Literature DB >> 32880848

Reinforcement Signaling Can Be Used to Reduce Elements of Cerebellar Reaching Ataxia.

Amanda S Therrien1, Matthew A Statton2, Amy J Bastian2,3.   

Abstract

Damage to the cerebellum causes a disabling movement disorder called ataxia, which is characterized by poorly coordinated movement. Arm ataxia causes dysmetria (over- or under-shooting of targets) with many corrective movements. As a result, people with cerebellar damage exhibit reaching movements with highly irregular and prolonged movement paths. Cerebellar patients are also impaired in error-based motor learning, which may impede rehabilitation interventions. However, we have recently shown that cerebellar patients can learn a simple reaching task using a binary reinforcement paradigm, in which feedback is based on participants' mean performance. Here, we present a pilot study that examined whether patients with cerebellar damage can use this reinforcement training to learn a more complex motor task-to decrease the path length of their reaches. We compared binary reinforcement training to a control condition of massed practice without reinforcement feedback. In both conditions, participants made target-directed reaches in 3-dimensional space while vision of their movement was occluded. In the reinforcement training condition, reaches with a path length below participants' mean were reinforced with an auditory stimulus at reach endpoint. We found that patients were able to use reinforcement signaling to significantly reduce their reach paths. Massed practice produced no systematic change in patients' reach performance. Overall, our results suggest that binary reinforcement training can improve reaching movements in patients with cerebellar damage and the benefit cannot be attributed solely to repetition or reduced visual control.

Entities:  

Keywords:  Ataxia; Cerebellum; Motor learning; Reaching; Reinforcement

Mesh:

Year:  2021        PMID: 32880848      PMCID: PMC7927977          DOI: 10.1007/s12311-020-01183-x

Source DB:  PubMed          Journal:  Cerebellum        ISSN: 1473-4222            Impact factor:   3.847


  34 in total

1.  Learning of visuomotor transformations for vectorial planning of reaching trajectories.

Authors:  J W Krakauer; Z M Pine; M F Ghilardi; C Ghez
Journal:  J Neurosci       Date:  2000-12-01       Impact factor: 6.167

2.  The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

Authors:  Peter A Butcher; Richard B Ivry; Sheng-Han Kuo; David Rydz; John W Krakauer; Jordan A Taylor
Journal:  J Neurophysiol       Date:  2017-06-21       Impact factor: 2.714

3.  Intact ability to learn internal models of arm dynamics in Huntington's disease but not cerebellar degeneration.

Authors:  Maurice A Smith; Reza Shadmehr
Journal:  J Neurophysiol       Date:  2004-12-29       Impact factor: 2.714

4.  Predicting and correcting ataxia using a model of cerebellar function.

Authors:  Nasir H Bhanpuri; Allison M Okamura; Amy J Bastian
Journal:  Brain       Date:  2014-05-08       Impact factor: 13.501

5.  Cerebellar outflow lesions: a comparison of movement deficits resulting from lesions at the levels of the cerebellum and thalamus.

Authors:  A J Bastian; W T Thach
Journal:  Ann Neurol       Date:  1995-12       Impact factor: 10.422

6.  Can patients with cerebellar disease switch learning mechanisms to reduce their adaptation deficits?

Authors:  Aaron L Wong; Cherie L Marvel; Jordan A Taylor; John W Krakauer
Journal:  Brain       Date:  2019-03-01       Impact factor: 13.501

7.  Individuals with cerebellar degeneration show similar adaptation deficits with large and small visuomotor errors.

Authors:  John E Schlerf; Jing Xu; Nola M Klemfuss; Thomas L Griffiths; Richard B Ivry
Journal:  J Neurophysiol       Date:  2012-11-28       Impact factor: 2.714

8.  Learning from sensory and reward prediction errors during motor adaptation.

Authors:  Jun Izawa; Reza Shadmehr
Journal:  PLoS Comput Biol       Date:  2011-03-10       Impact factor: 4.475

9.  Dissociating error-based and reinforcement-based loss functions during sensorimotor learning.

Authors:  Joshua G A Cashaback; Heather R McGregor; Ayman Mohatarem; Paul L Gribble
Journal:  PLoS Comput Biol       Date:  2017-07-28       Impact factor: 4.475

10.  The relationship between reinforcement and explicit control during visuomotor adaptation.

Authors:  Olivier Codol; Peter J Holland; Joseph M Galea
Journal:  Sci Rep       Date:  2018-06-14       Impact factor: 4.379

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  3 in total

1.  Reward timing matters in motor learning.

Authors:  Pierre Vassiliadis; Aegryan Lete; Julie Duque; Gerard Derosiere
Journal:  iScience       Date:  2022-04-25

2.  Preliminary Study of Vibrotactile Feedback during Home-Based Balance and Coordination Training in Individuals with Cerebellar Ataxia.

Authors:  Safa Jabri; David D Bushart; Catherine Kinnaird; Tian Bao; Angel Bu; Vikram G Shakkottai; Kathleen H Sienko
Journal:  Sensors (Basel)       Date:  2022-05-05       Impact factor: 3.847

Review 3.  Mechanisms of Human Motor Learning Do Not Function Independently.

Authors:  Amanda S Therrien; Aaron L Wong
Journal:  Front Hum Neurosci       Date:  2022-01-04       Impact factor: 3.473

  3 in total

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