Literature DB >> 20160084

Cortical activity during motor execution, motor imagery, and imagery-based online feedback.

Kai J Miller1, Gerwin Schalk, Eberhard E Fetz, Marcel den Nijs, Jeffrey G Ojemann, Rajesh P N Rao.   

Abstract

Imagery of motor movement plays an important role in learning of complex motor skills, from learning to serve in tennis to perfecting a pirouette in ballet. What and where are the neural substrates that underlie motor imagery-based learning? We measured electrocorticographic cortical surface potentials in eight human subjects during overt action and kinesthetic imagery of the same movement, focusing on power in "high frequency" (76-100 Hz) and "low frequency" (8-32 Hz) ranges. We quantitatively establish that the spatial distribution of local neuronal population activity during motor imagery mimics the spatial distribution of activity during actual motor movement. By comparing responses to electrocortical stimulation with imagery-induced cortical surface activity, we demonstrate the role of primary motor areas in movement imagery. The magnitude of imagery-induced cortical activity change was approximately 25% of that associated with actual movement. However, when subjects learned to use this imagery to control a computer cursor in a simple feedback task, the imagery-induced activity change was significantly augmented, even exceeding that of overt movement.

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Year:  2010        PMID: 20160084      PMCID: PMC2840149          DOI: 10.1073/pnas.0913697107

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  47 in total

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4.  Electrocorticography-based brain computer interface--the Seattle experience.

Authors:  Eric C Leuthardt; Kai J Miller; Gerwin Schalk; Rajesh P N Rao; Jeffrey G Ojemann
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2006-06       Impact factor: 3.802

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Journal:  Nature       Date:  2006-07-13       Impact factor: 49.962

6.  Spectral changes in cortical surface potentials during motor movement.

Authors:  Kai J Miller; Eric C Leuthardt; Gerwin Schalk; Rajesh P N Rao; Nicholas R Anderson; Daniel W Moran; John W Miller; Jeffrey G Ojemann
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8.  A brain-computer interface using electrocorticographic signals in humans.

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Journal:  J Neural Eng       Date:  2004-06-14       Impact factor: 5.379

9.  Electrocorticographically controlled brain-computer interfaces using motor and sensory imagery in patients with temporary subdural electrode implants. Report of four cases.

Authors:  Elizabeth A Felton; J Adam Wilson; Justin C Williams; P Charles Garell
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10.  Intraoperative electrocortical stimulation of Brodman area 4: a 10-year analysis of 255 cases.

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2.  Chronic embedded cortico-thalamic closed-loop deep brain stimulation for the treatment of essential tremor.

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3.  Decoding vowels and consonants in spoken and imagined words using electrocorticographic signals in humans.

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Journal:  J Neural Eng       Date:  2011-07-13       Impact factor: 5.379

4.  Connectivity mapping of the human ECoG during a motor task with a time-varying dynamic Bayesian network.

Authors:  Huaijian Zhang; Heather L Benz; Anastasios Bezerianos; Soumyadipta Acharya; Nathan E Crone; Anil Maybhate; Xiaoxiang Zheng; Nitish V Thakor
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2010

5.  Distributed cortical adaptation during learning of a brain-computer interface task.

Authors:  Jeremiah D Wander; Timothy Blakely; Kai J Miller; Kurt E Weaver; Lise A Johnson; Jared D Olson; Eberhard E Fetz; Rajesh P N Rao; Jeffrey G Ojemann
Journal:  Proc Natl Acad Sci U S A       Date:  2013-06-10       Impact factor: 11.205

6.  Neural Encoding of Auditory Features during Music Perception and Imagery.

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Journal:  Cereb Cortex       Date:  2018-12-01       Impact factor: 5.357

7.  Beta oscillations in the monkey sensorimotor network reflect somatosensory decision making.

Authors:  Saskia Haegens; Verónica Nácher; Adrián Hernández; Rogelio Luna; Ole Jensen; Ranulfo Romo
Journal:  Proc Natl Acad Sci U S A       Date:  2011-06-13       Impact factor: 11.205

8.  Collaborative approach in the development of high-performance brain-computer interfaces for a neuroprosthetic arm: translation from animal models to human control.

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9.  Evidence for a motor gamma-band network governing response interference.

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10.  Three-Dimensional Brain-Computer Interface Control Through Simultaneous Overt Spatial Attentional and Motor Imagery Tasks.

Authors:  Jianjun Meng; Taylor Streitz; Nicholas Gulachek; Daniel Suma; Bin He
Journal:  IEEE Trans Biomed Eng       Date:  2018-10-01       Impact factor: 4.538

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