D’Hooge, Rudi Van Dam, Debby Franck, Frieda Gieselmann, Volkmar and De Deyn, Peter P 2001. Hyperactivity, neuromotor defects, and impaired learning and memory in a mouse model for metachromatic leukodystrophy. Brain Research, Vol. 907, Issue. 1-2, p. 35.
Schultz, Wolfram and Dickinson, Anthony 2000. Neuronal Coding of Prediction Errors. Annual Review of Neuroscience, Vol. 23, Issue. 1, p. 473.
Kitazawa, Shigeru 2002. Optimization of goal-directed movements in the cerebellum: a random walk hypothesis. Neuroscience Research, Vol. 43, Issue. 4, p. 289.
Svensson, P. and Ivarsson, M. 1999. Short-lasting conditioned stimulus applied to the middle cerebellar peduncle elicits delayed conditioned eye blink responses in the decerebrate ferret. European Journal of Neuroscience, Vol. 11, Issue. 12, p. 4333.
Lewis, Kerrie P. and Barton, Robert A. 2004. Playing for keeps. Human Nature, Vol. 15, Issue. 1, p. 5.
Rădulescu, Anca R. and Hannon, Emily R. 2017. Applying fMRI complexity analyses to the single subject: a case study for proposed neurodiagnostics. Neurocase, Vol. 23, Issue. 2, p. 120.
Park, Jaebum Lewis, Mechelle M. Huang, Xuemei and Latash, Mark L. 2013. Effects of olivo-ponto-cerebellar atrophy (OPCA) on finger interaction and coordination. Clinical Neurophysiology, Vol. 124, Issue. 5, p. 991.
Doya, K. 1999. What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?. Neural Networks, Vol. 12, Issue. 7-8, p. 961.
Schultz, Wolfram 2002. Getting Formal with Dopamine and Reward. Neuron, Vol. 36, Issue. 2, p. 241.
Schutter, Erik De and Maex, Reinoud 1996. The cerebellum: cortical processing and theory. Current Opinion in Neurobiology, Vol. 6, Issue. 6, p. 759.
Gasbarri, A Pompili, A Pacitti, C and Cicirata, F 2003. Comparative effects of lesions to the ponto-cerebellar and olivo-cerebellar pathways on motor and spatial learning in the rat. Neuroscience, Vol. 116, Issue. 4, p. 1131.
Bazyan, A.S Zhulin, V.V Karpova, M.N Klishina, N.Y and Glebov, R.N 2001. Long-term reduction of benzodiazepine receptor density in the rat cerebellum by acute seizures and kindling and its recovery 6 months later by a pentylenetetrazole challenge. Brain Research, Vol. 888, Issue. 2, p. 212.
van der Smagt, Patrick 2000. Benchmarking cerebellar control. Robotics and Autonomous Systems, Vol. 32, Issue. 4, p. 237.
Gruart, A. and Delgado-García, J. M. 2007. Activity-dependent changes of the hippocampal CA3?CA1 synapse during the acquisition of associative learning in conscious mice. Genes, Brain and Behavior, Vol. 6, Issue. s1, p. 24.
Smits-Bandstra, Sarah and De Nil, Luc F. 2007. Sequence skill learning in persons who stutter: Implications for cortico-striato-thalamo-cortical dysfunction. Journal of Fluency Disorders, Vol. 32, Issue. 4, p. 251.
D'Hooge, R Hartmann, D Manil, J Colin, F Gieselmann, V and De Deyn, P.P 1999. Neuromotor alterations and cerebellar deficits in aged arylsulfatase A-deficient transgenic mice. Neuroscience Letters, Vol. 273, Issue. 2, p. 93.
Najafi, Farzaneh Giovannucci, Andrea Wang, Samuel S-H and Medina, Javier F 2014. Coding of stimulus strength via analog calcium signals in Purkinje cell dendrites of awake mice. eLife, Vol. 3,
Walton, James C. Schilling, Karl Nelson, Randy J. and Oberdick, John 2012. Sex-Dependent Behavioral Functions of the Purkinje Cell-Specific Gαi/o Binding Protein, Pcp2(L7). The Cerebellum, Vol. 11, Issue. 4, p. 982.
Ivancevic, Vladimir G. 2010. Nonlinear complexity of human biodynamics engine. Nonlinear Dynamics, Vol. 61, Issue. 1-2, p. 123.
Hausknecht, Matthew Li, Wen-Ke Mauk, Michael and Stone, Peter 2017. Machine Learning Capabilities of a Simulated Cerebellum. IEEE Transactions on Neural Networks and Learning Systems, Vol. 28, Issue. 3, p. 510.
Jaskowski, Piotr and Verleger, Rolf 2000. Attentional Bias toward Low-Intensity Stimuli: An Explanation for the Intensity Dissociation between Reaction Time and Temporal Order Judgment?. Consciousness and Cognition, Vol. 9, Issue. 3, p. 435.
Barto, Andrew G. Fagg, Andrew H. Sitkoff, Nathan and Houk, James C. 1999. A Cerebellar Model of Timing and Prediction in the Control of Reaching. Neural Computation, Vol. 11, Issue. 3, p. 565.
Teddy, S.D. Lai, E.M.-K. and Quek, C. 2007. Hierarchically Clustered Adaptive Quantization CMAC and Its Learning Convergence. IEEE Transactions on Neural Networks, Vol. 18, Issue. 6, p. 1658.
Hesslow, Germund Svensson, Pär and Ivarsson, Magnus 1999. Learned Movements Elicited by Direct Stimulation of Cerebellar Mossy Fiber Afferents. Neuron, Vol. 24, Issue. 1, p. 179.
Sugihara, Izumi Brown, Kerry M. and Ascoli, Giorgio A. 2013. New insights on vertebrate olivo-cerebellar climbing fibers from computerized morphological reconstructions. BioArchitecture, Vol. 3, Issue. 2, p. 38.
Gross, H.-M. Heinze, A. Seiler, T. and Stephan, V. 1999. Generative character of perception: a neural architecture for sensorimotor anticipation. Neural Networks, Vol. 12, Issue. 7-8, p. 1101.
Sekerková, Gabriella Ilijic, Ema Mugnaini, Enrico and Baker, James F. 2005. Otolith organ or semicircular canal stimulation induces c-fos expression in unipolar brush cells and granule cells of cat and squirrel monkey. Experimental Brain Research, Vol. 164, Issue. 3, p. 286.
Gould, T.J Rowe, W.B Heman, K.L Mesches, M.H Young, D.A Rose, G.M and Bickford, P.C 2002. Effects of hippocampal lesions on patterned motor learning in the rat. Brain Research Bulletin, Vol. 58, Issue. 6, p. 581.
Fielding, Joanne Corben, Louise Cremer, Phillip Millist, Lynette White, Owen and Delatycki, Martin 2010. Disruption to higher order processes in Friedreich ataxia. Neuropsychologia, Vol. 48, Issue. 1, p. 235.
Ebadzadeh, M. and Darlot, C. 2003. Cerebellar learning of bio-mechanical functions of extra-ocular muscles: modeling by artificial neural networks. Neuroscience, Vol. 122, Issue. 4, p. 941.
Hofstötter, Constanze Mintz, Matti and Verschure, Paul F. M. J. 2002. The cerebellum in action: a simulation and robotics study. European Journal of Neuroscience, Vol. 16, Issue. 7, p. 1361.
Teddy, S.D. Quek, C. and Lai, E.M.-K. 2008. PSECMAC: A Novel Self-Organizing Multiresolution Associative Memory Architecture. IEEE Transactions on Neural Networks, Vol. 19, Issue. 4, p. 689.
Kistler, Werner M. 2001. Time-slicing: A model for cerebellar function based on synchronization, reverberation, and time windows. Neurocomputing, Vol. 38-40, p. 1367.
LUQUE, NICETO R. GARRIDO, JESÚS A. RALLI, JARNO LAREDO, JUANLU J. and ROS, EDUARDO 2012. FROM SENSORS TO SPIKES: EVOLVING RECEPTIVE FIELDS TO ENHANCE SENSORIMOTOR INFORMATION IN A ROBOT-ARM. International Journal of Neural Systems, Vol. 22, Issue. 04, p. 1250013.
Shimansky, Yury P. 2009. Biologically plausible learning in neural networks: a lesson from bacterial chemotaxis. Biological Cybernetics, Vol. 101, Issue. 5-6, p. 379.
Dam, Gregory Kording, Konrad Wei, Kunlin and Gribble, Paul L. 2013. Credit Assignment during Movement Reinforcement Learning. PLoS ONE, Vol. 8, Issue. 2, p. e55352.
Dordevic, G.S. Rasic, M. Kostic, D. and Potkonjak, V. 2000. Representation of robot motion control skill. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), Vol. 30, Issue. 2, p. 219.
Gancarz, Gregory and Grossberg, Stephen 1999. A neural model of saccadic eye movement control explains task-specific adaptation. Vision Research, Vol. 39, Issue. 18, p. 3123.
Erni, T. and Dietz, V. 2001. Obstacle avoidance during human walking: learning rate and cross-modal transfer. The Journal of Physiology, Vol. 534, Issue. 1, p. 303.
Anderson, Carl M. Lowen, Steven B. and Renshaw, Perry F. 2006. Emotional task-dependent low-frequency fluctuations and methylphenidate: Wavelet scaling analysis of 1/f-type fluctuations in fMRI of the cerebellar vermis. Journal of Neuroscience Methods, Vol. 151, Issue. 1, p. 52.
Brown, Ian E. and Bower, James M. 2001. Congruence of mossy fiber and climbing fiber tactile projections in the lateral hemispheres of the rat cerebellum. The Journal of Comparative Neurology, Vol. 429, Issue. 1, p. 59.
Luque, N. R. Garrido, J. A. Carrillo, R. R. Coenen, Olivier J.-M D. and Ros, E. 2011. Cerebellarlike Corrective Model Inference Engine for Manipulation Tasks. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), Vol. 41, Issue. 5, p. 1299.
Lalonde, R. and Strazielle, C. 2007. Brain regions and genes affecting postural control. Progress in Neurobiology, Vol. 81, Issue. 1, p. 45.
Ivancevic, Vladimir G. and Ivancevic, Tijana T. 2010. Dynamics and Control of Humanoid Robots: A Geometrical Approach. Paladyn, Journal of Behavioral Robotics, Vol. 1, Issue. 4,
Tanaka, Hirokazu Homma, Kazuhiro and Imamizu, Hiroshi 2011. Physical delay but not subjective delay determines learning rate in prism adaptation. Experimental Brain Research, Vol. 208, Issue. 2, p. 257.
Yeo, Christopher H and Hesslow, Germund 1998. Cerebellum and conditioned reflexes. Trends in Cognitive Sciences, Vol. 2, Issue. 9, p. 322.
Ebadzadeh, M. Tondu, B. and Darlot, C. 2005. Computation of inverse functions in a model of cerebellar and reflex pathways allows to control a mobile mechanical segment. Neuroscience, Vol. 133, Issue. 1, p. 29.
Apps, Richard and Garwicz, Martin 2005. Anatomical and physiological foundations of cerebellar information processing. Nature Reviews Neuroscience, Vol. 6, Issue. 4, p. 297.
Steuber, Volker Schultheiss, Nathan W. Silver, R. Angus De Schutter, Erik and Jaeger, Dieter 2011. Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells. Journal of Computational Neuroscience, Vol. 30, Issue. 3, p. 633.
IVANCEVIC, VLADIMIR and SHARMA, SANJEEV 2008. COMPLEXITY IN HUMAN AND HUMANOID BIOMECHANICS. International Journal of Humanoid Robotics, Vol. 05, Issue. 04, p. 679.
Christopoulos, Vassilios N. Leuthold, Arthur C. and Georgopoulos, Apostolos P. 2012. Spatiotemporal neural interactions underlying continuous drawing movements as revealed by magnetoencephalography. Experimental Brain Research, Vol. 222, Issue. 1-2, p. 159.
Fielding, Joanne Clough, Meaghan Beh, Shin Millist, Lynette Sears, Derek Frohman, Ashley N. Lizak, Nathaniel Lim, Jayne Kolbe, Scott Rennaker, Robert L. Frohman, Teresa C. White, Owen B. and Frohman, Elliot M. 2015. Ocular motor signatures of cognitive dysfunction in multiple sclerosis. Nature Reviews Neurology, Vol. 11, Issue. 11, p. 637.
Spratling, M. W. 2017. A predictive coding model of gaze shifts and the underlying neurophysiology. Visual Cognition, p. 1.
Erkelens, Ian M. Thompson, Benjamin Bobier, William R. and Munoz, Doug 2016. Unmasking the linear behaviour of slow motor adaptation to prolonged convergence. European Journal of Neuroscience, Vol. 43, Issue. 12, p. 1553.
Girard, B. and Berthoz, A. 2005. From brainstem to cortex: Computational models of saccade generation circuitry. Progress in Neurobiology, Vol. 77, Issue. 4, p. 215.
Delgado-García, José M. and Gruart, A. 2005. Firing activities of identified posterior interpositus nucleus neurons during associative learning in behaving cats. Brain Research Reviews, Vol. 49, Issue. 2, p. 367.
Gojkovic, Zoran Ivancevic, Tijana and Jovanovic, Bojan 2017. A two-phase computational biomechanics model for successful rehabilitation after hip and knee surgery. Nonlinear Dynamics,
Silkis, Isabella 2000. Interrelated modification of excitatory and inhibitory synapses in three-layer olivary-cerebellar neural network. Biosystems, Vol. 54, Issue. 3, p. 141.
Carvalho, Regiane Luz and Almeida, Gil Lúcio 2008. Controle postural em indivíduos portadores da síndrome de Down: revisão de literatura. Fisioterapia e Pesquisa, Vol. 15, Issue. 3, p. 304.
MIER, HANNEKE I. and PETERSEN, STEVE E. 2002. Role of the Cerebellum in Motor Cognition. Annals of the New York Academy of Sciences, Vol. 978, Issue. 1 THE CEREBELLU, p. 334.
IVANCEVIC, VLADIMIR 2006. LIE–LAGRANGIAN MODEL FOR REALISTIC HUMAN BIODYNAMICS. International Journal of Humanoid Robotics, Vol. 03, Issue. 02, p. 205.
Anastasio, Thomas J. 2001. Input minimization: a model of cerebellar learning without climbing fiber error signals. Neuroreport, Vol. 12, Issue. 17, p. 3825.
Najafi, Farzaneh Giovannucci, Andrea Wang, Samuel S.-H. and Medina, Javier F. 2014. Sensory-Driven Enhancement of Calcium Signals in Individual Purkinje Cell Dendrites of Awake Mice. Cell Reports, Vol. 6, Issue. 5, p. 792.
Inagaki, Keiichiro and Hirata, Yutaka 2017. Computational Theory Underlying Acute Vestibulo-ocular Reflex Motor Learning with Cerebellar Long-Term Depression and Long-Term Potentiation. The Cerebellum, Vol. 16, Issue. 4, p. 827.
Caligiore, Daniele Pezzulo, Giovanni Miall, R. Chris and Baldassarre, Gianluca 2013. The contribution of brain sub-cortical loops in the expression and acquisition of action understanding abilities. Neuroscience & Biobehavioral Reviews, Vol. 37, Issue. 10, p. 2504.
Gao, Fan Latash, Mark L. and Zatsiorsky, Vladimir M. 2004. Neural network modeling supports a theory on the hierarchical control of prehension. Neural Computing and Applications, Vol. 13, Issue. 4, p. 352.
Luque, Niceto R. Garrido, Jesús A. Naveros, Francisco Carrillo, Richard R. D'Angelo, Egidio and Ros, Eduardo 2016. Distributed Cerebellar Motor Learning: A Spike-Timing-Dependent Plasticity Model. Frontiers in Computational Neuroscience, Vol. 10,
Simcock, Gabrielle Kildea, Sue Elgbeili, Guillaume Laplante, David P. Stapleton, Helen Cobham, Vanessa and King, Suzanne 2016. Age-related changes in the effects of stress in pregnancy on infant motor development by maternal report: The Queensland Flood Study. Developmental Psychobiology, Vol. 58, Issue. 5, p. 640.
McLachlan, Neil M. and Wilson, Sarah J. 2017. The Contribution of Brainstem and Cerebellar Pathways to Auditory Recognition. Frontiers in Psychology, Vol. 08,
Caligiore, Daniele Pezzulo, Giovanni Baldassarre, Gianluca Bostan, Andreea C. Strick, Peter L. Doya, Kenji Helmich, Rick C. Dirkx, Michiel Houk, James Jörntell, Henrik Lago-Rodriguez, Angel Galea, Joseph M. Miall, R. Chris Popa, Traian Kishore, Asha Verschure, Paul F. M. J. Zucca, Riccardo and Herreros, Ivan 2017. Consensus Paper: Towards a Systems-Level View of Cerebellar Function: the Interplay Between Cerebellum, Basal Ganglia, and Cortex. The Cerebellum, Vol. 16, Issue. 1, p. 203.
Shim, Vui Ann Ranjit, Chris Stephen Naveen Tian, Bo Yuan, Miaolong and Tang, Huajin 2015. A Simplified Cerebellar Model with Priority-based Delayed Eligibility Trace Learning for Motor Control. IEEE Transactions on Autonomous Mental Development, Vol. 7, Issue. 1, p. 26.
KISTLER, W. M. JEU, M. T. G. ELGERSMA, Y. GIESSEN, R. S. HENSBROEK, R. LUO, C. KOEKKOEK, S. K. E. HOOGENRAAD, C. C. HAMERS, F. P. T. GUELDENAGEL, M. SOHL, G. WILLECKE, K. and ZEEUW, C. I. 2002. Analysis of Cx36 Knockout Does Not Support Tenet That Olivary Gap Junctions Are Required for Complex Spike Synchronization and Normal Motor Performance. Annals of the New York Academy of Sciences, Vol. 978, Issue. 1 THE CEREBELLU, p. 391.
This article reviews models of the cerebellum and motor learning, from the landmark papers by Marr and Albus through those of the present time. The unique architecture of the cerebellar cortex is ideally suited for pattern recognition, but how is pattern recognition incorporated into motor control and learning systems? The present analysis begins with a discussion of exactly what the cerebellar cortex needs to regulate through its anatomically defined projections to premotor networks. Next, we examine various models showing how the microcircuitry in the cerebellar cortex could be used to achieve its regulatory functions. Having thus defined what it is that Purkinje cells in the cerebellar cortex must learn, we then evaluate theories of motor learning. We examine current models of synaptic plasticity, credit assignment, and the generation of training information, indicating how they could function cooperatively to guide the processes of motor learning.
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