Literature DB >> 25845626

How and why neural and motor variation are related.

Stephen G Lisberger1, Javier F Medina2.   

Abstract

Movements are variable. Recent findings in smooth pursuit eye movements provide an explanation for motor variation in terms of the organization of the brain's sensory-motor pathways. Variation in sensory estimation is propagated through sensory-motor circuits and ultimately causes motor variation. The sensory origin of motor variation creates trial-by-trial correlations among the responses of neurons at each level of the sensory motor circuit, and between neural and behavioral responses. We suggest that motor variation is a compromise between multiple competing constraints. The brain strives for motor behavior that is 'good enough' in the face of constraints that tend to promote variation.
Copyright © 2015 Elsevier Ltd. All rights reserved.

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Year:  2015        PMID: 25845626      PMCID: PMC4576830          DOI: 10.1016/j.conb.2015.03.008

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  40 in total

1.  Correlated firing in macaque visual area MT: time scales and relationship to behavior.

Authors:  W Bair; E Zohary; W T Newsome
Journal:  J Neurosci       Date:  2001-03-01       Impact factor: 6.167

2.  Bayesian integration in sensorimotor learning.

Authors:  Konrad P Körding; Daniel M Wolpert
Journal:  Nature       Date:  2004-01-15       Impact factor: 49.962

3.  Effect of changing feedback delay on spontaneous oscillations in smooth pursuit eye movements of monkeys.

Authors:  D Goldreich; R J Krauzlis; S G Lisberger
Journal:  J Neurophysiol       Date:  1992-03       Impact factor: 2.714

4.  The effect of correlated variability on the accuracy of a population code.

Authors:  L F Abbott; P Dayan
Journal:  Neural Comput       Date:  1999-01-01       Impact factor: 2.026

5.  Vector reconstruction from firing rates.

Authors:  E Salinas; L F Abbott
Journal:  J Comput Neurosci       Date:  1994-06       Impact factor: 1.621

6.  A computational analysis of the relationship between neuronal and behavioral responses to visual motion.

Authors:  M N Shadlen; K H Britten; W T Newsome; J A Movshon
Journal:  J Neurosci       Date:  1996-02-15       Impact factor: 6.167

7.  Motor variability arises from a slow random walk in neural state.

Authors:  Kris S Chaisanguanthum; Helen H Shen; Philip N Sabes
Journal:  J Neurosci       Date:  2014-09-03       Impact factor: 6.167

8.  Power spectrum analysis of bursting cells in area MT in the behaving monkey.

Authors:  W Bair; C Koch; W Newsome; K Britten
Journal:  J Neurosci       Date:  1994-05       Impact factor: 6.167

9.  Noise correlations in cortical area MT and their potential impact on trial-by-trial variation in the direction and speed of smooth-pursuit eye movements.

Authors:  Xin Huang; Stephen G Lisberger
Journal:  J Neurophysiol       Date:  2009-03-25       Impact factor: 2.714

10.  The interaction of bayesian priors and sensory data and its neural circuit implementation in visually guided movement.

Authors:  Jin Yang; Joonyeol Lee; Stephen G Lisberger
Journal:  J Neurosci       Date:  2012-12-05       Impact factor: 6.167

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  12 in total

1.  Sensorimotor Coding of Vermal Granule Neurons in the Developing Mammalian Cerebellum.

Authors:  Kelly H Markwalter; Yue Yang; Timothy E Holy; Azad Bonni
Journal:  J Neurosci       Date:  2019-06-24       Impact factor: 6.167

2.  Cerebellar granule cells acquire a widespread predictive feedback signal during motor learning.

Authors:  Andrea Giovannucci; Aleksandra Badura; Ben Deverett; Farzaneh Najafi; Talmo D Pereira; Zhenyu Gao; Ilker Ozden; Alexander D Kloth; Eftychios Pnevmatikakis; Liam Paninski; Chris I De Zeeuw; Javier F Medina; Samuel S-H Wang
Journal:  Nat Neurosci       Date:  2017-03-20       Impact factor: 24.884

3.  Individual Movement Variability Magnitudes Are Explained by Cortical Neural Variability.

Authors:  Shlomi Haar; Opher Donchin; Ilan Dinstein
Journal:  J Neurosci       Date:  2017-08-18       Impact factor: 6.167

4.  Increasing Muscle Speed Drives Changes in the Neuromuscular Transform of Motor Commands during Postnatal Development in Songbirds.

Authors:  Iris Adam; Coen P H Elemans
Journal:  J Neurosci       Date:  2020-06-02       Impact factor: 6.167

5.  Methods for measuring swallowing pressure variability using high-resolution manometry.

Authors:  Corinne A Jones; Ellen L Meisner; Courtney K Broadfoot; Sarah P Rosen; Christine R Samuelsen; Timothy M McCulloch
Journal:  Front Appl Math Stat       Date:  2018-07-02

Review 6.  The importance of task design and behavioral control for understanding the neural basis of cognitive functions.

Authors:  Christopher R Fetsch
Journal:  Curr Opin Neurobiol       Date:  2016-01-14       Impact factor: 6.627

Review 7.  Perceptual-motor styles.

Authors:  Pierre-Paul Vidal; Francesco Lacquaniti
Journal:  Exp Brain Res       Date:  2021-03-06       Impact factor: 2.064

8.  Behavioral and Neural Variability of Naturalistic Arm Movements.

Authors:  Steven M Peterson; Satpreet H Singh; Nancy X R Wang; Rajesh P N Rao; Bingni W Brunton
Journal:  eNeuro       Date:  2021-06-22

9.  Swallowing Pressure Variability as a Function of Pharyngeal Region, Bolus Volume, Age, and Sex.

Authors:  Corinne A Jones; Michelle R Ciucci; Suzan M Abdelhalim; Timothy M McCulloch
Journal:  Laryngoscope       Date:  2020-04-18       Impact factor: 3.325

10.  Redundancy and multifunctionality among spinal locomotor networks.

Authors:  Bau N Pham; Jiangyuan Luo; Harnadar Anand; Olivia Kola; Pia Salcedo; Connie Nguyen; Sarah Gaunt; Hui Zhong; Alan Garfinkel; Niranjala Tillakaratne; V Reggie Edgerton
Journal:  J Neurophysiol       Date:  2020-09-23       Impact factor: 2.974

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