Literature DB >> 20962235

Eyelid conditioning to a target amplitude: adding how much to whether and when.

Joy C Kreider1, Michael D Mauk.   

Abstract

Conceptual and practical advantages of pavlovian eyelid conditioning facilitate analysis of cerebellar computation and learning. Even so, eyelid conditioning procedures are unrealistic in an important way. The error signal to the olivocerebellar system does not decrease as learning adapts response amplitude or gain. This inherently limits the utility of eyelid conditioning for studies investigating how cerebellar learning mechanisms acquire and store an adaptive response amplitude. We report the development and characterization of a training procedure in which conditioned response amplitude is brought under experimental control with contingencies that more closely parallel natural conditions. In this procedure, the delivery of the unconditioned stimulus (US) is made contingent on conditioned response amplitude: the US is delivered for responses that fail to reach a specified target amplitude and is omitted for responses that meet or exceed the target. We find that rabbits trained with either a tone or with mossy fiber stimulation as the conditioned stimulus learn responses that approach target amplitudes ranging from 2 to 5 mm. Inactivating the interpositus nucleus with muscimol infusions abolished these conditioned responses, indicating that cerebellar involvement in eyelid conditioning is not tied explicitly to the use of pavlovian procedures. Together with previous studies, these data suggest that response amplitude is learned and encoded in the cerebellum during eyelid conditioning. As such, these results provide a foundation for systematic and controlled investigations of the cerebellar mechanisms that learn and encode the proper amplitude of adaptive movements.

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Year:  2010        PMID: 20962235      PMCID: PMC2975963          DOI: 10.1523/JNEUROSCI.3473-10.2010

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


  25 in total

1.  Simulations of cerebellar motor learning: computational analysis of plasticity at the mossy fiber to deep nucleus synapse.

Authors:  J F Medina; M D Mauk
Journal:  J Neurosci       Date:  1999-08-15       Impact factor: 6.167

2.  A model of Pavlovian eyelid conditioning based on the synaptic organization of the cerebellum.

Authors:  M D Mauk; N H Donegan
Journal:  Learn Mem       Date:  1997 May-Jun       Impact factor: 2.460

3.  Learned movements elicited by direct stimulation of cerebellar mossy fiber afferents.

Authors:  G Hesslow; P Svensson; M Ivarsson
Journal:  Neuron       Date:  1999-09       Impact factor: 17.173

4.  Inhibition of climbing fibres is a signal for the extinction of conditioned eyelid responses.

Authors:  Javier F Medina; William L Nores; Michael D Mauk
Journal:  Nature       Date:  2002-03-21       Impact factor: 49.962

5.  A mechanism for savings in the cerebellum.

Authors:  J F Medina; K S Garcia; M D Mauk
Journal:  J Neurosci       Date:  2001-06-01       Impact factor: 6.167

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.  Conditioned eyelid movement is not a blink.

Authors:  Alice Schade Powers; Pamela Coburn-Litvak; Craig Evinger
Journal:  J Neurophysiol       Date:  2009-11-25       Impact factor: 2.714

Review 8.  The nature of reinforcement in cerebellar learning.

Authors:  R F Thompson; J K Thompson; J J Kim; D J Krupa; P G Shinkman
Journal:  Neurobiol Learn Mem       Date:  1998 Jul-Sep       Impact factor: 2.877

9.  Neural learning rules for the vestibulo-ocular reflex.

Authors:  J L Raymond; S G Lisberger
Journal:  J Neurosci       Date:  1998-11-01       Impact factor: 6.167

Review 10.  Roles of cerebellar cortex and nuclei in motor learning: contradictions or clues?

Authors:  M D Mauk
Journal:  Neuron       Date:  1997-03       Impact factor: 17.173

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  7 in total

1.  Links Between Single-Trial Changes and Learning Rate in Eyelid Conditioning.

Authors:  Andrei Khilkevich; Hunter E Halverson; Jose Ernesto Canton-Josh; Michael D Mauk
Journal:  Cerebellum       Date:  2016-04       Impact factor: 3.847

Review 2.  Consensus paper: current views on the role of cerebellar interpositus nucleus in movement control and emotion.

Authors:  Vincenzo Perciavalle; Richard Apps; Vlastislav Bracha; José M Delgado-García; Alan R Gibson; Maria Leggio; Andrew J Carrel; Nadia Cerminara; Marinella Coco; Agnès Gruart; Raudel Sánchez-Campusano
Journal:  Cerebellum       Date:  2013-10       Impact factor: 3.847

3.  Using a million cell simulation of the cerebellum: network scaling and task generality.

Authors:  Wen-Ke Li; Matthew J Hausknecht; Peter Stone; Michael D Mauk
Journal:  Neural Netw       Date:  2012-11-20

4.  Disruption of rat deep cerebellar perineuronal net alters eyeblink conditioning and neuronal electrophysiology.

Authors:  Deidre E O'Dell; Bernard G Schreurs; Carrie Smith-Bell; Desheng Wang
Journal:  Neurobiol Learn Mem       Date:  2020-12-04       Impact factor: 2.877

5.  An agonist-antagonist cerebellar nuclear system controlling eyelid kinematics during motor learning.

Authors:  Raudel Sánchez-Campusano; Agnès Gruart; Rodrigo Fernández-Mas; José M Delgado-García
Journal:  Front Neuroanat       Date:  2012-03-14       Impact factor: 3.856

6.  Trace Eyeblink Conditioning in Mice Is Dependent upon the Dorsal Medial Prefrontal Cortex, Cerebellum, and Amygdala: Behavioral Characterization and Functional Circuitry

Authors:  Jennifer J Siegel; William Taylor; Richard Gray; Brian Kalmbach; Boris V Zemelman; Niraj S Desai; Daniel Johnston; Raymond A Chitwood
Journal:  eNeuro       Date:  2015-07-10

7.  A cerebellar adaptation to uncertain inputs.

Authors:  Andrei Khilkevich; Jose Canton-Josh; Evan DeLord; Michael D Mauk
Journal:  Sci Adv       Date:  2018-05-30       Impact factor: 14.136

  7 in total

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