Motor imagery and action observation: Modulation of sensorimotor brain rhythms during mental control of a brain–computer interface

Neuper, Christa; Scherer, Reinhold; Wriessnegger, Selina; Pfurtscheller, Gert

doi:10.1016/j.clinph.2008.11.015

Cited by 354 publications

(251 citation statements)

References 39 publications

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“…In a study by Neuper et al [2009] no correlation was found between the 'Vividness of Mental Imagery Questionnaire' [Isaac et al 1996] and classification of the BCI. The questionnaire used in that study favoured visual imagery by asking patients to perform complex tasks (e.g.…”

Section: Disucssion and Conclusionmentioning

confidence: 99%

“…The ERS/ERD is closely related to a decrease in the peak of the power amplitude of the SMR, which has been suggested as an indicator of motor imagination ability . Intensity of ERS/ERD has also been related to MI, and has been seen to improve with practice [Neuper et al 2009]. …”

Section: Introductionmentioning

confidence: 99%

“…a smiley) [Leeb et al 2007]. However a study by Neuper et al [2009] showed that there is no difference between controlling an abstract object (an arrow) and the highly realistic presentation of a hand (a hand reaching for a mug). In that study patients were controlling an object on a screen so it more likely that they applied visual rather than kinaesthetic imagery.…”

Section: Introductionmentioning

confidence: 99%

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Using a motor imagery questionnaire to estimate the performance of a Brain–Computer Interface based on object oriented motor imagery

Vučković

Osuagwu

2013

Clinical Neurophysiology

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Section: Disucssion and Conclusionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using a motor imagery questionnaire to estimate the performance of a Brain–Computer Interface based on object oriented motor imagery

Vučković

Osuagwu

2013

Clinical Neurophysiology

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“…It is important to note that while performing motor imagery, participants received the same visual scene as during the RHI procedure (bilateral visual hand stimuli; e.g. Neuper et al, 2009). Each experimental block consisted of 30 randomized trials (15 left hand imagery, 15 right hand imagery trials) and was repeated three times, resulting in 90 trials.…”

Section: Motor Imagerymentioning

confidence: 99%

Shared electrophysiology mechanisms of body ownership and motor imagery

Evans

Blanke

2013

NeuroImage

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Although we feel, see, and experience our hands as our own (body or hand ownership), recent research has shown that illusory hand ownership can be induced for fake or virtual hands and may be useful for neuroprosthetics and brain-computer interfaces. Despite the vast amount of behavioral data on illusory hand ownership, neuroimaging studies are rare, in particular electrophysiological studies. Thus, while the neural systems underlying hand ownership are relatively well described, the spectral signatures of body ownership as measured by electroencephalography (EEG) remain elusive. Here we induced illusory hand ownership in an automated, computer-controlled manner using virtual reality while recording 64-channel EEG and found that illusory hand ownership is reflected by a body-specific modulation in the mu-band over fronto-parietal cortex. In a second experiment in the same subjects, we then show that mu as well as beta-band activity in highly similar fronto-parietal regions was also modulated during a motor imagery task often used in paradigms employing non-invasive brain-computer interface technology. These data provide insights into the electrophysiological brain mechanisms of illusory hand ownership and their strongly overlapping mechanisms with motor imagery in fronto-parietal cortex. They also highlight the potential of combining high-resolution EEG with virtual reality setups and automatized stimulation protocols for systematic, reproducible stimulus presentation in cognitive neuroscience, and may inform the design of non-invasive brain-computer interfaces.

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“…NFT allows real-time information of brain activity to be fed back visually to a user by means of a computer in a closed loop, enabling control and natural operation of brain oscillations across cortical networks in vivo and in near real-time (Nowlis and Kamiya 1970;Wolpaw et al 2002;Neuper et al 2009). The possibility of volitional control of brain electrical activity suggests, provided that they play a causal role in cognitive functions, that their modulation can have a functional impact.…”

Section: Introductionmentioning

confidence: 99%

An Effective Neurofeedback Intervention to Improve Social Interactions in Children with Autism Spectrum Disorder

Friedrich

Sivanathan

Lim

et al. 2015

J Autism Dev Disord

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Neurofeedback training (NFT) approaches were investigated to improve behavior, cognition and emotion regulation in children with autism spectrum disorder (ASD). Thirteen children with ASD completed pre-/post-assessments and 16 NFT-sessions. The NFT was based on a game that encouraged social interactions and provided feedback based on imitation and emotional responsiveness. Bidirectional training of EEG mu suppression and enhancement (8-12 Hz over somatosensory cortex) was compared to the standard method of enhancing mu. Children learned to control mu rhythm with both methods and showed improvements in (1) electrophysiology: increased mu suppression, (2) emotional responsiveness: improved emotion recognition and spontaneous imitation, and (3) behavior: significantly better behavior in every-day life. Thus, these NFT paradigms improve aspects of behavior necessary for successful social interactions.

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Motor imagery and action observation: Modulation of sensorimotor brain rhythms during mental control of a brain–computer interface

Cited by 354 publications

References 39 publications

Using a motor imagery questionnaire to estimate the performance of a Brain–Computer Interface based on object oriented motor imagery

Using a motor imagery questionnaire to estimate the performance of a Brain–Computer Interface based on object oriented motor imagery

Shared electrophysiology mechanisms of body ownership and motor imagery

An Effective Neurofeedback Intervention to Improve Social Interactions in Children with Autism Spectrum Disorder

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