- About this Journal
- Abstracting and Indexing
- Aims and Scope
- Article Processing Charges
- Articles in Press
- Author Guidelines
- Bibliographic Information
- Citations to this Journal
- Contact Information
- Editorial Board
- Editorial Workflow
- Free eTOC Alerts
- Publication Ethics
- Reviewers Acknowledgment
- Submit a Manuscript
- Subscription Information
- Table of Contents
Advances in Human-Computer Interaction
Volume 2012 (2012), Article ID 127627, 10 pages
Source Detection and Functional Connectivity of the Sensorimotor Cortex during Actual and Imaginary Limb Movement: A Preliminary Study on the Implementation of eConnectome in Motor Imagery Protocols
Lab of Medical Informatics, Medical School, Aristotle University of Thessaloniki (AUTH), 54124 Thessaloniki, Greece
Received 6 July 2012; Revised 29 November 2012; Accepted 29 November 2012
Academic Editor: Christos Papadelis
Copyright © 2012 Alkinoos Athanasiou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- J. Decety and D. H. Ingvar, “Brain structures participating in mental simulation of motor behavior: a neuropsychological interpretation,” Acta Psychologica, vol. 73, no. 1, pp. 13–34, 1990.
- A. Athanasiou and P. D. Bamidis, “A review on brain computer interfaces: contemporary achievements and future goals towards movement restoration,” Aristotle University Medical Journal, vol. 37, no. 3, pp. 35–44, 2010.
- R. Sitaram, A. Caria, R. Veit et al., “FMRI brain-computer interface: a tool for neuroscientific research and treatment,” Computational Intelligence and Neuroscience, vol. 2007, Article ID 25487, 10 pages, 2007.
- G. Pfurtscheller and C. Neuper, “Motor imagery activates primary sensorimotor area in humans,” Neuroscience Letters, vol. 239, no. 2-3, pp. 65–68, 1997.
- S. Arroyo, R. P. Lesser, B. Gordon, S. Uematsu, D. Jackson, and R. Webber, “Functional significance of the mu rhythm of human cortex: an electrophysiologic study with subdural electrodes,” Electroencephalography and Clinical Neurophysiology, vol. 87, no. 3, pp. 76–87, 1993.
- C. Neuper, R. Scherer, S. Wriessnegger, and G. Pfurtscheller, “Motor imagery and action observation: modulation of sensorimotor brain rhythms during mental control of a brain-computer interface,” Clinical Neurophysiology, vol. 120, no. 2, pp. 239–247, 2009.
- E. V. C. Friedrich, D. J. McFarland, C. Neuper, T. M. Vaughan, P. Brunner, and J. R. Wolpaw, “A scanning protocol for a sensorimotor rhythm-based brain-computer interface,” Biological Psychology, vol. 80, no. 2, pp. 169–175, 2009.
- J. Zhou, J. Yao, J. Deng, and J. P. A. Dewald, “EEG-based classification for elbow versus shoulder torque intentions involving stroke subjects,” Computers in Biology and Medicine, vol. 39, no. 5, pp. 443–452, 2009.
- V. Morash, O. Bai, S. Furlani, P. Lin, and M. Hallett, “Classifying EEG signals preceding right hand, left hand, tongue, and right foot movements and motor imageries,” Clinical Neurophysiology, vol. 119, no. 11, pp. 2570–2578, 2008.
- L. Astolfi, H. Bakardjian, F. Cincotti et al., “Estimate of causality between independent cortical spatial patterns during movement volition in spinal cord injured patients,” Brain Topography, vol. 19, no. 3, pp. 107–123, 2007.
- A. A. Ioannides, “Dynamic functional connectivity,” Current Opinion in Neurobiology, vol. 17, no. 2, pp. 161–170, 2007.
- F. Varela, J. P. Lachaux, E. Rodriguez, and J. Martinerie, “The brainweb: phase synchronization and large-scale integration,” Nature Reviews Neuroscience, vol. 2, no. 4, pp. 229–239, 2001.
- K. J. Friston, “Functional and effective connectivity in neuroimaging: a synthesis,” Human Brain Mapping, vol. 2, no. 1-2, pp. 56–78, 1994.
- C. W. J. Granger, “Investigating causal relations by econometric models and cross spectra methods,” Econometrica, vol. 37, pp. 424–438, 1969.
- F. de Vico Fallani, L. Astolfi, F. Cincotti et al., “Cortical functional connectivity networks in normal and spinal cord injured patients: evaluation by graph analysis,” Human Brain Mapping, vol. 28, no. 12, pp. 1334–1346, 2007.
- B. He, Y. Dai, L. Astolfi, F. Babiloni, H. Yuan, and L. Yang, “eConnectome: a MATLAB toolbox for mapping and imaging of brain functional connectivity,” Journal of Neuroscience Methods, vol. 195, no. 2, pp. 261–269, 2011.
- A. Athanasiou, E. Chatzitheodorou, K. Kalogianni, C. Lithari, I. Moulos, and P. D. Bamidis, “Comparing sensorimotor cortex activation during actual and imaginary movement,” in Proceedings of the 12th Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON '10), vol. 29 of IFMBE Proceedings, pp. 111–114, Chalkidiki, Greece, May 2010.
- A. Delorme and S. Makeig, “EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis,” Journal of Neuroscience Methods, vol. 134, no. 1, pp. 9–21, 2004.
- A. M. Dale and M. I. Sereno, “Improved localization of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: a linear approach,” Journal of Cognitive Neuroscience, vol. 5, no. 2, pp. 162–176, 1993.
- P. A. Valdés-Hernández, N. von Ellenrieder, A. Ojeda-Gonzalez, et al., “Approximate average head models for EEG source imaging,” Journal of Neuroscience Methods, vol. 185, no. 1, pp. 125–132, 2009.
- F. Babiloni, F. Cincotti, C. Babiloni et al., “Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function,” NeuroImage, vol. 24, no. 1, pp. 118–131, 2005.
- C. Wilke, L. Ding, and B. He, “Estimation of time-varying connectivity patterns through the use of an adaptive directed transfer function,” IEEE Transactions on Biomedical Engineering, vol. 55, no. 11, pp. 2557–2564, 2008.
- R. Oostenveld and P. Praamstra, “The five percent electrode system for high-resolution EEG and ERP measurements,” Clinical Neurophysiology, vol. 112, no. 4, pp. 713–719, 2001.
- R. Scherer, A. Schloegl, F. Lee, H. Bischof, J. Janša, and G. Pfurtscheller, “The self-paced graz brain-computer interface: methods and applications,” Computational Intelligence and Neuroscience, vol. 2007, Article ID 79826, 9 pages, 2007.
- D. J. Krusienski, G. Schalk, D. J. McFarland, and J. R. Wolpaw, “A -rhythm matched filter for continuous control of a brain-computer interface,” IEEE Transactions in Biomedical Engineering, vol. 54, no. 2, pp. 273–280, 2007.
- F. Pichiorri, F. De Vico Fallani, F. Cincotti et al., “Sensorimotor rhythm-based brain-computer interface training: the impact on motor cortical responsiveness,” Journal of Neural Engineering, vol. 8, no. 2, Article ID 025020, 2011.
- S. H. Jin, P. Lin, and M. Hallet, “Reorganization of brain functional small-world networks during finger movements,” Human Brain Mapping, vol. 33, no. 4, pp. 861–872, 2012.
- F. Wendling, K. Ansari-Asl, F. Bartolomei, and L. Senhadji, “From EEG signals to brain connectivity: a model-based evaluation of interdependence measures,” Journal of Neuroscience Methods, vol. 183, no. 1, pp. 9–18, 2009.
- T. Li, J. Hong, and J. Zhang, “Electroencephalographic (EEG) control of cursor movement in three-dimensional scene based on small-world neural network,” in Proceedings of the IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS '10), vol. 3, pp. 587–591, Xiamen, China, October 2010.