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Schema-based learning of adaptable and flexible prey-catching in anurans I. The basic architecture

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Abstract

A motor action often involves the coordination of several motor synergies and requires flexible adjustment of the ongoing execution based on feedback signals. To elucidate the neural mechanisms underlying the construction and selection of motor synergies, we study prey-capture in anurans. Experimental data demonstrate the intricate interaction between different motor synergies, including the interplay of their afferent feedback signals (Weerasuriya 1991; Anderson and Nishikawa 1996). Such data provide insights for the general issues concerning two-way information flow between sensory centers, motor circuits and periphery in motor coordination. We show how different afferent feedback signals about the status of the different components of the motor apparatus play a critical role in motor control as well as in learning. This paper, along with its companion paper, extend the model by Liaw et al. (1994) by integrating a number of different motor pattern generators, different types of afferent feedback, as well as the corresponding control structure within an adaptive framework we call Schema-Based Learning. We develop a model of the different MPGs involved in prey-catching as a vehicle to investigate the following questions: What are the characteristic features of the activity of a single muscle? How can these features be controlled by the premotor circuit? What are the strategies employed to generate and synchronize motor synergies? What is the role of afferent feedback in shaping the activity of a MPG? How can several MPGs share the same underlying circuitry and yet give rise to different motor patterns under different input conditions? In the companion paper we also extend the model by incorporating learning components that give rise to more flexible, adaptable and robust behaviors. To show these aspects we incorporate studies on experiments on lesions and the learning processes that allow the animal to recover its proper functioning

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References

  • Anderson CW, Nishikawa KC (1993) A prey type dependent hypoglossal feedback system in the frog Rana Pipiens. Brain Behav Evol 42:198–196

    Article  Google Scholar 

  • Anderson CW, Nishikawa KC (1996) The role of visual and proprioceptive information during motor program choice in frogs. J Comp Physiol A 179:753–762

    Article  PubMed  CAS  Google Scholar 

  • Arbib MA (1992) Schema theory. In: Shapiro S (eds) The encyclopedia of artificial intelligence 2nd edn. Wiley Interscience, New York, pp 1427–1443

    Google Scholar 

  • Arbib MA (1987) Levels of modeling of mechanisms of visually guided behavior (with commentaries and author’s response). Behavioral and Brain Sciences 10:407–465

    Google Scholar 

  • Bizzi E, Hogan N, Mussa-Ivaldi FA, Giszter S (1992) Does the nervous system use equilibrium-point control to guide single and multiple joint movements?. Brain Behav Sci 15:603–613

    Google Scholar 

  • Bizzi E., Saltiel P., Tresch M (1998) Modular organization of motor behavior. Z. Naturforsch [C] 53 (7-8):510-7

    CAS  Google Scholar 

  • Cervantes-Pérez F (1985) Modeling and analysis of neural networks in the visuomotor system of anuran amphibian. PhD Dissertation University of Massachussetts, Amherst

    Google Scholar 

  • Corbacho F, Nishikawa KC, Liaw JS, Arbib MA (1996a) An expectation-based model of adaptable and flexible prey-catching in anurans. Society for Neuroscience. Abs. 644.2

  • Corbacho F, Nishikawa KC, Liaw JS, Arbib MA (1996b) Adaptable and flexible prey-catching in anurans. In: Proceedings of the workshop on sensorimotor coordination: amphibians, models, and comparative studies. Sedona, Arizona

  • Corbacho F (1997) Schema-based learning: towards a theory of organization for autonomous agents. PhD Thesis, University of Southern California

  • Cruse H, Brunn D, Bartling Ch, Dean J, Dreifert M, Kindermann T, Schmitz J (1995a) Walking: a complex behavior controlled by simple networks. Adapt Behav 3:385–419

    Article  Google Scholar 

  • Cruse H, Bartling Ch, Cymbalyuk GDJ, Dreifert M (1995b) A modular artificial neuralnet for controlling a 6-legged walking system. Biol Cybern 72:421–430

    Article  PubMed  CAS  Google Scholar 

  • Cruse H (1999) Feeling our body—the basis of cognition? In: Hendrichs H (eds) Animal mind. Evolution and cognition, Vol 5, pp 162–173

  • de Vlugt E, van der Helm FCT, Schouten AC, Brouwn GG (2001) Analysis of the reflexive feedback control loop during posture maintenance. Biol Cybern 84:133–141

    Article  PubMed  Google Scholar 

  • Edward G, Freedman EG (2001) Interactions between eye and head control signals can account for movement kinematics. Biol Cybern 84:453–462

    Article  PubMed  Google Scholar 

  • Ekeberg O (1993) A combined neuronal and mechanical model of fish swimming. Biol Cybern 69:363–374

    Article  Google Scholar 

  • Ekeberg O, Lansner A, Grillner S (1995) The neural control of fish swimming studied through numerical simulations. Adap Behav 3:363–385

    Article  Google Scholar 

  • Eilam D, Smotherman WP (1998) How the neonatal rat gets to the nipple:common motor modules and their involvement in the expression of ealy motor behavior. Dev Psychobiol 1:57–66

    Article  Google Scholar 

  • Emerson SB (1977) Movement of the hyoid in frogs during feeding. Am J Anat 149:115–120

    Article  PubMed  CAS  Google Scholar 

  • Ewert J-P (1984) Tectal mechanism that underlies prey-catching and avoidance behavior in toads. In: Vanegas H (eds) Comparative neurology of the optic tectum. Plenum, NY, pp 247–416

    Google Scholar 

  • Ewert J-P (1987) Neuroethology of releasing mechanisms: prey catching in toads. Brain Behav Sci 10:337–405

    Article  Google Scholar 

  • Ewert J-P.(1997) Neural correlates of key stimulus and releasing mechanism: a case study and two concepts. Trends Neurosci 20(8):332–339

    Article  PubMed  CAS  Google Scholar 

  • Ewert J-P, Arbib MA (1989) Visuomotor coordination: amphibians, comparisons, models & robots. Plenum, New York

    Google Scholar 

  • Ewert J-P, Arbib MA (1991) Visual structures and integrated functions. Research notes in neural computing, vol. 3. Springer, Berlin Heidelberg New York

    Google Scholar 

  • Ewert J-P, Buxbaum-Conradi H, Fingerling S, Schurg-Pfeiffer E, Beneke TW, Dinges AW, Glagow M, Schwippert WW (1992) Adapted and adaptive properties in neural networks for visual pattern discrimination: a neurobiological analysis toward neural engineering adaptive behavior, vol. 1, N 2, pp 123–154

  • Ewert J-P, Buxbaum-Conradi H, Dreisvogt F, Glagow M, Merkel-Harf C, Röttgen A, Schürg-Pfeifer E, Schwippert WW (2001) Neural modulation of visuomotor functions underlying prey-catching behaviour in anurans: perception, attention, motor performance, learning. Comp Biochem Physiol A 128:417–461

    Article  CAS  Google Scholar 

  • Ewert J-P, Weerasuriya A, Schürg-Pfeiffer E, Framing, E (1990) Responses of medullary neurons to moving visual stimuli in the common toad: I) Characterization of medial reticular neurons by extracellular recording. J Comp Physiol A 167:495–508

    Article  PubMed  CAS  Google Scholar 

  • Ewert J-P, Wietersheim Av (1974) Musterauswertung durch tectale und thalamus/ praetectale Nervennetze im visuellen System der Krote (Bufo bufo L.). J Comp Physiol 92:131–148

    Article  Google Scholar 

  • Gaillard F, Arbib MA, Corbacho F, Lee HB (1998) Modeling the physiological responses of anuran r3 ganglion cells. Vision Res 38:1282–1299

    Article  Google Scholar 

  • Gans C (1992) Electromyography, in biomechanics structures and systems. In: Biewener AA (eds) A practical approach. Oxford University Press, New York

    Google Scholar 

  • Gans C, Gorniak GC (1982) Functional morphology of lingual protrusion in marine toads (Bufo marinus). Amer J Anat 163:195–222

    Article  PubMed  CAS  Google Scholar 

  • Gottlieb GL, Latash ML, Corcos DM, Liubinskas TJ, Agarwal GC (1992) Organizing principles for single joint movements: V. Agonist-antagonist interactions. J Neurophysiol 67:1417–1427

    PubMed  CAS  Google Scholar 

  • Grantyn A, Berthoz A (1988) The role of the tectoreticulospinal system in the control of head movement. In: Peterson BP, Richmond FJ (eds) Control of head movement. Oxford University Press, New York, pp 224–244

    Google Scholar 

  • Grillner S, Deliagina T, Ekeberg O, El Manira A, Hill RH, Lansner A, Orlovsky GN, Wallen P (1995) Neural networks that coordinate locomotion and body orientation in lamprey. Trends Neurosci 18:270–279

    Article  PubMed  CAS  Google Scholar 

  • Grillner S (1997) Ion channels and locomotion. Science 278:1087–1088

    Article  PubMed  CAS  Google Scholar 

  • Grobstein P (1989) Organization in the sensorimotor interface: a case study with increased resolution. In: Ewert J-S, Arbib MA (eds) Visuomotor coordination: amphibians, comparisons, models, and robots. Plenum, New York, pp 537–568

    Google Scholar 

  • Grüsser O-J, Grüsser-Cornehls U (1976) Neurophysiology of the anuran visual system. In: Llinas R, Precht W (eds) Frog Neurobiology. Springer Berlin Heidelberg, New york, pp 297–385

    Google Scholar 

  • Gurney K, Prescott TJ, Redgrave P (2001) A computational model of action selection in the basal ganglia. I. A new functional anatomy. Biol Cybern 84:401–410

    Article  PubMed  CAS  Google Scholar 

  • Gurney K, Prescott TJ, Redgrave P (2001) A computational model of action selection in the basal ganglia. II. Analysis and simulation of behaviour. Biol Cybern 84:411–423

    Article  PubMed  CAS  Google Scholar 

  • Hatsopoulos NG (1996) Coupling the neural and physical dynamics in rhythmic movements. Neural Comput 8:567–581

    Article  PubMed  CAS  Google Scholar 

  • Herrick CJ (1930) The medulla oblongata of Necturus. J Comp Neurol 50:1–96

    Article  Google Scholar 

  • Hinsche G (1935) Ein Schnappreflex nach “Nichts” bei Anuren. Zool Anz 111:113–122

    Google Scholar 

  • Hoff B, Arbib MA (1993) Models of trajectory formation and temporal interaction of reach and grasp. J Mot Behav 25(3):175–192

    Article  PubMed  Google Scholar 

  • Huerta R, Sanchez-Montañes M, Corbacho F, Siguenza JA (2000). Optimal central pattern generator to control a pyloric-based system. Biol Cybern 82:85–94

    Article  PubMed  CAS  Google Scholar 

  • Ingle D (1983) Brain mechanism of visual localization by frogs and toads. In: Ewert J-P, Capranica R, Ingle D (eds) Advances in vertebrate neuroethology. Plenum, New York

    Google Scholar 

  • Ito M (1986) Neural systems controlling movements. TINS 9:515–518

    Google Scholar 

  • Kozlov AK, Ullen F, Fagerstedt P, Aurell E, Lansner A, Grillner S (2002) Mechanisms for lateral turns in lamprey in response to descending unilateral commands: a modeling study. Biol Cybern 86:1–14

    Article  PubMed  Google Scholar 

  • Liaw J-S, Weerasuriya A, Arbib MA (1994) Snapping: a paradigm for modeling coordination of motor synergies. Neural Netw 7:1137–1152

    Article  Google Scholar 

  • Liaw J-S, Weerasuriya A, Arbib MA (1998) Feedback modulation in coordinating rapid motor synergies. Center for neural engineering technical report, University of Southern California

  • Loeb GE, Gans C (1986) Electromyography for Experimentalists. University of Chicago Press, Chicago

    Google Scholar 

  • Loeb GE, Brown IE, Cheng EJ (1999) A hierarchical foundation for models of sensorimotor control. Exp Brain Res 126(1):1–18

    Article  PubMed  CAS  Google Scholar 

  • Lund JP, Enomoto S (1988) The generation of mastication by the mammalian central nervous system. In: Cohen AH, Rossignol S, Grillner D (eds) Neural control of rhythmic movements in vertebrates . Wiley, New York, pp 41–72

    Google Scholar 

  • Lyons DM, Arbib MA (1988) A formal model of distributed computation for schema-based robot control. IEEE J. Robotics and Automation, 5: 280–293

    Article  Google Scholar 

  • Mallet ES, Yamaguchi GT, Birch JM, Nishikawa KC (2001) Feeding motor patterns in anurans: insights from biomechanical modeling. Am Zool 41:1364–1374

    Article  Google Scholar 

  • Matsushima T, Satou M, Ueda K (1985) An electromyographic analysis of electrically-evoked prey-catching behavior by means of stimuli applied to the optic tectum in the Japanese toad. Neurosci Res 3:154–161

    Article  PubMed  CAS  Google Scholar 

  • Matsushima T, Satou M, Ueda K (1986) Glossopharyngeal and tectal influences on tongue-muscle motoneuorns in the Japanese toad. Brain Res 365:198–203

    Article  PubMed  CAS  Google Scholar 

  • Matsushima T, Satou M, Ueda K (1988) Neuronal pathways for the lingual reflex in the Japanese toad. J Comp Physiol A 164:173–193

    Article  PubMed  CAS  Google Scholar 

  • Matsushima T, Satou M, Ueda K (1989) Medullary reticular neurons in the Japanese toad: morphologies and excitatory inputs from the optic tectum. J Comp Physiol A 166:7–22

    Article  PubMed  CAS  Google Scholar 

  • Nishikawa K, Roth G (1991) The mechanism of tongue protraction during prey capture in the frog Discoglossus pictus. J Exp Biol 159:217–234

    Google Scholar 

  • Nishikawa KC, Gans C (1992). The role of hypoglossal sensory feedback during feeding in the Marine toad. Bufo marinus. J Exp Zool 264:245–252

    Article  CAS  Google Scholar 

  • Nishikawa KC, Anderson CW, Deban SM, O’Reilly JC (1992) The Evolution of Neural Circuits Controlling Feeding Behavior in Frogs. Brain Behav Evol 40:125–140

    Article  PubMed  CAS  Google Scholar 

  • Nishikawa KC, Mallett ES, Yamaguchi GT (1997) A biomechanical model for the simulation of prey capture in toads. Soc Neurosci Abstr 23:2135

    Google Scholar 

  • Ogihara N, Yamazaki N (2001). Generation of human bipedal locomotion by a bio-mimetic neuro-musculo-skeletal model. Biol Cybern 84:1–11

    Article  PubMed  CAS  Google Scholar 

  • Robinson DA (1981) Control of eye movements. In: Brookhart JM, Montcastle VB, Brooks VB, Roberts BL (eds) Handbook of Physiology. American Physiology Society, Bethesda, pp 1275–1320

    Google Scholar 

  • Roth G (1987) Visual behavior in salamanders. Springer, Berlin Heidelberg New York

    Google Scholar 

  • Rumelhart DE, Norman DA (1982) Simulating a skilled typist: a study of skilled cognitive-motor performance. Cognitive Science 6:1–36

    Article  Google Scholar 

  • Sanguineti V, Laboissiere R, Ostry DJ (1998) A dynamic biomechanical model for the neural control of speech production. J Acoust Soc Am 103:1615–1627

    Article  PubMed  CAS  Google Scholar 

  • Schmidt RA, Sherwood DE, Walter CB (1988) Rapid movement with reversals in direction: 1. The control of movement time. Exp Brain Res 69:344–354

    Article  PubMed  CAS  Google Scholar 

  • Schöner G (1995) Recent developments and problems in human movement science and their conceptual implications. Ecol Psychol 7:291–314

    Article  Google Scholar 

  • Schöner G, Dijkstra TMH, Jeka JJ (1998) Action-Perception patterns emerge from coupling and adaptation. Ecol Psychol 10:323–346

    Article  Google Scholar 

  • Schomaker LRB (1992) A neural oscillator-network model of temporal pattern generation. Hum Mov Sci 11:181–192

    Article  Google Scholar 

  • Schürg-Pffieffer E (1989) Behavior-correlated properties of tectal neurons in freely moving toads. In: Ewert J-P, Arbib MA (eds) Visuomotor coordination, amphians, comparisons, models, and robots. Plenum, New York, pp 451–480

    Google Scholar 

  • Schwippert W, Beneke T, Framing E (1989) Visual integration in bulbal structures of toads: intra/extra-cellular recording and labeling studies. In: Ewert J-P, Arbib MA (eds) Visuomotor coordination, amphians, comparisons, models, and robots. Plenum, New York, pp 481–536

    Google Scholar 

  • Schwippert W, Beneke T, Ewert J-P (1990) Responses of medullary neurons to moving visual stimuli in the common toad: II) An intracellular recording and cobalt-lysine labeling study. J Comp Physiol A 167:509–520

    Article  PubMed  CAS  Google Scholar 

  • Scudder CA (1988) A new local feedback model of the saccadic burst generator. J Neurophysiol 59:1455–1475

    PubMed  CAS  Google Scholar 

  • Selverston AI, Moulins M (eds) (1987) The crustacean stomatogastric system. Springer, Berlin Heidelberg New York, pp. 1–1

  • Sherwood DE, Schmidt RA, Walter CB (1988) Rapid movement with reversals in direction: 1. The control of movement amplitude and inertial load. Exp Brain Res 69:355–367

    CAS  Google Scholar 

  • Steinkühler U, Cruse H (1998) A holistic model for an internal representation to control the movement of a manipulator with redundant degrees of freedom. Biol. Cybern 79:457–466

    Article  Google Scholar 

  • Sumbre G, Gutfreund Y, Fiorito G, Flash T, Hochner B (2001) Control of octopus arm extension by a peripheral motor program. Science 293(5536):1845–8

    Article  PubMed  CAS  Google Scholar 

  • Teeters JL, Arbib MA, Corbacho F, Lee HB (1993) Quantitative modeling of responses of anuran retina: Stimulus shape and size dependency. Vision Res 33:2361–2379

    Article  PubMed  CAS  Google Scholar 

  • Tresch MC, Saltiel P, Bizzi E (1999) The construction of movement by the spinal cord. Nat. Neurosci. (2):162–7

  • Valdez CM, Nishikawa KC (1997) Sensory modulation and motor program choice during feeding in the Austrailian frog, Cyclorana novachollandiae. Journal of Comparative Physiology A 180:187–202

    Article  CAS  Google Scholar 

  • van der Smagt P (1998) Cerebellar control of robot arms. Connect Sci 10:301–320

    Article  Google Scholar 

  • van der Kooij H, Jacobs R, Koopman B, van der Helm F (2001) An adaptive model of sensory integration in a dynamic environment applied to human stance control. Biol Cybern 84:103–115

    Article  PubMed  Google Scholar 

  • Weerasuriya A (1983) Snapping in toads: some aspects of sensorimotor interfacing and motor pattern generation. In: Ewert J-P, Capranicca RR, Ingle DJ (eds) Advances in vertebrate neuroethology. Plenum, New York, pp 613–627

    Google Scholar 

  • Weerasuriya A (1989) In search of the pattern generator for snapping in toads. In: Ewert J-P, Arbib MA (eds) Visuomotor coordination, amphibians, comparisons, models, and robots. Plenum, New York, pp 589–614

    Google Scholar 

  • Weerasuriya A (1991) Motor pattern generators in anuran prey capture. In: Arbib MA, Ewert J-P (eds) Visual structure and integrated functions. research notes in neural computing. Springer, Berlin Heidelberg New York, pp 255–270

    Google Scholar 

  • Weitzenfeld A (1991) NSL, neural simulation language, technical report 91-05. Center for Neural Engineering, University of Southern California

  • Winter DA (1979) Biomechanics of human movement. Wiley, New York

    Google Scholar 

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Authors and Affiliations

  1. USC Brain Project, University of Southern California, Los Angeles, CA, 90089-0871, USA

    Fernando Corbacho, Jim-Shih Liaw & Michael A. Arbib

  2. Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, 86011-5640, USA

    Kiisa C. Nishikawa

  3. School of Medicine, Mercer University, Macon, GA, 31207, USA

    Ananda Weerasuriya

  4. Biomedical Engineering, University of Southern California, Los Angeles, CA, 90089-0871, USA

    Jim-Shih Liaw

  5. Grupo de Neurocomputación Biológica (GNB), Ingeniería Informática, Universidad Autónoma de Madrid, 28049, Madrid, Spain

    Fernando Corbacho

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  1. Fernando Corbacho
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  2. Kiisa C. Nishikawa
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  3. Ananda Weerasuriya
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  4. Jim-Shih Liaw
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  5. Michael A. Arbib
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Correspondence to Fernando Corbacho.

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Corbacho, F., Nishikawa, K.C., Weerasuriya, A. et al. Schema-based learning of adaptable and flexible prey-catching in anurans I. The basic architecture. Biol Cybern 93, 391–409 (2005). https://doi.org/10.1007/s00422-005-0013-0

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