A Cerebellar Model of Timing and Prediction in the Control of Reaching

A simplified model of the cerebellum was developed to explore its potential for adaptive, predictive control based on delayed feedback information. An abstract representation of a single Purkinje cell with multistable properties was interfaced, using a formalized premotor network, with a simulated single degree-of-freedom limb. The limb actuator was a nonlinear spring-mass system based on the nonlinear velocity dependence of the stretch reflex. By including realistic mossy fiber signals, as well as realistic conduction delays in afferent and efferent pathways, the model allowed the investigation of timing and predictive processes relevant to cerebellar involvement in the control of movement. The model regulates movement by learning to react in an anticipatory fashion to sensory feedback. Learning depends on training information generated from corrective movements and uses a temporally asymmetric form of plasticity for the parallel fiber synapses on Purkinje cells.

[1]  J. Lance Anatomy and physiology of the cerebellum. , 1963, Bulletin of the Post-Graduate Committee in Medicine, University of Sydney.

[2]  D. Marr A theory of cerebellar cortex , 1969, The Journal of physiology.

[3]  D. Robinson,et al.  Absence of a stretch reflex in extraocular muscles of the monkey. , 1971, Journal of neurophysiology.

[4]  J. Albus A Theory of Cerebellar Function , 1971 .

[5]  A. H. Klopf,et al.  Brain Function and Adaptive Systems: A Heterostatic Theory , 1972 .

[6]  L. Optican,et al.  Cerebellar-dependent adaptive control of primate saccadic system. , 1980, Journal of neurophysiology.

[7]  R. Llinás,et al.  Electrophysiological properties of in vitro Purkinje cell dendrites in mammalian cerebellar slices. , 1980, The Journal of physiology.

[8]  O. Oscarsson,et al.  CLIMBING FIBRE ELICITED PROLONGED DEPOLARIZATIONS IN PURKINJE CELL DENDRITES , 1981 .

[9]  A G Barto,et al.  Toward a modern theory of adaptive networks: expectation and prediction. , 1981, Psychological review.

[10]  John F. Kalaska,et al.  Spatial coding of movement: A hypothesis concerning the coding of movement direction by motor cortical populations , 1983 .

[11]  Wg Lehnert,et al.  THE HEDONISTIC NEURON - A THEORY OF MEMORY, LEARNING, AND INTELLIGENCE - KLOPF,AH , 1983 .

[12]  John S. Edwards,et al.  The Hedonistic Neuron: A Theory of Memory, Learning and Intelligence , 1983 .

[13]  G. Hesslow,et al.  Dendritic plateau potentials evoked in Purkinje cells by parallel fibre volleys in the cat. , 1983, The Journal of physiology.

[14]  J. Houk,et al.  Somatosensory properties of the inferior olive of the cat , 1983, The Journal of comparative neurology.

[15]  J. Houk,et al.  Nonlinear viscosity of human wrist. , 1984, Journal of neurophysiology.

[16]  B. Alstermark,et al.  Visually guided switching of forelimb target reaching in cats. , 1984, Acta physiologica Scandinavica.

[17]  Masao Ito The Cerebellum And Neural Control , 1984 .

[18]  G. Hesslow,et al.  Integration of Mossy Fiber and Climbing Fiber Inputs to Purkinje Cells , 1984 .

[19]  Graham C. Goodwin,et al.  Adaptive filtering prediction and control , 1984 .

[20]  J. Houk,et al.  Inferior olivary neurons in the awake cat: detection of contact and passive body displacement. , 1985, Journal of neurophysiology.

[21]  C. Prablanc,et al.  Large adjustments in visually guided reaching do not depend on vision of the hand or perception of target displacement , 1986, Nature.

[22]  Paul E. Kinahan,et al.  A teachable neural network based on an unorthodox neuron , 1986 .

[23]  G W Hoffmann,et al.  A neural network model based on the analogy with the immune system. , 1986, Journal of theoretical biology.

[24]  S. Sasaki,et al.  Long C3-C5 propriospinal neurones in the cat , 1987, Brain Research.

[25]  D. Armstrong,et al.  Complex spikes in Purkinje cells in the lateral vermis (b zone) of the cat cerebellum during locomotion. , 1987, The Journal of physiology.

[26]  M. Sakurai Synaptic modification of parallel fibre‐Purkinje cell transmission in in vitro guinea‐pig cerebellar slices. , 1987, The Journal of physiology.

[27]  B. Alstermark,et al.  Effect of different spinal cord lesions on visually guided switching of target-reaching in cats , 1987, Neuroscience Research.

[28]  A. Klopf A neuronal model of classical conditioning , 1988 .

[29]  M. Kano,et al.  Stimulation parameters influencing climbing fibre induced long-term depression of parallel fibre synapses , 1989, Neuroscience Research.

[30]  James C. Houk,et al.  An Adaptive Sensorimotor Network Inspired by the Anatomy and Physiology , 1989 .

[31]  J. Houk Cooperative Control of Limb Movements by the Motor Cortex, Brainstem and , 1989 .

[32]  L. Wang,et al.  Synchronous neural networks of nonlinear threshold elements with hysteresis. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[33]  Richard S. Sutton,et al.  Time-Derivative Models of Pavlovian Reinforcement , 1990 .

[34]  J. Keeler A dynamical system view of cerebellar function , 1990 .

[35]  James C. Houk,et al.  Cerebellar control of endpoint position-a simulation model , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[36]  J. Houk,et al.  Nonlinear damping of limb motion , 1990 .

[37]  C Ghez,et al.  Roles of proprioceptive input in the programming of arm trajectories. , 1990, Cold Spring Harbor symposia on quantitative biology.

[38]  O. Kiehn Plateau potentials and active integration in the ‘final common pathway’ for motor behaviour , 1991, Trends in Neurosciences.

[39]  M. Kawato,et al.  Model of four regions of the cerebellum , 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.

[40]  Aron M. Gutman Bistability of Dendrites , 1991, Int. J. Neural Syst..

[41]  N. Hogan,et al.  Does the nervous system use equilibrium-point control to guide single and multiple joint movements? , 1992, The Behavioral and brain sciences.

[42]  T Tyrrell,et al.  Cerebellar cortex: its simulation and the relevance of Marr's theory. , 1992, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[43]  C. Prablanc,et al.  Automatic control during hand reaching at undetected two-dimensional target displacements. , 1992, Journal of neurophysiology.

[44]  A. Barto,et al.  Distributed sensorimotor learning , 1992 .

[45]  David Willshaw,et al.  Performance characteristics of the associative net , 1992 .

[46]  J. Houk,et al.  Cooperative control of gaze by the superior colliculus, brainstem and cerebellum , 1992 .

[47]  J. Houk,et al.  Movement-related inputs to intermediate cerebellum of the monkey. , 1993, Journal of neurophysiology.

[48]  A. Barto,et al.  Distributed motor commands in the limb premotor network , 1993, Trends in Neurosciences.

[49]  J. Houk,et al.  Output organization of intermediate cerebellum of the monkey. , 1993, Journal of neurophysiology.

[50]  D. Alkon,et al.  Rabbit cerebellar slice analysis of long-term depression and its role in classical conditioning , 1993, Brain Research.

[51]  Satinder Singh,et al.  Distributed Representation of Limb Motor Programs in Arrays of Adjustable Pattern Generators , 1993, Journal of Cognitive Neuroscience.

[52]  D. Wolpert,et al.  Is the cerebellum a smith predictor? , 1993, Journal of motor behavior.

[53]  J. Houk,et al.  Erratum: Movement-related inputs to intermediate cerebellum of the monkey (Journal of Neurophysiology (January 1993) 69 (74-94)) , 1993 .

[54]  Aron Gutman Gelfand-Tsetlin Principle of Minimal Afferentation and Bistability of Dendrites , 1994, Int. J. Neural Syst..

[55]  Kuniharu Arai,et al.  Two-dimensional neural network model of the primate saccadic system , 1994, Neural Networks.

[56]  P. Dean,et al.  Modelling the role of the cerebellar fastigial nuclei in producing accurate saccades: the importance of burst timing , 1995, Neuroscience.

[57]  R. F. Thompson,et al.  Temporal specificity of long-term depression in parallel fiber--Purkinje synapses in rat cerebellar slice. , 1995, Learning & memory.

[58]  James C. Houk,et al.  A Predictive Switching Model of Cerebellar Movement Control , 1995, NIPS.

[59]  S P Wise,et al.  Distributed modular architectures linking basal ganglia, cerebellum, and cerebral cortex: their role in planning and controlling action. , 1995, Cerebral cortex.

[60]  Lance M. Optican,et al.  A field theory of saccade generation: Temporal-to-spatial transform in the superior colliculus , 1995, Vision Research.

[61]  A. Gibson,et al.  Reduction of rostral dorsal accessory olive responses during reaching. , 1996, Journal of neurophysiology.

[62]  F. Crépel,et al.  Cellular mechanisms of long-term depression in the cerebellum , 1996 .

[63]  Michael A. Arbib,et al.  A model of the cerebellum in adaptive control of saccadic gain , 1996, Biol. Cybern..

[64]  S. Lisberger,et al.  The Cerebellum: A Neuronal Learning Machine? , 1996, Science.

[65]  Peter Ford Dominey,et al.  A model of the cerebellum in adaptive control of saccadic gain , 1996, Biological cybernetics.

[66]  Douglas R. Wylie,et al.  More on climbing fiber signals and their consequence(s) , 1996 .

[67]  A. Barto,et al.  Models of the cerebellum and motor learning , 1996 .

[68]  J. Houk,et al.  Computational significance of the cellular mechanisms for synaptic plasticity in Purkinje cells , 1996 .

[69]  D. Alkon,et al.  Pairing-specific long-term depression of Purkinje cell excitatory postsynaptic potentials results from a classical conditioning procedure in the rabbit cerebellar slice. , 1996, Journal of neurophysiology.

[70]  T. Ebner,et al.  Movement kinematics encoded in complex spike discharge of primate cerebellar Purkinje cells , 1997, Neuroreport.

[71]  James C. Houk,et al.  A model of cerebellar learning for control of arm movements using muscle synergies , 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.

[72]  James C. Houk,et al.  Cerebellar learning for control of a two-link arm in muscle space , 1997, Proceedings of International Conference on Robotics and Automation.

[73]  B. Alstermark,et al.  Effect of spinal cord lesions on forelimb target-reaching and on visually guided switching of target-reaching in the cat , 1997, Neuroscience Research.

[74]  A G Barto,et al.  Prediction of complex two-dimensional trajectories by a cerebellar model of smooth pursuit eye movement. , 1997, Journal of neurophysiology.

[75]  R. Tsien,et al.  Synergies and Coincidence Requirements between NO, cGMP, and Ca2+ in the Induction of Cerebellar Long-Term Depression , 1997, Neuron.

[76]  Richard S. Sutton,et al.  Introduction to Reinforcement Learning , 1998 .

[77]  Tatsuya Kimura,et al.  Cerebellar complex spikes encode both destinations and errors in arm movements , 1998, Nature.

[78]  S. Kitazawa,et al.  Possible roles of the cerebellar complex spikes during arm movements , 1998, Neuroscience Research.

[79]  G. Inbar,et al.  The Use of a Nonlinear Muscle Model in Explaining the Relationship Between Duration, Amplitude, and Peak Velocity of Human Rapid Movements. , 1999, Journal of motor behavior.

[80]  Stephen Grossberg,et al.  A neural model of cortico-cerebellar interactions during attentive imitation and predictive learning of sequential handwriting movements , 2000, Neural Networks.