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A model for the neuronal substrate of dead reckoning and memory in arthropods: a comparative computational and behavioral study

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Abstract

Returning to the point of departure after exploring the environment is a key capability for most animals. In the absence of landmarks, this task will be solved by integrating direction and distance traveled over time. This is referred to as path integration or dead reckoning. An important question is how the nervous systems of navigating animals such as the 1 mm3 brain of ants can integrate local information in order to make global decision. In this article we propose a neurobiologically plausible system of storing and retrieving direction and distance information. The path memory of our model builds on the well established concept of population codes, moreover our system does not rely on trigonometric functions or other complex non-linear operations such as multiplication, but only uses biologically plausible operations such as integration and thresholding. We test our model in two paradigms; in the first paradigm the system receives input from a simulated compass, in the second paradigm, the model is tested against behavioral data recorded from 17 ants. We were able to show that our path memory system was able to reliably encode and compute the angle of the vector pointing to the start location, and that the system stores the total length of the trajectory in a dependable way. From the structure and behavior of our model, we derive testable predictions both at the level of observable behavior as well as on the anatomy and physiology of its underlying neuronal substrate.

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References

  • Angstadt J (1999) Persistent inward currents in cultured Retzius cells of the medicinal leech. J Comp Physiol [A] 184:49–61

    Article  CAS  Google Scholar 

  • Bernardet U (2007) iqr–large-scale neural systems simulator http://iqr.sourceforge.net

  • Bernardet U, Blanchard M, Verschure P (2002) Iqr: a distributed system for real-time real-world neuronal simulation. Neurocomputing 44-46:1043–1048

    Article  Google Scholar 

  • Darwin C (1873) Origin of certain instincts. Nature 7:417–418

    Article  Google Scholar 

  • Egorov A, Hamam B, Fransén E, Hasselmo M, Alonso A (2002) Graded persistent activity in entorhinal cortex neurons. Nature 420:173–178

    Article  CAS  PubMed  Google Scholar 

  • Elias S, Grossberg S (1975) Pattern formation, contrast control and oscillations in the short term memory of shunting on-center off-surround networks. Biol Cybern (20):69–98

    Article  Google Scholar 

  • Esch H, Burns J (1996) Distance estimation by foraging honeybees. J Exp Biol 199:155–162

    PubMed  Google Scholar 

  • Etienne A, Jeffery K (2004) Path integration in mammals. Hippocampus 14:180–192

    Article  PubMed  Google Scholar 

  • Feldman J, Ballard D (1982) Connectionist models and their properties. Cognit Sci 6:205–254

    Article  Google Scholar 

  • Fukushima K (1980) Neocognitron: a self organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol Cybern 36(4):193–202. 0340-1200 (Print) Journal Article

    Google Scholar 

  • Gabbiani F, Krapp H, Koch C, Laurent G (2002) Multiplicative computation in a visual neuron sensitive to looming. Nature 420:320–324

    Article  CAS  PubMed  Google Scholar 

  • Georgopoulos A (1994) New concepts in generation of movement. Neuron 13:257–268

    Article  CAS  PubMed  Google Scholar 

  • Georgopoulos A, Schwartz A, Kettner R (1986) Neuronal population coding of movement direction. Science 233:1416–1419

    Article  CAS  PubMed  Google Scholar 

  • Hartmann G, Wehner R (1995) The ant’s path integration system: a neural architecture. Biol Cybern 73:483–497

    Google Scholar 

  • Hertz J, Krogh A, Palmer R (1991) Introduction to the theory of neural computation. Addison-Wesley, Redwood City

    Google Scholar 

  • Homberg U, Würden S (1997) Movement-sensitive, polarization-sensitive, and light-sensitive neurons of the medulla and accessory medulla of the locust, Schistocerca gregaria. J Comp Neurol 386:329–346

    Article  CAS  PubMed  Google Scholar 

  • Hrncir M, Jarau S, Zucchi R, Barth F (2003) A stingless bee (Melipona seminigra) uses optic flow to estimate flight distances. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 189:761–768

    Article  CAS  PubMed  Google Scholar 

  • Jacobs G, Theunissen F (1996) Functional organization of a neural map in the cricket cercal sensory system. J Neurosci 16:769–784

    CAS  PubMed  Google Scholar 

  • Knierim J, Kudrimoti H, McNaughton B (1995) Place cells, head direction cells, and the learning of landmark stability. J Neurosci 15:1648–1659

    CAS  PubMed  Google Scholar 

  • Labhart T (1988) Polarization-opponent interneurones in the insect visual system. Nature 331:435–437

    Article  Google Scholar 

  • Labhart T, Meyer EP, Schenker L (1992) Specialized ommatidia for polarization vision in the compound eye of cockchafers, Melolontha melolontha (coleoptera, scarabaeidae). Cell Tissue Res 268 (3), 419–429

    Article  CAS  PubMed  Google Scholar 

  • Lambrinos D (2003) Navigation in desert ants: the robotic solution. Robotica 21:407–426

    Article  Google Scholar 

  • Lambrinos D, Möller R, Labhart T, Pfeifer R, Wehner R (2000) A mobile robot employing insect strategies for navigation. Rob Auton Syst 30:39–64

    Article  Google Scholar 

  • Lewis J, Kristan W (1998) A neuronal network for computing population vectors in the leech. Nature 391:76–79

    Article  CAS  PubMed  Google Scholar 

  • Liu G, Seiler H, Wen A, Zars T, Ito K, Wolf R, Heisenberg M, Liu L (2006) Distinct memory traces for two visual features in the Drosophila brain. Nature 439:551–556

    Article  CAS  PubMed  Google Scholar 

  • Loesel R, Homberg U (2001) Anatomy and physiology of neurons with processes in the accessory medulla of the cockroach Leucophaea maderae. J Comp Neurol 439:193–207

    Article  CAS  PubMed  Google Scholar 

  • Major G, Tank D (2004) Persistent neural activity: prevalence and mechanisms. Curr Opin Neurobiol 14:675–684

    Article  CAS  PubMed  Google Scholar 

  • Marr D, Poggio T (1979) A computational theory of human stereo vision. Proc R Soc Lond B Biol Sci 204 (1156):301–328. 0080-4649 (Print) Journal Article

  • Menzel R, Greggers U, Smith A, Berger S, Brandt R, Brunke S, Bundrock G, Hülse S, Plümpe T, Schaupp F, Schüttler, E., Stach S, Stindt J, Stollhoff N, Watzl S (2005) Honey bees navigate according to a map-like spatial memory. Proc Natl Acad Sci U S A 102:3040–3045

    Article  CAS  PubMed  Google Scholar 

  • Mercer A, Kloppenburg P, Hildebrand J (2005) Plateau potentials in developing antennal-lobe neurons of the moth, Manduca sexta. J Neurophysiol 93:1949–1958

    Article  CAS  PubMed  Google Scholar 

  • Mittelstaedt ML, Mittelstaedt H (1980) Homing by path integration in a mammal. Naturwissenschaften 67:566–567

    Article  Google Scholar 

  • Möller R (2000) Insect visual homing strategies in a robot with analog processing. Biol Cybern 83:231–243

    Article  PubMed  Google Scholar 

  • Mudra R, Douglas R (2003) Self-correction mechanism for path integration in a modular navigation system on the basis of an egocentric spatial map. Neural Netw 16:1373–1388

    Article  PubMed  Google Scholar 

  • Pascual A, Préat T (2001) Localization of long-term memory within the Drosophila mushroom body. Science 294:1115–1117

    Article  CAS  PubMed  Google Scholar 

  • Ramirez J, Pearson K (1991) Octopamine induces bursting and plateau potentials in insect neurones. Brain Res 549:332–337

    Article  CAS  PubMed  Google Scholar 

  • Reinhard J, Srinivasan M, Zhang S (2006) Complex memories in honeybees: can there be more than two? J Comp Physiol A Neuroethol Sens Neural Behav Physiol 192:409–416

    Article  PubMed  Google Scholar 

  • Reppert S, Zhu H, White R (2004) Polarized light helps monarch butterflies navigate. Curr Biol 14:155–158

    Article  CAS  PubMed  Google Scholar 

  • Ronacher B, Gallizzi K, Wohlgemuth S, Wehner R (2000) Lateral optic flow does not influence distance estimation in the desert ant Cataglyphis fortis. J Exp Biol 203:1113–1121

    CAS  PubMed  Google Scholar 

  • Rossel S, Wehner R (1986) Polarized vision in bees. Nature 323:128–131

    Article  Google Scholar 

  • Salinas E, Abbott L (1994) Vector reconstruction from firing rates. J Comput Neurosci 1:89–107

    Article  CAS  PubMed  Google Scholar 

  • Si A, Srinivasan M, Zhang S (2003) Honeybee navigation: properties of the visually driven “odometer”. J Exp Biol 206:1265–1273

    Article  PubMed  Google Scholar 

  • Sommer S, Wehner R (2004) The ant’s estimation of distance travelled: experiments with desert ants, Cataglyphis fortis. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 190:1–6

    Article  CAS  PubMed  Google Scholar 

  • Spero D (2004) A review of outdoor robotics research. Tech. Rep. MECSE-17-2004, Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia. URL:http://www.citeseer.ist.psu.edu/spero04review.html

  • Srinivasan M, Zhang S, Altwein M, Tautz J (2000) Honeybee navigation: nature and calibration of the "odometer". Science 287: 851–853

    Article  CAS  PubMed  Google Scholar 

  • Stalleicken J, Mukhida M, Labhart T, Wehner R, Frost B, Mouritsen H (2005) Do monarch butterflies use polarized skylight for migratory orientation? J Exp Biol 208:2399–2408

    Article  PubMed  Google Scholar 

  • Taube J (2007) The head direction signal: origins and sensory-motor integration. Annu Rev Neurosci 30:181–207

    Article  CAS  PubMed  Google Scholar 

  • Tautz J, Zhang S, Spaethe J, Brockmann A, Si A, Srinivasan M (2004) Honeybee odometry: performance in varying natural terrain. PLoS Biol 2(7):E 211

    Google Scholar 

  • Verschure P, Voegtlin T, Douglas R (2003) Environmentally mediated synergy between perception and behaviour in mobile robots. Nature 425:620–624

    Article  CAS  PubMed  Google Scholar 

  • Vickerstaff R, Di Paolo E (2005) Evolving neural models of path integration. J Exp Biol 208:3349–3366

    Article  CAS  PubMed  Google Scholar 

  • von Frisch K (1993) The dance language and orientation of bees. Harvard University Press, Cambridge

    Google Scholar 

  • von Philipsborn A, Labhart T (1990) A behavioural study of polarization vision in the fly, Musca domestica. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 167(6):737–743

    Google Scholar 

  • Wallace D, Hines D, Pellis S, Whishaw I (2002) Vestibular information is required for dead reckoning in the rat. J Neurosci 22:10009–10017

    CAS  PubMed  Google Scholar 

  • Wehner R (1997) Orientation and communication in arthropodes, the ant’s celestial compass system: spectral and polarization channels. Birkhäuser, Basel pp 145–185

    Google Scholar 

  • Wehner R (2003) Desert ant navigation: how miniature brains solve complex tasks. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 189:579–588

    Article  CAS  PubMed  Google Scholar 

  • Wehner R, Srinivasan M (2003) The Neurobiology of spatial behaviour, path integration in insects. Oxford University Press, Oxford, pp 9–30

    Google Scholar 

  • Wittlinger M, Wehner R, Wolf H (2006) The ant odometer: stepping on stilts and stumps. Science 312:1965–1967

    Article  CAS  PubMed  Google Scholar 

  • Wittmann T, Schwegler H (1995) Path integration - a network model. Biol Cybern 73(6):569–575. doi:10.1007/s004220050212

    Article  Google Scholar 

  • Wohlgemuth S, Ronacher B, Wehner R (2001) Ant odometry in the third dimension. Nature 411:795–798

    Article  CAS  PubMed  Google Scholar 

  • Yu A, Giese M, Poggio T (2002) Biophysically plusible implementations of the maximum operation. Neural Comput 14: 2857–2888

    Article  PubMed  Google Scholar 

  • Yuille A, Grzywacz N (1988) A computational theory for the perception of coherent visual motion. Nature 333(6168):71–74. 0028-0836 (Print) Journal Article

    Google Scholar 

  • Zars T, Fischer M, Schulz R, Heisenberg M (2000a) Localization of a short-term memory in Drosophila. Science 288:672–675

    Article  CAS  PubMed  Google Scholar 

  • Zars T, Wolf R, Davis R, Heisenberg M (2000b) Tissue-specific expression of a type I adenylyl cyclase rescues the rutabaga mutant memory defect: in search of the engram. Learn Mem 7:18–31

    Article  CAS  PubMed  Google Scholar 

  • Zhang S, Bock F, Si A, Tautz J, Srinivasan M (2005) Visual working memory in decision making by honey bees. Proc Natl Acad Sci USA 102:5250–5255

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

The authors thank Dr Markus Knaden for providing them with the behavioral data of the ants. This project was supported through the Synthetic Forager (FP7-IST 217148) and Neurochem (FP7-IST 216916).

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Authors and Affiliations

  1. Synthetic Perceptive, Emotive and Cognitive Systems, IUA, Universitat Pompeu Fabra, Tànger, 135, 08018, Barcelona, Spain

    Ulysses Bernardet & Sergi Bermúdez i Badia

  2. Synthetic Perceptive, Emotive and Cognitive Systems, IUA, ICREA, Universitat Pompeu Fabra, Tànger, 135, 08018, Barcelona, Spain

    Paul FMJ Verschure

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  1. Ulysses Bernardet
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Correspondence to Ulysses Bernardet.

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Bernardet, U., Bermúdez i Badia, S. & Verschure, P.F. A model for the neuronal substrate of dead reckoning and memory in arthropods: a comparative computational and behavioral study. Theory Biosci. 127, 163–175 (2008). https://doi.org/10.1007/s12064-008-0038-8

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