Literature DB >> 24849344

Role of plasticity at different sites across the time course of cerebellar motor learning.

Yan Yang1, Stephen G Lisberger2.   

Abstract

Learning comprises multiple components that probably involve cellular and synaptic plasticity at multiple sites. Different neural sites may play their largest roles at different times during behavioral learning. We have used motor learning in smooth pursuit eye movements of monkeys to determine how and when different components of learning occur in a known cerebellar circuit. The earliest learning occurs when one climbing-fiber response to a learning instruction causes simple-spike firing rate of Purkinje cells in the floccular complex of the cerebellum to be depressed transiently at the time of the instruction on the next trial. Trial-over-trial depression and the associated learning in eye movement are forgotten in <6 s, but facilitate long-term behavioral learning over a time scale of ∼5 min. During 100 repetitions of a learning instruction, simple-spike firing rate becomes progressively depressed in Purkinje cells that receive climbing-fiber inputs from the instruction. In Purkinje cells that prefer the opposite direction of pursuit and therefore do not receive climbing-fiber inputs related to the instruction, simple-spike responses undergo potentiation, but more weakly and more slowly. Analysis of the relationship between the learned changes in simple-spike firing and learning in eye velocity suggests an orderly progression of plasticity: first on Purkinje cells with complex-spike (CS) responses to the instruction, later on Purkinje cells with CS responses to the opposite direction of instruction, and last in sites outside the cerebellar cortex. Climbing-fiber inputs appear to play a fast and primary, but nonexclusive, role in pursuit learning.
Copyright © 2014 the authors 0270-6474/14/347077-14$15.00/0.

Entities:  

Keywords:  climbing fibers; floccular complex; long-term depression; smooth pursuit eye movement; synaptic plasticity; trial-over-trial learning

Mesh:

Year:  2014        PMID: 24849344      PMCID: PMC4028490          DOI: 10.1523/JNEUROSCI.0017-14.2014

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  58 in total

Review 1.  Computer simulation of cerebellar information processing.

Authors:  J F Medina; M D Mauk
Journal:  Nat Neurosci       Date:  2000-11       Impact factor: 24.884

2.  Effects of lesions of the oculomotor cerebellar vermis on eye movements in primate: smooth pursuit.

Authors:  M Takagi; D S Zee; R J Tamargo
Journal:  J Neurophysiol       Date:  2000-04       Impact factor: 2.714

Review 3.  Mechanisms of cerebellar learning suggested by eyelid conditioning.

Authors:  J F Medina; W L Nores; T Ohyama; M D Mauk
Journal:  Curr Opin Neurobiol       Date:  2000-12       Impact factor: 6.627

4.  Long-term potentiation of intrinsic excitability at the mossy fiber-granule cell synapse of rat cerebellum.

Authors:  S Armano; P Rossi; V Taglietti; E D'Angelo
Journal:  J Neurosci       Date:  2000-07-15       Impact factor: 6.167

5.  A new form of cerebellar long-term potentiation is postsynaptic and depends on nitric oxide but not cAMP.

Authors:  Varda Lev-Ram; Scott T Wong; Daniel R Storm; Roger Y Tsien
Journal:  Proc Natl Acad Sci U S A       Date:  2002-06-04       Impact factor: 11.205

Review 6.  Beyond parallel fiber LTD: the diversity of synaptic and non-synaptic plasticity in the cerebellum.

Authors:  C Hansel; D J Linden; E D'Angelo
Journal:  Nat Neurosci       Date:  2001-05       Impact factor: 24.884

7.  Reciprocal bidirectional plasticity of parallel fiber receptive fields in cerebellar Purkinje cells and their afferent interneurons.

Authors:  Henrik Jörntell; Carl-Fredrik Ekerot
Journal:  Neuron       Date:  2002-05-30       Impact factor: 17.173

8.  Cerebellar LTD facilitates but is not essential for long-term adaptation of the vestibulo-ocular reflex.

Authors:  A M van Alphen; C I De Zeeuw
Journal:  Eur J Neurosci       Date:  2002-08       Impact factor: 3.386

9.  Changes in the responses of Purkinje cells in the floccular complex of monkeys after motor learning in smooth pursuit eye movements.

Authors:  M Kahlon; S G Lisberger
Journal:  J Neurophysiol       Date:  2000-12       Impact factor: 2.714

10.  Partial ablations of the flocculus and ventral paraflocculus in monkeys cause linked deficits in smooth pursuit eye movements and adaptive modification of the VOR.

Authors:  H Rambold; A Churchland; Y Selig; L Jasmin; S G Lisberger
Journal:  J Neurophysiol       Date:  2002-02       Impact factor: 2.714

View more
  34 in total

Review 1.  Motor Learning and the Cerebellum.

Authors:  Chris I De Zeeuw; Michiel M Ten Brinke
Journal:  Cold Spring Harb Perspect Biol       Date:  2015-09-01       Impact factor: 10.005

2.  Bidirectional short-term plasticity during single-trial learning of cerebellar-driven eyelid movements in mice.

Authors:  Farzaneh Najafi; Javier F Medina
Journal:  Neurobiol Learn Mem       Date:  2019-10-11       Impact factor: 2.877

3.  Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning.

Authors:  Samuel D McDougle; Krista M Bond; Jordan A Taylor
Journal:  J Neurosci       Date:  2015-07-01       Impact factor: 6.167

Review 4.  Oscillations, Timing, Plasticity, and Learning in the Cerebellum.

Authors:  G Cheron; J Márquez-Ruiz; B Dan
Journal:  Cerebellum       Date:  2016-04       Impact factor: 3.847

5.  Movement Rate Is Encoded and Influenced by Widespread, Coherent Activity of Cerebellar Molecular Layer Interneurons.

Authors:  Michael A Gaffield; Jason M Christie
Journal:  J Neurosci       Date:  2017-04-07       Impact factor: 6.167

6.  Cerebellar-M1 Connectivity Changes Associated with Motor Learning Are Somatotopic Specific.

Authors:  Danny A Spampinato; Hannah J Block; Pablo A Celnik
Journal:  J Neurosci       Date:  2017-01-30       Impact factor: 6.167

7.  Responses of Purkinje cells in the oculomotor vermis of monkeys during smooth pursuit eye movements and saccades: comparison with floccular complex.

Authors:  Ramanujan T Raghavan; Stephen G Lisberger
Journal:  J Neurophysiol       Date:  2017-05-17       Impact factor: 2.714

8.  Multiple components in direction learning in smooth pursuit eye movements of monkeys.

Authors:  Nathan J Hall; Yan Yang; Stephen G Lisberger
Journal:  J Neurophysiol       Date:  2018-08-01       Impact factor: 2.714

9.  Modeling eye-head gaze shifts in multiple contexts without motor planning.

Authors:  Iman Haji-Abolhassani; Daniel Guitton; Henrietta L Galiana
Journal:  J Neurophysiol       Date:  2016-07-20       Impact factor: 2.714

10.  Population coding in the cerebellum: a machine learning perspective.

Authors:  Reza Shadmehr
Journal:  J Neurophysiol       Date:  2020-10-28       Impact factor: 2.714

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.