
Cerebellar Learning
- 1st Edition, Volume 210 - June 6, 2014
- Imprint: Elsevier
- Editor: Narender Ramnani
- Language: English
- Hardback ISBN:9 7 8 - 0 - 4 4 4 - 6 3 3 5 6 - 9
- eBook ISBN:9 7 8 - 0 - 4 4 4 - 6 3 4 2 6 - 9
Progress in Brain Research is the most acclaimed and accomplished series in neuroscience, firmly established as an extensive documentation of the advances in contemporary brain res… Read more

Purchase options

Institutional subscription on ScienceDirect
Request a sales quoteProgress in Brain Research is the most acclaimed and accomplished series in neuroscience, firmly established as an extensive documentation of the advances in contemporary brain research. The volumes, some of which are derived from important international symposia, contain authoritative reviews and original articles by invited specialists. The rigorous editing of the volumes assures that they will appeal to all laboratory and clinical brain research workers in the various disciplines: neuroanatomy, neurophysiology, neuropharmacology, neuroendocrinology, neuropathology, basic neurology, biological psychiatry, and the behavioral sciences.
This volume, The Cerebellum and Memory Formation: Structure, Computation and Function, covers topics including feedback control of cerebellar learning; cortico-cerebellar organization and skill acquisition; cerebellar plasticity and learning in the oculomotor system, and more.
- Leading authors review the state-of-the-art in their field of investigation, and provide their views and perspectives for future research
- The volume reflects current thinking about the ways in which the cerebellum can engage in learning, and the contributors come from a variety of research fields
- The chapters express perspectives from different levels of analysis that range from molecular and cellular mechanisms through to long-range systems that allow the cerebellum to communicate with other brain areas
This volume is aimed at neuroscientists who are interested in the cerebellar function and its relationships with learning, memory and cognition.
Chapter 1: Long-Term Depression as a Model of Cerebellar Plasticity
- Abstract
- 1 A Historical Overview of LTD Studies
- 2 Molecular Mechanisms of LTD
- 3 Roles of LTD in Motor Learning
- 4 Significance of LTD in Cerebellar Neural Network
- 5 LTD Versus Learning Mismatch
- 6 Perspectives
- Acknowledgments
Chapter 2: The Organization of Plasticity in the Cerebellar Cortex: From Synapses to Control
- Abstract
- 1 Introduction
- 2 Plasticity in the Granular Layer
- 3 Mossy Fiber–Granule Cell LTP and LTD
- 4 Plasticity in the Molecular Layer
- 5 An Integrated View of Cerebellar Cortical Plasticity
- 6 Cerebellar Cortical Plasticity and Timing
- 7 Integration of Plasticity in the Cerebellar Cortex and Nuclei
- 8 Cerebellar Plasticity in Learning and Control
- 9 Conclusions
- Acknowledgments
Chapter 3: Questioning the Cerebellar Doctrine
- Abstract
- 1 The Cerebellar Doctrine and Its Three Pillars
- 2 The First Pillar: The Sole Cerebellar Function Is to Control Motor Behavior
- 3 The Second Pillar: Inputs Converge Only at the Level of Purkinje Cells
- 4 The Third Pillar: Depression at the Parallel Fiber to Purkinje Cell Synapse Is the Molecular Substrate of Cerebellar Learning
- 5 Concluding Remarks
Chapter 4: Distribution of Neural Plasticity in Cerebellum-Dependent Motor Learning
- Abstract
- 1 Introduction
- 2 Cerebellum-Dependent Learning—Eyeblink and NMR Conditioning as Behavioral Models for Analysis
- 3 Lesion Studies Reveal that NMR Conditioning Depends upon Cerebellar Compartments with C1 and C3 Cortical Zones in Lobule HVI
- 4 Inactivation Experiments Reveal Essential Roles for the Cerebellar Nuclei and Inferior Olive in the Acquisition of NMR and Eyeblink Conditioning
- 5 Inferior Olive Function in NMR and Eyeblink Conditioning
- 6 Cerebellar Cortex Function in NMR and Eyeblink Conditioning
- 7 Distribution of Plasticity at Cerebellar Cortical and Cerebellar Nuclear, or Brainstem, Levels
- 8 Cortical Plasticity in NMR and Eyeblink Conditioning
- 9 Conclusions
- Acknowledgment
Chapter 5: Feedback Control of Learning by the Cerebello-Olivary Pathway
- Abstract
- 1 Feedback is Essential for Learning
- 2 Anticipating Consequences
- 3 Classical Conditioning
- 4 The Cerebellar Microcomplex
- 5 Classical Conditioning Requires the Cerebellum
- 6 The Nucleo-Olivary Pathway and Negative Feedback
- 7 Reaching Equilibrium
- 8 Back to Behavior
- 9 Feedback, Anticipation, and Nucleo-Olivary Inhibition
- 10 Broadening the Perspective
Chapter 6: Cerebellum-Dependent Motor Learning: Lessons from Adaptation of Eye Movements in Primates
- Abstract
- 1 Introduction
- 2 Adaptation of the VOR
- 3 Short-Term Saccadic Adaptation
- 4 Smooth Pursuit Adaptation
- 5 Oculomotor Cerebellum—An Overview
- 6 Floccular Complex
- 7 Oculomotor Vermis
- 8 Complex Spike Activity During STSA and SPA
- 9 Conclusions
Chapter 7: Decorrelation Learning in the Cerebellum: Computational Analysis and Experimental Questions
- Abstract
- 1 Introduction
- 2 Implementation of Learning Rule
- 3 Properties of Learning Rule
- 4 Sensory Prediction
- 5 Motor Control
- 6 Future Directions
- Appendix Derivation of Supervised-Learning Rule
- Acknowledgments
Chapter 8: Modeling the Evolution of the Cerebellum: From Macroevolution to Function
- Abstract
- 1 Cerebellum, Learning, and Human Evolution
- 2 Evolutionary Neuroscience and Its Adoption of the Cerebellum
- 3 Comparative Studies of Cerebellar Connectivity
- 4 Macroevolutionary Studies of the Cerebellum
- 5 How Can Macroevolutionary Studies Contribute to Our Understanding of Cerebellar Function?
- 6 Summary
- Acknowledgment
Chapter 9: Cerebellar and Prefrontal Cortex Contributions to Adaptation, Strategies, and Reinforcement Learning
- Abstract
- 1 Introduction
- 2 The Cerebellum and Error-Based Learning
- 3 Computational Models of Sensorimotor Adaptation
- 4 Multiple Learning Mechanisms in Sensorimotor Adaptation
- 5 Strategy Use During Sensorimotor Adaptation
- 6 Cerebellar and Neocortical Contributions to Sensorimotor Adaptation
- 7 Systems Interaction in Sensorimotor Learning
- 8 Cerebellum and Sensorimotor Learning: Beyond Adaptation
- 9 Conclusions
- Acknowledgments
Chapter 10: Automatic and Controlled Processing in the Corticocerebellar System
- Abstract
- 1 Dual Systems, Skills, and Habits
- 2 Control Theory
- 3 The Cerebellum and Forward Models
- 4 Cognitive Habits
- 5 Conclusion
- Acknowledgment
- Edition: 1
- Volume: 210
- Published: June 6, 2014
- No. of pages (Hardback): 312
- No. of pages (eBook): 312
- Imprint: Elsevier
- Language: English
- Hardback ISBN: 9780444633569
- eBook ISBN: 9780444634269
NR
Narender Ramnani
Professor Ramnani received his PhD in Behavioural Neuroscience from the Department of Anatomy and Developmental Biology at University College London (UCL). He also holds a BSc (Hons) in Psychology from Birkbeck College London, and an MSc in Neuroscience from the Institute of Psychiatry (London). His postdoctoral training took place at the Wellcome Trust Centre for Neuroimaging (Institute of Neurology, UCL), the University Laboratory of Physiology and the Centre for fMRI of the Brain (FMRIB) at the University of Oxford. After his postdoctoral training he was appointed to a Lectureship in the Department of Psychology, Royal Holloway, University of London, where he is Professor of Neuroscience.
Cerebellar learning and plasticity are central to Professor Ramnani’s core research interests. He has attempted to integrate behavior, neurobiology and theory to understand cerebellar contributions to learning. This approach began as a PhD student when he studied a simple, cerebellar-dependent form of motor learning in animals. Since then his interests have expanded to include the roles of frontal lobe areas in cognition and action. His work has also built on the finding that the cerebellum communicates with multiple areas in the frontal lobe that include not only the cortical motor areas, but also the prefrontal cortex. His research group has used neuroimaging methods to understand the anatomical organization and evolution of prefrontal-cerebellar circuits, and the manner in which they communicate to support to the automation of cognitive operations. Professor Ramnani’s work is supported by research grants from a number of sources including the UK Biotechnology and Biological Sciences Research Council (BBSRC). He has published in a range of specialist and high profile journals including Nature Neurscience, Nature Reviews Neuroscience, and the Journal of Neuroscience. For the last ten years he has been actively engaged in promoting UK neuroscience as a Council and Committee member of the British Neuroscience Association.