Computation of inverse functions in a model of cerebellar and reflex pathways allows to control a mobile mechanical segment.
The command and control of limb movements by the cerebellar and reflex pathways are modeled by means of a circuit whose structure is deduced from functional constraints. One constraint is that fast limb movements must be accurate although they cannot be continuously controlled in closed loop by use of sensory signals. Thus, the pathways which process the motor orders must contain approximate inverse functions of the bio-mechanical functions of the limb and of the muscles. This can be achieved by means of parallel feedback loops, whose pattern turns out to be comparable to the anatomy of the cerebellar pathways. They contain neural networks able to anticipate the motor consequences of the motor orders, modeled by artificial neural networks whose connectivity is similar to that of the cerebellar cortex. These networks learn the direct biomechanical functions of the limbs and muscles by means of a supervised learning process. Teaching signals calculated from motor errors are sent to the learning sites, as, in the cerebellum, complex spikes issued from the inferior olive are conveyed to the Purkinje cells by climbing fibers. Learning rules are deduced by a differential calculation, as classical gradient rules, and they account for the long term depression which takes place in the dendritic arborizations of the Purkinje cells. Another constraint is that reflexes must not impede voluntary movements while remaining at any instant ready to oppose perturbations. Therefore, efferent copies of the motor orders are sent to the interneurones of the reflexes, where they cancel the sensory-motor consequences of the voluntary movements. After learning, the model is able to drive accurately, both in velocity and position, angular movements of a rod actuated by two pneumatic McKibben muscles. Reflexes comparable to the myotatic and tendinous reflexes, and stabilizing reactions comparable to the cerebellar sensory-motor reactions, reduce efficiently the effects of perturbing torques. These results allow to link the behavioral concepts of the equilibrium-point "lambda model" [J Motor Behav 18 (1986) 17] with anatomical and physiological features: gains of reflexes and sensori-motor reactions set the slope of the "invariant characteristic," and efferent copies set the "threshold of the stretch reflex." Thus, mathematical and physical laws account for the raison d'etre of the inhibitory nature of Purkinje cells and for the conspicuous anatomical pattern of the cerebellar pathways. These properties of these pathways allow to perform approximate inverse calculations after learning of direct functions, and insure also the coordination of voluntary and reflex motor orders.
Ebadzadeh
M
M
Ecole Nationale Supérieure des Télécommunications, CNRS URA 820, Département de Traitement des Signaux et des Images, 46 rue Barrault 75634 Paris 13, France. ebadzade@enst.fr
Tondu
B
B
Darlot
C
C
D000465:Algorithms; D001185:Artificial Intelligence; D001696:Biomechanical Phenomena; D002525:Cerebellar Cortex / Q000166:cytology / Q000502:physiology; D002529:Cerebellar Nuclei / Q000166:cytology / Q000502:physiology; D002531:Cerebellum / Q000166:cytology / Q000502:physiology*; D005121:Extremities / Q000502:physiology*; D008570:Memory, Short-Term / Q000502:physiology; D008959:Models, Neurological; D009046:Motor Neurons / Q000502:physiology; D009068:Movement / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology; D018482:Muscle, Skeletal / Q000294:innervation / Q000502:physiology; D016571:Neural Networks, Computer; D009434:Neural Pathways / Q000502:physiology*; D009474:Neurons / Q000502:physiology; D009847:Olivary Nucleus / Q000166:cytology / Q000502:physiology; D012012:Red Nucleus / Q000502:physiology; D012018:Reflex / Q000502:physiology*