Literature DB >> 19955356

Trial-to-trial variability of single cells in motor cortices is dynamically modified during visuomotor adaptation.

Yael Mandelblat-Cerf1, Rony Paz, Eilon Vaadia.   

Abstract

Neurons in all brain areas exhibit variability in their spiking activity. Although part of this variability can be considered as noise that is detrimental to information processing, recent findings indicate that variability can also be beneficial. In particular, it was suggested that variability in the motor system allows for exploration of possible motor states and therefore can facilitate learning and adaptation to new environments. Here, we provide evidence to support this idea by analyzing the variability of neurons in the primary motor cortex (M1) and in the supplementary motor area (SMA-proper) of monkeys adapting to new rotational visuomotor tasks. We found that trial-to-trial variability increased during learning and exhibited four main characteristics: (1) modulation occurred preferentially during a delay period when the target of movement was already known, but before movement onset; (2) variability returned to its initial levels toward the end of learning; (3) the increase in variability was more apparent in cells with preferred movement directions close to those experienced during learning; and (4) the increase in variability emerged at early phases of learning in the SMA, whereas in M1 behavior reached plateau levels of performance. These results are highly consistent with previous findings that showed similar trends in variability across a population of neurons. Together, the results strengthen the idea that single-cell variability can be much more than mere noise and may be an integral part of the underlying mechanism of sensorimotor learning.

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Mesh:

Year:  2009        PMID: 19955356      PMCID: PMC6665974          DOI: 10.1523/JNEUROSCI.3011-09.2009

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


  37 in total

1.  The modulation of BOLD variability between cognitive states varies by age and processing speed.

Authors:  Douglas D Garrett; Natasa Kovacevic; Anthony R McIntosh; Cheryl L Grady
Journal:  Cereb Cortex       Date:  2012-03-14       Impact factor: 5.357

2.  Trial-to-trial variability of the prefrontal neurons reveals the nature of their engagement in a motion discrimination task.

Authors:  Cory Hussar; Tatiana Pasternak
Journal:  Proc Natl Acad Sci U S A       Date:  2010-11-22       Impact factor: 11.205

3.  Parkinson's disease differentially affects adaptation to gradual as compared to sudden visuomotor distortions.

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4.  The importance of being variable.

Authors:  Douglas D Garrett; Natasa Kovacevic; Anthony R McIntosh; Cheryl L Grady
Journal:  J Neurosci       Date:  2011-03-23       Impact factor: 6.167

5.  Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model.

Authors:  Stephanie Westendorff; Shenbing Kuang; Bahareh Taghizadeh; Opher Donchin; Alexander Gail
Journal:  J Neurophysiol       Date:  2015-01-21       Impact factor: 2.714

6.  Distinct types of neural reorganization during long-term learning.

Authors:  Xiao Zhou; Rex N Tien; Sadhana Ravikumar; Steven M Chase
Journal:  J Neurophysiol       Date:  2019-02-06       Impact factor: 2.714

7.  Corticospinal excitability is enhanced after visuomotor adaptation and depends on learning rather than performance or error.

Authors:  Hamid F Bagce; Soha Saleh; Sergei V Adamovich; John W Krakauer; Eugene Tunik
Journal:  J Neurophysiol       Date:  2012-11-28       Impact factor: 2.714

8.  Temporal stability of visually selective responses in intracranial field potentials recorded from human occipital and temporal lobes.

Authors:  Arjun K Bansal; Jedediah M Singer; William S Anderson; Alexandra Golby; Joseph R Madsen; Gabriel Kreiman
Journal:  J Neurophysiol       Date:  2012-09-05       Impact factor: 2.714

9.  Trial-to-Trial Variability in Electrodermal Activity to Odor in Autism.

Authors:  Sarah M Haigh; Yaara Endevelt-Shapira; Marlene Behrmann
Journal:  Autism Res       Date:  2020-08-28       Impact factor: 5.216

10.  Stimulus onset quenches neural variability: a widespread cortical phenomenon.

Authors:  Mark M Churchland; Byron M Yu; John P Cunningham; Leo P Sugrue; Marlene R Cohen; Greg S Corrado; William T Newsome; Andrew M Clark; Paymon Hosseini; Benjamin B Scott; David C Bradley; Matthew A Smith; Adam Kohn; J Anthony Movshon; Katherine M Armstrong; Tirin Moore; Steve W Chang; Lawrence H Snyder; Stephen G Lisberger; Nicholas J Priebe; Ian M Finn; David Ferster; Stephen I Ryu; Gopal Santhanam; Maneesh Sahani; Krishna V Shenoy
Journal:  Nat Neurosci       Date:  2010-02-21       Impact factor: 24.884

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