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[1] H. Alle, A. Roth and J. R.P. Geiger "Energy-Efficient Action Potentials in Hippocampal Mossy Fibers" Science doi= 10.1126/science.1174331 325 (5946) pp. 1405-1408 http://www.sciencemag.org/cgi/reprint/325/5946/1405.pdf (Sept 2009) - Energy used in a neuron

[2] T. A. Bekinschtein "Classical conditioning in the vegetative and minimally conscious state" Nature Neuroscience doi= 10.1038/nn.2391 12 pp. 1343-1349 (2009) - readiness potential

[3] D.J. Bennett, J.M. Hollerbach, Y. Xu and I.W. Hunter "Time-varying stiffness of human elbow joint during cyclic voluntary movement" Experimental Brain Research doi= 10.1007/BF02259118 88 pp. 433-442 http:Bennett1992.pdf (1992) (UR Call Periodical 612.805)

[4] Bizzi, Accornero, Chapple and Hogan "Arm trajectory formation in monkeys" Experimental brain research 46 pp. 139-143 (1982) (UR Call Folio Periodical--612.805)

[5] S.J. Blakemore, D.M. Wolpert and C.D. Frith "Why can't you tickle yourself?" NeuroReport 11 (11) pp. 11-15 http://blg.eng.cam.ac.uk/t/pub/Public/Wolpert/Publications/BlaWolFri00.pdf (2000)

[6] S. Blakemore, C. D. Frith and D. M. Wolpert "The cerebellum is involved in predicting the sensory consequences of action" Neuroreport 12 (9) pp. 1879-1884 http://blg.eng.cam.ac.uk/t/pub/Public/Wolpert/Publications/BlaFriWol01.pdf (2001)

We used H215O PET to examine neural responses to parametrically varied degrees of discrepancy between the predicted and actual sensory consequences of movement. Subjects used their right hand to move a robotic arm. The motion of this robotic arm determined the position of a second foam-tipped robotic arm which made contact with the subject's left palm. Using this robotic interface computer controlled delays were introduced between the movement of the right hand and the tactile stimulation on the left. Activity in the right lateral cerebellar cortex showed a positive correlation with delay. These results suggest the cerebellum is involved in signalling the sensory discrepancy between the predicted and actual sensory consequences of movements.

[7] Bower and Beeman "The Book of Genesis" Springer (1997)

[8] D. J. Cannon "Experiments with a target-threshold control theory model for deriving Fitts' Law parameters for human-machine systems" IEEE T. Systems Man and Cybernetics 24 (8) pp. 1089-1098 (1994)

[9] W.J. Chen and R.E. Poppele "Small-signal analysis of response of mammalian muscle spindles with fusimotor stimulation and a comparison with large signal responses" J. Neurophysiology 41 (1) pp. 15-27 (Jan 1978) (UR Call Periodical--591.18)

[10] G. Courtine and e. al. "Transformation of nonfunctional spinal circuits into functional states after the loss of brain input" Nature Neuroscience doi= 10.1038/nn.2401 12 pp. 1333-1342 (2009) - spinal locomotion and central pattern generation

[11] T. Flash and T. J. Sejnowski "Computational Approaches to Motor Control" Current Opinion in Neurobiology 11 pp. 655-662 http://papers.cnl.salk.edu/PDFs/Computational%20Approaches%20to%20Motor%20Control%202001-3052.pdf (2001)

[12] P. Haggard and A. Wing "Coordinated responses following mechanical perturbation of the arm during prehension" Experimental Brain Research 102 (483-494) (1995) (UR Call periodical folio--612.805 )

We have investigated how the control of hand transport and of hand aperture are coordinated in prehensile movements by delivering mechanical perturbations to the hand transport component and looking for coordinated adjustments in hand aperture. An electric actuator attached to the subject's right arm randomly pulled the subject backwards away from the target or pushed them towards it during a quarter of the experimental trials. A compensatory adjustment of hand aperture followed the immediate mechanical effects of the perturbation of hand transport. The adjustment appeared to return the subject towards a stereotyped spatial relation between hand aperture and hand transport. These spatial patterns suggest how the two components may be coordinated during prehension. A simple model of this coordination based on coupled position feedback systems is presented.

[13] C. M. Harris and D. M. Wolpert "Signal-dependent noise determines motor planning" Nature doi= 10.1038/29528 pp. 780-784 (1998)

When we make saccadic eye movements or goal-directed arm movements there is an infinite number of possible trajectories that the eye or arm could take to reach the target. However humans show highly stereotyped trajectories in which velocity profiles of both the eye and hand are smooth and symmetric for brief movements. Here we present a unifying theory of eye and arm movements based on the single physiological assumption that the neural control signals are corrupted by noise whose variance increases with the size of the control signal. We propose that in the presence of such signal-dependent noise the shape of a trajectory is selected to minimize the variance of the final eye or arm position. This minimum-variance theory accurately predicts the trajectories of both saccades and arm movements and the speed/accuracy trade-off described by Fitt's law. These profiles are robust to changes in the dynamics of the eye or arm as found empirically. Moreover the relation between path curvature and hand velocity during drawing movements reproduces the empirical 'two-thirds power law'. This theory provides a simple and powerful unifying perspective for both eye and arm movement control.

[14] Z. Hasan "A model of spindle afferent response to muscle stretch" J Neurophysiol 49 (4) pp. 989-1006 (1983)

[15] H. Hatze "A myocybernetic control model of Skeletal Muscle" Biological Cybernetics 25 pp. 103-119 (1977) (UR Call Folio Periodical --003.505)

[16] H. Hatze "Analysis of stretch responses of a myocybernetic model muscle-fibe" Biological Cybernetics 39 (3) pp. 165-170 (1981) (UR Call Folio Periodical --003.505)

[17] A.V. Hill "The Heat of shortening and the dynamic constants of muscle" Proc. Royal Society B126 pp. 399-420 (1938)

[18] A.V. Hill "First and last experiments in muscle mechanics" Cambridge University Press (1970 )

[19] J. Houk and W. Simon "Response of Golgi tendon organs to forces applied to muscle tendon" J. Neurophysiology 30 pp. 1466-1481 (1967) (UR Call Periodical--591.18)

[20] J. Houk, W. Rymer and P. Crago "Dependence of dynamic response of spindle receptors on muscle length and velocity" J. Neurophysiology 44 (1) pp. 143-166 (July 1981) (UR Call Periodical --591.18)

[21] E.M. Izhikevich "Simple Model of Spiking Neurons" IEEE T. on Neural Networks doi= 10.1109/TNN.2003.820440 14 (6) (November 2003)

[22] E.M. Izhikevich "Simple Model of Spiking Neurons" IEEE T. on Neural Networks doi= 10.1109/TNN.2003.820440 14 (6) (November 2003)

[23] E.M. Izhikevich "Which model to use for cortical spiking neurons?" IEEE T. on Neural Networks doi= 10.1109/TNN.2004.832719 15 (5) pp. 1063 - 1070 (2004)

[24] G.C. Joyce and P.M.H. Rack "Isotonic lengthening and shortening movements of cat soleus muscle" J. Physiol. 204 pp. 475-491 (1969)

[25] R. E. Kearney, R. B. Stein and L. Parameswaran "Identification of Intrinsic and Reflex Contributions to Human Ankle Stiffness Dynamics" IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING doi= 10.1109/10.581944 44 (6) http://ieeexplore.ieee.org/iel1/10/12629/00581944.pdf (June 1997)

We have examined dynamic stiffness at the human ankle using position perturbations which were designed to provide a wide-bandwidth input with low average velocity. A parallel-cascade, nonlinear system identification technique was used to separate overall stiffness into intrinsic and reflex components. Intrinsic stiffness was described by a linear, secondorder system similar to that demonstrated previously. Reflex stiffness dynamics were more complex, comprising a delay, a unidirectional rate-sensitive element and then lowpass dynamics. Reflex mechanisms were found to be most important at frequencies of 5-10 Hz. The gain and dynamics of reflex stiffness varied strongly with the parameters of the perturbation, the gain decreasing as the mean velocity of the perturbation increased. Under some conditions, torques generated by reflex mechanisms were of the same magnitude as those from intrinsic mechanisms. It is concluded that reflex stiffness can be large enough to be important functionally, but that its effects will depend strongly upon the particular conditions.

[26] A. M. Krylow, T. G. Sandercock and W.Z. Rymer "The handbook of brain theory and neural networks" Muscle Models MIT Press , Michael A. Arbib (Eds.) , Michael A. Arbib (Eds.) part 3 pp. 609-613 (1995) (UR Call FOLIO--612.82-HAN)

[27] A. D. Kuo "The relative roles of feedforward and feedback in the control of rhythmic movements" Motor Control 6 pp. 129-145 http://www-personal.umich.edu/~artkuo/Papers/MC02.pdf (2002) - A more reasoned explanation of central pattern generators, the neurons become a sensory filter

[28] T. A. McMahon "Muscles reflexes and locomotion" Princeton N.J. : Princeton University Press , isbn 0691083223 (1984) (UR Call 591.47-MAC)

[29] R.C. Miall and J. Jackson "Adaptation to visual feedback delays in manual tracking - evidence against the Smith Predictor model of human visually guided action" Exp. Brain Res. 172 pp. 77-84 http://prism.bham.ac.uk/pdf_files/Miall_Jackson_EBR_2006.pdf (2006)

[30] R.C. Miall, D.J. Weir, D.M. Wolpert and J.F. Stein "Is the Cerebellum a Smith Predictor?" Journal of Motor Behavior 25 (3) pp. 203-216 http://prism.bham.ac.uk/pdf_files/SmithPred_93.PDF (1993)

The motor system may use intemal predictive models of the motor apparatus to achieve better control than would be possible by negative feedback. Several theories have proposed that the cerebellum may form these predictive representations, In this article, we review these theories and try to unify them by reference to an engineering control model known as a Smith Predictor. We suggest that the cerebellum forms two types of internal model. One model is a forward predictive model of the motor apparatus (e.g. , limb and muscle), providing a rapid prediction of the sensory consequences of each movement. The second model is of the time delays in the control loop (due to receptor and effector delays, axona] conductances, and cognitive processing delays). This model delays a copy of the rapid prediction so that it can be compared in temporal register with actual sensory feedback from the movement. The result of this comparison is used both to correct for errors in performance and as a training signal to learn the first model We discuss evidence that the cerebellum could form both of these models and suggest that the cerebellum may hold at least two separate Smith Predictors. One, in the lateral cerebellum, would predict the movement outcome in visual, egocentric, or peripersonaJ coordinates. Another, in the intermediate cerebellum, would predict the consequences in motor coordinates. Generalization of the Smith Predictor theory is discussed in ]ight of cerebellar involvement in nonmotor control systems, including autonomic functions and cognition

[31] M.M. Mirbagheri, R.A. Harvey and W.Z. Rymer "Mechanical properties of the elbow joint in spastic hemiparetic stroke subjects" Proceedings of the 2nd Joint EMBS/BMES Conference pp. 2449-2450 (2002)

[32] M.M. Mirbagheri, R.A. Harvey, D. Chen and W.Z. Rymer "Identification of reflex and intrinsic mechanical properties in stroke and spinal cord injury" Proceedings of the 25' Annual Internatinal Conference of the IEEE EMBS pp. 1495-1498 (2003)

We used system identification techniques to characterize the mechanical abnormalities associated with spasticity and to identify the contribution of intrinsic and reflex stiffness to these abnormalities. Modulation of intrinsic and reflex stiffness of elhow flexor muscles in hemiparetic stroke, spinal cord injured (SCI), and normal subjects was studied by applying perturbations to the elbow at different initial joint angles with subjects' muscles relaxed. We found that intrinsic stiffness was larger in SCI than normal subjects, whereas it was within normal range in stroke arms. Reflex stiffness was similar in spastic SCI and stroke subjects and was significantly larger than in normal subjects. However, the reflex relative contribution to overall joint stiffness was smaller in SCI than stroke group due to greater increase in intrinsic stiffness in SCI subjects. Both reflex and intrinsic stiffness were strongly position dependent; they both increased with increasing elbow extension but reflex stiffness declined at full extension. The mechanical properties of the contralateral arms in stroke subjects were not normal; reflex stiffness was larger and intrinsic stiffness was lower. These findings demonstrate that although increased reflex stiffness is a common mechanical abnormality in SCI and stroke the major mechanical abnormalities of the spastic elbow are enhanced intrinsic contribution in the SCI subjects and increased reflex contribution in stroke subjects. Moreover, the findings suggest that the contralateral side of stroke subjects is also affected and cannot be used as reliable

[33] M.M. Mirbagheri, L. Alibiglou, M. Thajchayapong and W.Z. Rymer "Muscle and reflex changes with joint angle in Hempiparetic stroke." J Neuroeng Rehabil doi= 10.1186/1743-0003-5-6 5 (1) pp. 1-11 http://www.jneuroengrehab.com/content/pdf/1743-0003-5-6.pdf (2008)

[34] F.A. Mussa-Ivaldi "Geometrical principles in motor control" The handbook of brain theory and neural networks 2nd edition mit press pp. 478-482 (2002)

[35] Partridge and Benton "Handbook of physiology : a critical comprehensive presentation of physiological knowledge and concepts- Section 1 The nervous system" Muscle the motor , Vernon B. Brooks (Eds.) , Vernon B. Brooks (Eds.) () (UR Call Folio book 612-HAN 1.2.1)

[36] Penfield and Rasmussen "The Cerebral Cortex of Man" New York: Macmillan (1950) - The first homonculus (UR Call 612.825-PEN)

[37] A. Prochazka, D. Gillard and D.J. Bennett "Implications of positive feedback in the control of movement" Journal of Neurophysiology 77 (6) pp. 3237-3251 http://www.ualberta.ca/~aprochaz/pdfs/1997%20Prochazka%20pos%20ff%202.pdf (1997) (UR Call Folio Periodical -- 591.18 V. 61)

In the absence of sensory input the central nervous system can generate a rhythmical pattern of coordinated activation of limb muscles. Contracting muscles have spring-like properties. If synergistic muscles are co-activated in the right way, sustained locomotion can occur. What is the role of sensory input in this scheme? In this chapter we first discuss the implications of positive force feedback control in hindlimb extensor reflexes in the cat. We then raise the question of whether the sensory-evoked responses, which are modest in size and quite delayed in the stance phase, contribute to any significant extent. A locomotor model is used to show that when centrally generated activation levels are low, stretch reflexes can be crucial. However, when these levels are higher, stretch reflexes have a less dramatic role. The more important role for sensory input is probably in mediating higher level control decisions.

[38] A. Prochazka and M. Gorassini "Ensemble firing of muscle afferents recorded during normal locomotion in cats" Journal of Physiology 507 (1) pp. 293-304 (1998)

[39] A. Prochazka and M. Gorassini "Models of ensemble firing of muscle spindle afferents recorded during normal locomotion in cats" Journal of Physiology 507 (1) pp. 277-291 (1998)

[40] Rack and Westbury "The effects of length and stimulus rate on tension in the isometric cat soleus muscle" J. Physiology 204 pp. 443-460 (1969) (UR Call Periodical 591.0597-473)

[41] S. Schaal "Arm and hand movement control" The handbook of brain theory and neural networks 2nd edition mit press pp. 110-113 http://www-clmc.usc.edu/publications/S/schaal-HBTNN2002b.pdf (2002)

[42] E. J. Hwang and R. Shadmehr "Internal Models of Limb Dynamics and the Encoding of Limb State" J Neural Eng. 2 (3) pp. S266-S278 (September 2005) - Describes the Hasan muscle spindle model

[43] G. Vines "The Hand in your head" New Scientist pp. 42-45 (8 May 1999)

[44] P. Viviania and C. Terzuolo "Trajectory determines movement dynamics" Neuroscience 7 (2) pp. 431-437 (Feburary 1982)

The relation between between figural and kinematic aspects of movement was studied in handwriting and drawing. It was found that, throughout the movement, the tangential velocity. V is proportional to the radius of curvature r of the trajectory: V= kr, or, equivalently, that the angular velocity is constant: dalpha(t)/dt = K. However, the constant k generally takes several distinct values during the movement, the changes being abrupt. These changes suggest a clear segmentation of the movement into units of action which overlap but do not coincide with the figural units as defined by the discontinuities of the movement (cuspids, points of inflection). This organisational principle holds even when movements are mechanically constrained or are executed under strict visuo-motor guidance. Moreover, the segmentation of a given trajectory is invariant with respect to the total duration of the movement. A tentative interpretation of the principle is proposed which results from the assumption that the actual movement is produced as a continuous approximation to an intended movement, and that the well known relationship between movement speed and extent in rectilinear trajectories (Fitts' law) also applies to such continuous approximation.

[45] Wierzbicka, Wiegner and Shahani "Role of agonist and antagonist muscles in fast arm movemens in man" Experimental brain research 63 pp. 331-340 (1986) - (Introduction has a summary of triphasic muscle response) (UR Call Folio Periodical--612.805)

[46] A.M.and Turton Wing and C Fraser "Grasp size and accuracy of approach in reaching" J Mot. Behaviour 18 (1) pp. 245-260 http://www.symon.bham.ac.uk/publications/Papers1/GraspPap.pdf (Sept 1986)

[47] A.M. Wing and J.R. Flanagan "Anticipating Dynamic Loads in Handling Objects" Proceedings of the ASME Dynamic Systems and Control Division ASME DSC-Vol 64 pp. 139-143 http://www.symon.bham.ac.uk/publications/wng_fla_ASME98.pdf (1998)

[48] "Multiple Muscle Systems: Biomechanics and movement organisation" Chapter 5: Hill Based Muscle Models: A system Engineering perspective Springer Verlag (1990)

[49] D. M. Wolpert, R.C. Miali and M. Kawato "Internal models in the cerebellum" Trends in Cognative Science 2 pp. 338 (1998)

[50] Zangemeister, Lehman and Stark "Simulation of head movement trajectories: model and fit to main sequence" Biological cybernetics 41 pp. 19-32 (1981) (UR Call Folio Periodical --003.505)