Literature DB >> 28580720

Learned control of inter-hemispheric connectivity: Effects on bimanual motor performance.

Diljit Singh Kajal1,2,3,4, Christoph Braun2,4,5,6, Jürgen Mellinger7, Matthew D Sacchet8, Sergio Ruiz1,9,10, Eberhard Fetz11, Niels Birbaumer1,12,13, Ranganatha Sitaram9,10,14.   

Abstract

Bimanual movements involve the interactions between both primary motor cortices. These interactions are assumed to involve phase-locked oscillatory brain activity referred to as inter-hemispheric functional coupling. So far, inter-hemispheric functional coupling has been investigated as a function of motor performance. These studies report mostly a negative correlation between the performance in motor tasks and the strength of functional coupling. However, correlation might not reflect a causal relationship. To overcome this limitation, we opted for an alternative approach by manipulating the strength of inter-hemispheric functional coupling and assessing bimanual motor performance as a dependent variable. We hypothesize that an increase/decrease of functional coupling deteriorates/facilitates motor performance in an out-of-phase bimanual finger-tapping task. Healthy individuals were trained to volitionally regulate functional coupling in an operant conditioning paradigm using real-time magnetoencephalography neurofeedback. During operant conditioning, two discriminative stimuli were associated with upregulation and downregulation of functional coupling. Effects of training were assessed by comparing motor performance prior to (pre-test) and after the training (post-test). Participants receiving contingent feedback learned to upregulate and downregulate functional coupling. Comparing motor performance, as indexed by the ratio of tapping speed for upregulation versus downregulation trials, no change was found in the control group between pre- and post-test. In contrast, the group receiving contingent feedback evidenced a significant decrease of the ratio implicating lower tapping speed with stronger functional coupling. Results point toward a causal role of inter-hemispheric functional coupling for the performance in bimanual tasks. Hum Brain Mapp 38:4353-4369, 2017.
© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  behavior; braincomputer interface; coherence; magnetoencephalography; motor; neurofeedback

Mesh:

Year:  2017        PMID: 28580720      PMCID: PMC6867064          DOI: 10.1002/hbm.23663

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


  59 in total

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Authors:  Andre M Bastos; Julien Vezoli; Pascal Fries
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2.  Dynamic imaging of coherent sources: Studying neural interactions in the human brain.

Authors:  J Gross; J Kujala; M Hamalainen; L Timmermann; A Schnitzler; R Salmelin
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3.  The control of electroencephalographic alpha rhythms through auditory feedback and the associated mental activity.

Authors:  D P Nowlis; J Kamiya
Journal:  Psychophysiology       Date:  1970-01       Impact factor: 4.016

Review 4.  Interhemispheric control of manual motor activity.

Authors:  G M Geffen; D L Jones; L B Geffen
Journal:  Behav Brain Res       Date:  1994-10-20       Impact factor: 3.332

5.  Inter-hemispheric functional connectivity changes with corpus callosum morphology in multiple sclerosis.

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Journal:  Neuroscience       Date:  2014-01-29       Impact factor: 3.590

6.  Synchronization of neurons during local field potential oscillations in sensorimotor cortex of awake monkeys.

Authors:  V N Murthy; E E Fetz
Journal:  J Neurophysiol       Date:  1996-12       Impact factor: 2.714

7.  An MEG-based brain-computer interface (BCI).

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Journal:  Neuroimage       Date:  2007-03-27       Impact factor: 6.556

8.  Volitional control of neuromagnetic coherence.

Authors:  Matthew D Sacchet; Jürgen Mellinger; Ranganatha Sitaram; Christoph Braun; Niels Birbaumer; Eberhard Fetz
Journal:  Front Neurosci       Date:  2012-12-26       Impact factor: 4.677

9.  Brain-Computer Interface-Based Communication in the Completely Locked-In State.

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10.  Connectivity-based neurofeedback: dynamic causal modeling for real-time fMRI.

Authors:  Yury Koush; Maria Joao Rosa; Fabien Robineau; Klaartje Heinen; Sebastian W Rieger; Nikolaus Weiskopf; Patrik Vuilleumier; Dimitri Van De Ville; Frank Scharnowski
Journal:  Neuroimage       Date:  2013-05-11       Impact factor: 6.556

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