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Cognitive Neuroscience
Current Debates, Research & Reports
Volume 10, 2019 - Issue 1
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Acquisition of a mental strategy to control a virtual tail via brain–computer interface

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References

  • Agashe, H. A., Paek, A. Y., Zhang, Y., & Contreras-Vidal, J. L. (2015). Global cortical activity predicts shape of hand during grasping. Frontiers in Neuroscience, 9, 121.
  • Ahn, M., Cho, H., Ahn, S., & Jun, S. C. (2013). High theta and low alpha powers may be indicative of BCI-illiteracy in motor imagery. PLoS One, 8(11), e80886.
  • Birbaumer, N., Ghanayim, N., Hinterberger, T., Iversen, I., Kotchoubey, B., Kübler, A., & Flor, H. (1999). A spelling device for the paralysed. Nature, 398(6725), 297–298.
  • Blankertz, B., Sannelli, C., Halder, S., Hammer, E. M., Kübler, A., Müller, K. R., & Dickhaus, T. (2010). Neurophysiological predictor of SMR-based BCI performance. Neuroimage, 51(4), 1303–1309.
  • Carmena, J. M., Lebedev, M. A., Crist, R. E., O’Doherty, J. E., Santucci, D. M., Dimitrov, D. F., & Nicolelis, M. A. (2003). Learning to control a brain-machine interface for reaching and grasping by primates. PLoS Biology, 1(2), E42.
  • Cassim, F., Monaca, C., Szurhaj, W., Bourriez, J. L., Defebvre, L., Derambure, P., & Guieu, J. D. (2001). Does post-movement beta synchronization reflect an idling motor cortex? Neuroreport, 12(17), 3859–3863.
  • Clausen, J., Fetz, E. E., Donoghue, J., Ushiba, J., Spörhase, U., Chandler, J., & Soekadar, S. R. (2017). Help, hope, and hype: Ethical dimensions of neuroprosthetics. Science, 356(6345), 1338–1339.
  • Favilla, M. (2006). Reaching movements in children: Accuracy and reaction time development. Experimental Brain Research, 169(1), 122–125.
  • Fetz, E. E. (1969). Operant conditioning of cortical unit activity. Science, 163(3870), 955–958.
  • Finke, A., Lenhardt, A., & Ritter, H. (2009). The MindGame: A P300-based brain-computer interface game. Neural Networks, 22(9), 1329–1333.
  • Gaetz, W., & Cheyne, D. (2006). Localization of sensorimotor cortical rhythms induced by tactile stimulation using spatially filtered MEG. Neuroimage, 30(3), 899–908.
  • Green, A. M., & Kalaska, J. F. (2011). Learning to move machines with the mind. Trends in Neurosciences, 34(2), 61–75.
  • Hjorth, B. (1975). An on-line transformation of EEG scalp potentials into orthogonal source derivations. Electroencephalography and Clinical Neurophysiology, 39(5), 526–530.
  • Hochberg, L. R., Bacher, D., Jarosiewicz, B., Masse, N. Y., Simeral, J. D., Vogel, J., & Donoghue, J. P. (2012). Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature, 485(7398), 372–375.
  • Hochberg, L. R., Serruya, M. D., Friehs, G. M., Mukand, J. A., Saleh, M., Caplan, A. H., & Donoghue, J. P. (2006). Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature, 442(7099), 164–171.
  • Jackson, A., & Zimmermann, J. B. (2012). Neural interfaces for the brain and spinal cord–Restoring motor function. Nature Reviews. Neurology, 8(12), 690–699.
  • Körding, K. P., Tenenbaum, J. B., & Shadmehr, R. (2007). The dynamics of memory as a consequence of optimal adaptation to a changing body. Nature Neuroscience, 10(6), 779–786.
  • Krakauer, J. W., Pine, Z. M., Ghilardi, M. F., & Ghez, C. (2000). Learning of visuomotor transformations for vectorial planning of reaching trajectories. Journal of Neuroscience, 20(23), 8916–8924.
  • Lisi, G., Noda, T., & Morimoto, J. (2014). Decoding the ERD/ERS: Influence of afferent input induced by a leg assistive robot. Frontiers in Systems Neuroscience, 8. doi:10.3389/fnsys.2014.00085
  • Lackner, J. R., & Dizio, P. (1994). Rapid adaptation to Coriolis force perturbations of arm trajectory. Journal of Neurophysiology, 72(1), 299–313.
  • Mazzoni, P., & Krakauer, J. W. (2006). An implicit plan overrides an explicit strategy during visuomotor adaptation. The Journal of Neuroscience, 26(14), 3642–3645.
  • Mukaino, M., Ono, T., Shindo, K., Fujiwara, T., Ota, T., Kimura, A., & Ushiba, J. (2014). Efficacy of brain-computer interface-driven neuromuscular electrical stimulation for chronic paresis after stroke. Journal of Rehabilitation Medicine, 46(4), 378–382.
  • Müller, G. R., Neuper, C., Rupp, R., Keinrath, C., Gerner, H. J., & Pfurtscheller, G. (2003). Event-related beta EEG changes during wrist movements induced by functional electrical stimulation of forearm muscles in man. Neuroscience Letters, 340(2), 143–147.
  • Müller-Putz, G. R., Zimmermann, D., Graimann, B., Nestinger, K., Korisek, G., & Pfurtscheller, G. (2007). Event-related beta EEG-changes during passive and attempted foot movements in paraplegic patients. Brain Research, 1137(1), 84–91.
  • Naros, G., & Gharabaghi, A. (2015). Reinforcement learning of self-regulated β-oscillations for motor restoration in chronic stroke. Frontiers in Human Neuroscience, 9, 391.
  • Ono, T., Kimura, A., & Ushiba, J. (2013). Daily training with realistic visual feedback improves reproducibility of event-related desynchronisation following hand motor imagery. Clinical Neurophysiology, 124(9), 1779–1786.
  • Ono, T., Shindo, K., Kawashima, K., Ota, N., Ito, M., Ota, T., & Ushiba, J. (2014). Brain-computer interface with somatosensory feedback improves functional recovery from severe hemiplegia due to chronic stroke. Frontiers in Neuroengineering, 7, 19.
  • Pfurtscheller, G., Brunner, C., Schlögl, A., & Lopes da Silva, F. H. (2006). Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks. Neuroimage, 31(1), 153–159.
  • Pfurtscheller, G., & Lopes da Silva, F. H. (1999). Event-related EEG/MEG synchronization and desynchronization: Basic principles. Clinical Neurophysiology, 110(11), 1842–1857.
  • Pfurtscheller, G., & Neuper, C. (1994). Event-related synchronization of mu rhythm in the EEG over the cortical hand area in man. Neuroscience Letters, 174(1), 93–96.
  • Pfurtscheller, G., & Solis-Escalante, T. (2009). Could the beta rebound in the EEG be suitable to realize a “brain switch”? Clinical Neurophysiology, 120(1), 24–29.
  • Pineda, J. A., Silverman, D. S., Vankov, A., & Hestenes, J. (2003). Learning to control brain rhythms: Making a brain-computer interface possible. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 11(2), 181–184.
  • Ramos-Murguialday, A., & Birbaumer, N. (2015). Brain oscillatory signatures of motor tasks. Journal of Neurophysiology, 113(10), 3663–3682.
  • Ramos-Murguialday, A., Broetz, D., Rea, M., Läer, L., Yilmaz, O., Brasil, F. L., & Birbaumer, N. (2013). Brain-machine interface in chronic stroke rehabilitation: A controlled study. Annals of Neurology, 74(1), 100–108.
  • Schalk, G., McFarland, D. J., Hinterberger, T., Birbaumer, N., & Wolpaw, J. R. (2004). BCI2000: A general-purpose brain-computer interface (BCI) system. IEEE Transactions on Bio-Medical Engineering, 51(6), 1034–1043.
  • Serruya, M. D., Hatsopoulos, N. G., Paninski, L., Fellows, M. R., & Donoghue, J. P. (2002). Instant neural control of a movement signal. Nature, 416(6877), 141–142.
  • Shadmehr, R., & Mussa-Ivaldi, F. A. (1994). Adaptive representation of dynamics during learning of a motor task. The Journal of Neuroscience, 14(5 Pt 2), 3208–3224.
  • Sitaram, R., Ros, T., Stoeckel, L., Haller, S., Scharnowski, F., Lewis-Peacock, J., & Sulzer, J. (2017). Closed-loop brain training: The science of neurofeedback. Nature Reviews. Neuroscience, 18(2), 86–100.
  • Soekadar, S. R., Witkowski, M., Birbaumer, N., & Cohen, L. G. (2015). Enhancing Hebbian Learning to Control Brain Oscillatory Activity. Cerebral Cortex, 25(9), 2409–2415.
  • Sutton, R., & Barto, A. (1998). Reinforcement learning: An introduction. Cambridge, MA: MIT Press.
  • Takemi, M., Masakado, Y., Liu, M., & Ushiba, J. (2013). Event-related desynchronization reflects downregulation of intracortical inhibition in human primary motor cortex. Journal of Neurophysiology, 110(5), 1158–1166.
  • Takemi, M., Masakado, Y., Liu, M., & Ushiba, J. (2015). Sensorimotor event-related desynchronization represents the excitability of human spinal motoneurons. Neuroscience, 297, 58–67.
  • Truccolo, W., Friehs, G. M., Donoghue, J. P., & Hochberg, L. R. (2008). Primary motor cortex tuning to intended movement kinematics in humans with tetraplegia. The Journal of Neuroscience, 28(5), 1163–1178.
  • Ushiba, J., & Soekadar, S. R. (2016). Brain-machine interfaces for rehabilitation of poststroke hemiplegia. Progress in Brain Research, 228, 163–183.
  • van de Laar, B., Gürkök, H., Plass-Oude Bos, D., Poel, M., & Nijholt, A. (2013). Experiencing BCI control in a popular computer game. IEEE Transactions Comparative Intel and AI in Games, 5(2), 176–184.
  • Vukelić, M., & Gharabaghi, A. (2015). Oscillatory entrainment of the motor cortical network during motor imagery is modulated by the feedback modality. Neuroimage, 111, 1–11.
  • Wagner, J., Solis-Escalante, T., Grieshofer, P., Neuper, C., Müller-Putz, G., & Scherer, R. (2012). Level of participation in robotic-assisted treadmill walking modulates midline sensorimotor EEG rhythms in able-bodied subjects. Neuroimage, 63(3), 1203–1211.
  • Wei, K. L., & Körding, K. (2009). Relevance of error: What drives motor adaptation? Journal of Neurophysiology, 101(2), 655–664.
  • Wolpaw, J. R., & McFarland, D. J. (2004). Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proceedings of the National Academy of Sciences of the United States of America, 101(51), 17849–17854.

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