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Functions of Distributed Plasticity in a Biologically-Inspired Adaptive Control Algorithm: From Electrophysiology to Robotics University of Edinburgh University of Sheffield University of the West of England 1. Background to project AwayDay 2005 Slide No 2 • • • In some respects animal movements better than robot movement Could in part be due to characteristics of biological control algorithms Which region of the brain particularly concerned with skilled movement? AwayDay 2005 Slide No 3 Cerebellum • located at base of brain (here a human brain) • looks like a small version of overlying cerebral cortex? • cerebellum = ‘little brain’ AwayDay 2005 Slide No 4 Cerebellar Function • Clinical and experimental observations of cerebellar damage • Does not cause paralysis, but makes many movements inaccurate, slow and uncoordinated • Similar to effects of alcohol: tests for intoxication may resemble clinical test for cerebellar impairment AwayDay 2005 Slide No 5 • Conclusion: cerebellum is particularly associated with those features of movements that distinguish animals from robots • Framework of project: to investigate whether there are features of cerebellar control that are likely to be of interest to robotics AwayDay 2005 Slide No 6 1. Framework: is cerebellar control of interest to robotics? 2. Problem AwayDay 2005 Slide No 7 Cerebellar Cortex • Adjacent to and connected with the the brainstem • Has its own cortex (= rind) AwayDay 2005 Slide No 8 Cerebellar Cortex • Small number of cell types in cerebellar cortex • AwayDay 2005 Connected to form a distinctive microcircuit Slide No 9 Cerebellar Microcircuitry • Classic work published in 1967 • Investigated anatomy and electrophysiology of microcircuit • Same basic circuit repeated many times (hence “neuronal machine”) • Important: half the cells in the entire brain are in the cerebellum AwayDay 2005 Slide No 10 Mossy Fibres Idea of Cerebellar ‘Chip’ • Structure of cerebellar cortex is very uniform over its entire surface • Different regions have different inputs and outputs, (microzones) but same basic organisation • Gives rise to idea of cerebellar chip: ~5000, each with its own particular connections. AwayDay 2005 Slide No 11 Choose Your Task • Consequence of this arrangement: all motor tasks using the cerebellum employ the same basic cerebellar algorithm • The investigator can therefore choose the most ‘appropriate’ motor task • In our case, control of the vestibulo-ocular reflex (VOR) AwayDay 2005 Slide No 12 Vestibulo-Ocular Reflex (VOR) • Vision is degraded if the image moves (‘slips’) too much across the retina • Retinal slip would be produced by movements of the head, such as occur in locomotion • The VOR acts to counterrotate the eyes to prevent retinal slip, i.e. to maintain stable gaze • Usually not aware when we use it AwayDay 2005 Slide No 13 VOR Control: Basic Circuit Semicircular canals Primary Vestibular Neurons Secondary Vestibular Neurons Ocular Motor Neurons Extraocular Muscles • Input from vestibular position, senses head movement • Passed to interneurons in vestibular nuclei (secondary vestibular neurons) • Thence to motor neurons that control the eye muscles • This circuit in brainstem (just below cerebellum) AwayDay 2005 Slide No 14 VOR Control: Cerebellum Flocculus head velocity Brainstem Retinal slip motoneuron firing Eye Muscles Orbital Tissue eye velocity • Cerebellar flocculus receives information about – Head velocity – Eye movement commands – Retinal slip • Projects back to brainstem AwayDay 2005 Slide No 15 VOR Control: Generalised Version head velocity reference r(t) AwayDay 2005 Flocculus and Brainstem Controller motoneuron firing command u(t) Eye Muscles Orbital Tissue Plant eye velocity output y(t) Slide No 16 Not Feedback Control reference r(t) Controller command u(t) X Plant output y(t) Sensor • Retinal slip signal is delayed by 100 ms (visual processing) • Feedback control would become unstable at ~ 2.5 Hz, yet VOR operates up to ~25 Hz • Feedback control not suitable AwayDay 2005 Slide No 17 Control Method: Open-Loop reference r(t) Inverse Plant Model P-1 command u(t) Plant P output y(t) • If feedback not available, then open-loop control must be used • If reference signal is desired output, then the controller becomes an inverse model of the plant (‘plant compensation’) AwayDay 2005 Slide No 18 Adaptive Control desired output r(t) Inverse Plant Model P-1 command u(t) training signal Plant P output y(t) Sensor • How can we be sure the inverse plant model is accurate? • Requires constant calibration – ‘adaptive control’ • Use information about system output for learning, rather than online control AwayDay 2005 Slide No 19 VOR Equivalent head velocity Brainstem Flocculus motoneuron firing Eye Muscles Orbital Tissue eye velocity retinal slip • Available training signal is retinal slip, known to be sent to the flocculus • Consistent with flocculus being the adaptive part of the controller • Consistent with e.g. lesion evidence that VOR adaptation is lost after floccular inactivation AwayDay 2005 Slide No 20 Why VOR Calibration? 1. Well-defined adaptive control problem 2. Eye movements are relatively simple – single joint instead of up to ~6 joints in finger movements – constant load 3. Great deal known about underlying circuitry 4. Well established cerebellar involvement AwayDay 2005 Slide No 21 1. Framework: is cerebellar control of interest to robotics? 2. Problem: adaptive calibration of VOR 3. Approach: multidisciplinary AwayDay 2005 Slide No 22 Multidisciplinary Approach • Modelling – (theoretical neuroscience, Sheffield) • Electrophysiology – (experimental neuroscience, Edinburgh) • Robotics – (University of the West of England, Bristol) AwayDay 2005 Slide No 23 General Modelling Task • Devise a working algorithm that connects the microcircuit to the behavioural competence • Obeys known anatomical and physiological constraints AwayDay 2005 Slide No 24 Cerebellar Modelling • Cerebellar microcircuit has been extensively modelled, starting with classic work of Marr (1969) and Albus (1971) • Here in more modern form of the adaptive filter AwayDay 2005 Slide No 25 Specific Modelling Problem • Extensive experimental work shows that in VOR calibration there are TWO sites of plasticity 1. In cerebellar cortex, as predicted by adaptive filter models 2. In the brainstem • AwayDay 2005 What are the computational advantages of this distributed plasticity? Slide No 26 Electrophysiology: Problem Mayank B Dutia Centre for Integrative Physiology University of Edinburgh AwayDay 2005 • What are the learning rules underlying brainstem plasticity? • Existence known for ~20 years, rules yet to be identified • Critical for understanding computation significance Slide No 27 Electrophysiology: Technique Rostral Midline Medial Vestibular Nucleus • Record from neurons in slices through brainstem • Look for neurons that receive input for the flocculus (flocculus target neurons, FTNs) Caudal Rat Brainstem Slice AwayDay 2005 Slide No 28 Robotics Does Algorithm Work in Real World? • Tony Pipe, Chris Melhuish, UWE Bristol • Camera stabilisation • How does algorithm compare with control engineering alternatives? AwayDay 2005 Slide No 29 Multidisciplinary Approach 1. Framework: is cerebellar control of interest to robotics? 2. Problem: adaptive calibration of VOR 3. Approach: multidisciplinary Modelling: plausible candidate algorithm Electrophysiology: biological underpin Robotics: real world application AwayDay 2005 Slide No 30 AwayDay 2005 Slide No 31