestial cues to compensate for the magnetic field anomalies such as declination.
A neural representation of space and direction is found in the "place" and "head direction" hippocampal cells of rats (McNaughton and others 1996). The "head direction" cells are calibrated to different visual environments, and do not provide an invariant sense of direction like a compass. The "place" cells are re-mapped in different sensory contexts, so they do not represent just one place in the world. Recent work (Hafting and others 2005) has identified "grid" cells in the entorhinal cortex afferent to the hippocampus that have place fields consisting of multiple regularly spaced points laid out on a repeating triangular grid. The fields of these cells persist in different environments, even in the dark. The activity of multiple grid cells could be used to more accurately predict position by overlaying their respective grids. The authors suggest that these neurons might form a virtual grid that can be overlaid over any area of space much as human maps use latitude and longitude. Such a system could contribute to both path integration and map-based navigation. The role of the hippocampus in sun-compass orientation has also been supported by work on pigeons (Gagliardo and others 2005). These authors showed that both the left and right hippocampus participate in spatial learning for a food reward.
Many species have been shown to have a "map sense" that allows them to perform so-called "true navigation" (for review see Johnsen and Lohmann 2005). This requires that the animal know its position in the world, even if it received no cues in transit (much like a human could use a GPS receiver to ascertain position). "True navigation" is possible when the animal not only know its present position, but also possesses a knowledge of the destination of its future position, and can relate those 2 positions to one another using a "cognitive map" of space.
A map sense has been demonstrated recently in both sea turtles (Lohmann and others 2004) and spiny lobsters (Boles and Lohmann 2003). In each case, the animals were captured at one location, moved in a way to prevent the detection of directional cues en route, then exposed to magnetic fields of an intensity and inclination that is characteristic of locations displaced several hundred kilometers away. The animals each attempted to move towards the original capture site ("home") as though they derived their present location from the sensed properties of the imposed magnetic field (Fig. 1). Where these locations are stored in the nervous system is not known for either species, but the spiny lobster has a relatively simpler central nervous system with larger cells that would be amenable to cellular analysis.
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TRITONIA DIOMEDEA AS A MODEL SYSTEM FOR NEURAL CONTROL OF ORIENTATION |
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One impediment to investigating the neurobiology of complex navigational tasks at the cellular and subcellular level in finding a suitable experimental system. We have been using the nudibranch gastropod Tritonia diomedea as a model in which to examine the neural mechanisms underlying orientation behavior. This slug resides in subtidal forests of its prey, sessile soft corals, and can orient its crawling locomotion to water flow direction and the geomagnetic field (Lohmann and Willows 1987
; Murray and Willows 1996; Willows 1999; Murray and others 2006; Wyeth and Willows 2006b). The propensity to orient towards or away from the direction of water flow is influenced by the presence of attractive odorants (released from prey and conspecifics) and repulsive odorants (released from potential predators such as sea stars) (Wyeth and others 2006). The locomotion of the blind Tritonia is guided by these cues, as well as by touch, in an environment that is relatively flat and otherwise featureless. As the slug possesses only 7000 neurons in its brain, and brain cells can be 50–800 µm wide, it has served as an excellent model system for the neural bases of simple behaviors.
This animal does not perform large-scale homing or migration, but does use a number of environmental cues for navigation. Further, the cues the animal uses vary due to behavioral state (Wyeth and others 2006) and the local environment (S. Cain, unpublished data). Wyeth (2004) proposed a strategy by which Tritonia can locate food and mates in shifting water flow using chemically gated rheotaxis, and a magnetic compass sense (Fig. 2). Since water flow direction changes significantly on a time scale faster than a Tritonia can close on its target, the slug would benefit from crawling upstream when it smells an attractive odor, and if the scent was lost, continue to crawl across the water flow direction on a constant magnetic bearing until the original source of the odor is contacted. This "orienteering hypothesis" is supported by some observations of slugs in nature, but has yet to be tested explicitly. Support for this hypothesis would show an additional function for the magnetic sense, and suggest that the chemosensory, water flow orientation, and magnetic orientations systems must be tightly coordinated.
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While crawling, Tritonia orients its body in response to several stimuli found in its environment, but in none of these cases are the mechanisms known whereby sensory information causes turning with respect to the stimuli. In contrast, considerable progress has been made recently in the investigation of the neural control of locomotion (Willows and others 1997; Popescu and Frost 2002
; Wang and others 2003; Redondo and Murray 2005; Cain and others 2006). Audesirk (1978) showed that Tritonia is propelled forward via the beating of cilia on the underside of the foot. These pedal cilia are in part controlled by an identified pair of ciliary motor neurons (located in the pedal ganglia) called left and right pedal neurons 21 (Pd21). Pd21 contains serotonin (Audesirk and others 1979; Fickbohm and others 2001), and serotonergic terminals could synapse directly on ciliated cells of the foot (S. Cain, unpublished data). This pair of neurons fire action potentials in synchrony due to electrical synaptic coupling and common synaptic input, and the rate of firing is directly related to the rate of movement caused by cilia (Audesirk 1978). If the bilateral pair of Pd21 neurons fire synchronously while crawling, as inferred from immobilized semi-intact preparations, then they cannot directly cause turning. Audesirk (1978) suggested that Tritonia turn by lifting a portion of the foot off the substratum, making ciliary beating in that area ineffective, thus turning the animal toward the lifted side of the foot. Our preliminary evidence (Fig. 3) supports this hypothesis.
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Two more pairs of pedal neurons have recently been identified as ciliary motor neurons—Pd5 and Pd6 (Willows and others 1997
; Popescu and Willows 1999; Wang and others 2003; Cain and others 2006). It is unknown whether these pairs of neurons fire in synchrony during crawling, but evidence from magnetic stimulation trials in semi-intact preparations indicate that, although they fire bursts at the same time and receive common synaptic input, the action potentials are not perfectly synchronized (Lohmann and others 1991; Popescu and Willows 1999; Wang and others 2003; Cain and others 2006). Thus, Tritonia could turn in response to magnetic fields due to asymmetric activity of pedal cilia, rather than by lifting the pedal cilia off the substrate. If Pd5 and Pd6 tend to burst together at similar rates during crawling, then turning due to hypothesized asymmetries in the activity of pedal cilia (Wang and others 2003; Cain and others 2006) is likely to take a longer time than the 1 min duration turns observed in response to water flow. Furthermore, Lohmann and Willows (1987) observed that Tritonia make turns toward a particular magnetic direction in a Y-maze, and these turns take less than a few minutes to accomplish. Thus, even turning in response to magnetic stimuli may require muscle contractions.
Pedal neurons 3 (Pd3) have been proposed to control turning by bending the animal in a C-shape (Willows and others 1973), or by lifting of the foot off the substrate (Murray and others 1992). Turning may result from the lifting of the ciliated foot epithelium off the substrate, due to contractions of the muscular foot. Such contractions of the foot are observed during turning in response to water flow (Fig. 3). Contractions of the same part of the foot are elicited when stimulating the presumptive motor neuron Pedal 3 (Pd3). It is unknown whether Pd3 directly innervates muscles cells, or controls contraction via a peripheral nerve net, but it is an effective "flexion neuron." Preliminary experiments causing inactivation of Pd3 leads to reduction in turning (Fig. 4).
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One model is that 1 pair of neurons controls the speed of locomotion, and another pair of neurons controls the direction of turning. This model is based on previous research and on the preliminary findings described above. If true, this will help form a basis for studying the mechanisms of sensorimotor integration in other orientation behaviors such as chemotaxis and magnetic orientation. If Pd3 is the only controller of direction in navigation, then it should be a key part of the navigational circuitry underlying orientation to flow, magnetic orientation, and chemotaxis.
Our knowledge of the motor system and the large cells of the Tritonia nervous system provides us a model that might allow us to determine how multiple sensory cues are integrated in the nervous system to perform complex navigational tasks. For example, Tritonia show variation in attention to various environmental cues, depending on its behavioral state (Wyeth and Willows 2006a). How does the nervous system switch attention from one cue to another? In addition, during mate- and prey-finding behavior, this slug uses multiple cues sequentially to find its goal. What are the neural processes that determine which cue to use at different times during the journey? Because we know the brain cells involved in motor commands during locomotion, we have the opportunity to investigate these mechanisms using both isolated brain preparations and individual cells, as well as in intact and semi-intact animals. We expect that the mechanisms discerned in Tritonia will point the way to neural investigations of more complex navigational tasks (that is, map and compass navigation) in other animals.
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Acknowledgements |
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We acknowledge the contributions made by fruitful discussions with multiple participants in the Recent Advances symposium, especially with Dr Russell Wyeth. The manuscript was greatly improved in response to comments from 2 anonymous reviewers. We also thank Dr Rich Satterlie for organizing the symposium, the Division of Neurobiology for sponsoring the symposium, and NSF for their financial support. Ms Elizabeth Murray assisted with editing. Dr Murray's and Ms Estepp's research was supported by the Arkansas Science and Technology Authority, and by the University of Central Arkansas Research Council. Dr Cain's research was supported by NSF Grant #IOB-0416328. We also thank Dr Dennis Willows and the Friday Harbor Laboratories for excellent facilities and support.
Conflict of interest: None declared.
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Footnotes |
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From the symposium "Recent Developments in Neurobiology" presented at the annual meeting of the Society for Integrative and Comparative Biology, January 4–8, 2006, at Orlando, Florida.
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