Imagery of motor actions: differential effects of kinesthetic and visual-motor mode of imagery in single-trial EEG.
By Christa Neuper, Reinhold Scherer, Miriam Reiner, Gert Pfurtscheller. Brain research. Cognitive brain research, 2005
751 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Cellular and Molecular Neuroscience, Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/f6a88ed02805577d96e859c25cf2f7f68524a4ea
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Brendan Z. Allison
- Gert Pfurtscheller
- Christa Neuper
- Jonathan R. Wolpaw
- Dennis J. McFarland
- Luis F. Nicolás-Alonso
- Horst Bischof
- K. Müller
In Cellular and Molecular Neuroscience
- Fabien Lotte
- Brendan Z. Allison
- Benjamin Blankertz
- Jonathan R. Wolpaw
- K. Müller
- Gert Pfurtscheller
- Luis F. Nicolás-Alonso
- Jaime Gómez Gil
In Cognitive Neuroscience
- Fabien Lotte
- Benjamin Blankertz
- K. Müller
- Luis F. Nicolás-Alonso
- Jaime Gómez Gil
- Brendan Z. Allison
- Cuntai Guan
- Gert Pfurtscheller
Citations in the corpus
- Optimizing Spatial filters for Robust EEG Single-Trial Analysis (2008, background): “1For more effective performance it is important to instruct the subjects to concentrate on the kinesthetic aspect rather than the visual ([37]).”
- Motor imagery and action observation: modulation of sensorimotor brain rhythms during mental control of a brain-computer interface. (2009, methodology): “…have been utilized as important features in motor related BCI systems, and the discrimination between right hand and left hand motor imagery has shown to be very useful for ERD-based classification (Pfurtscheller et al., 1997; Neuper et al., 1999, 2005, 2006; Pfurtscheller and Neuper, 2001).”
- A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals (2007, background): “…et al 2005, Borisoff et al 2004, Fatourechi et al 2004, 2005) Distinctive sensitive learning vector quantization (DSLVQ) (Flotzinger et al 1994, Neuper et al 2005, Pfurtscheller et al 1996, 1997, 1998, 2000, Pfurtscheller and Neuper 2001, Pregenzer and Pfurtscheller 1995, 1999) Sequential…”
- BCI Demographics: How Many (and What Kinds of) People Can Use an SSVEP BCI? (2010, background): “found that subjects performed better in an SMR BCI when they imagined themselves moving compared to when they imagined watching themselves move [35].”
- Towards an independent brain-computer interface using steady state visual evoked potentials. (2008, background): “Similarly, subjects who utilized first-person movement imagery learned mu BCI control better than subjects who were told to adopt third-person movement imagery (Neuper et al., 2005).”
- Brain–computer interface systems: progress and prospects (2007, methodology): “Cognitive neuroscience can inform and inspire research concerning training, feedback, display parameters, con-trol strategies, usability, distraction, fatigue, motivation and discomfort [6,39,40,46,49,102,109,115,146] .”
- Brain–computer interface using a simplified functional near-infrared spectroscopy system (2007, background): “They were asked to imagine the kinaesthetic experience of movement while avoiding muscle tension [ 21 ].”
- Combining Brain–Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges (2010, background): “Because the aim of motor imagery is to activate the motor networks, it is crucial that subjects perform the mental task from the 1st person perspective (so called kines-thetic MI), in contrast to 3rd person perspective or visual imagery [36, 134].”
- EEG datasets for motor imagery brain–computer interface (2017, positive): “When imagining the movement, we asked subjects to imagine the kinesthetic experience [8], rather than imagining the visual experience.”
- Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design (2013, background): “…the user to perform kines-thetic imagination of movements rather than visual imagination of movements substantially improved performances (Neuper et al., 2005) It should be mentioned that although the training procedure and the signal processing algorithms used are important factors in…”
- Brain-Computer Interfaces: A Gentle Introduction (2009, background): “In a BCI, a user who wants to move the cursor up may learn that mentally visualizing a certain motor task such as a clenching one’s fist is less effective than thinking about the kinaesthetic experience of such a movement [22].”
- Brain Computer Interfaces, a Review (2012, background): “User training should emphasize kinesthetic experiences instead of visual representations of actions [143].”
- Neurophysiological predictor of SMR-based BCI performance (2010, neutral): “One possible reason for this phenomenon could be that these participants used a wrong strategy, e.g., only visually imagining the movements instead of kinesthetically (Neuper et al. (2005)).”
- Could Anyone Use a BCI? (2010, background): “Neuper et al. (2005) showed that instructing subjects to focus on first-person motor imagery (that is, imagining their own hand moving) could improve performance relative to third-person motor imagery (that is, imagining watching a hand move).”