Table of Contents Author Guidelines Submit a Manuscript
Computational Intelligence and Neuroscience
Volume 2009 (2009), Article ID 279515, 12 pages
http://dx.doi.org/10.1155/2009/279515
Research Article

Changes in EEG Power Spectral Density and Cortical Connectivity in Healthy and Tetraplegic Patients during a Motor Imagery Task

1Department of Electronics, Computer Science and Systems, University of Bologna, Via Venezia 52, 47023 Cesena, Italy
2Department of Human Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
3Istituti di ricovero e cura a carattere scientifico (IRCCS) Fondazione Santa Lucia, 00179 Rome, Italy

Received 12 December 2008; Accepted 8 April 2009

Academic Editor: Andrzej Cichocki

Copyright © 2009 Filippo Cona 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.

Linked References

  1. B. Horwitz, “The elusive concept of brain connectivity,” NeuroImage, vol. 19, no. 2, pp. 466–470, 2003. View at Publisher · View at Google Scholar
  2. L. Astolfi, F. Cincotti, D. Mattia et al., “Estimation of the effective and functional human cortical connectivity with structural equation modeling and directed transfer function applied to high-resolution EEG,” Magnetic Resonance Imaging, vol. 22, no. 10, pp. 1457–1470, 2004. View at Publisher · View at Google Scholar
  3. L. A. Baccalá and K. Sameshima, “Partial directed coherence: a new concept in neural structure determination,” Biological Cybernetics, vol. 84, no. 6, pp. 463–474, 2001. View at Publisher · View at Google Scholar
  4. M. Kamiński, K. Blinowska, and W. Szelenberger, “Investigation of coherence structure and EEG activity propagation during sleep,” Acta Neurobiologiae Experimentalis, vol. 55, no. 3, pp. 213–219, 1995. View at Google Scholar
  5. M. Kamiński, K. Blinowska, and W. Szelenberger, “Topographic analysis of coherence and propagation of EEG activity during sleep and wakefulness,” Electroencephalography and Clinical Neurophysiology, vol. 102, no. 3, pp. 216–227, 1997. View at Publisher · View at Google Scholar
  6. M. Kamiński, M. Ding, W. A. Truccolo, and S. L. Bressler, “Evaluating causal relations in neural systems: granger causality, directed transfer function and statistical assessment of significance,” Biological Cybernetics, vol. 85, no. 2, pp. 145–157, 2001. View at Publisher · View at Google Scholar
  7. M. Kamiński and K. J. Blinowska, “A new method of the description of the information flow in the brain structures,” Biological Cybernetics, vol. 65, no. 3, pp. 203–210, 1991. View at Publisher · View at Google Scholar
  8. A. Korzeniewska, M. G. Mańczak, M. Kamiński, K. J. Blinowska, and S. Kasicki, “Determination of information flow direction among brain structures by a modified directed transfer function (dDTF) method,” Journal of Neuroscience Methods, vol. 125, no. 1-2, pp. 195–207, 2003. View at Publisher · View at Google Scholar
  9. W. J. Freeman, “Models of the dynamics of neural populations,” Electroencephalography and Clinical Neurophysiology, vol. 34, pp. 9–18, 1978. View at Google Scholar
  10. F. H. Lopes da Silva, A. van Rotterdam, P. Barts, E. van Heusden, and W. Burr, “Models of neuronal populations: the basic mechanisms of rhythmicity,” Progress in Brain Research, vol. 45, pp. 281–308, 1976. View at Publisher · View at Google Scholar
  11. B. H. Jansen and V. G. Rit, “Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns,” Biological Cybernetics, vol. 73, no. 4, pp. 357–366, 1995. View at Publisher · View at Google Scholar
  12. F. Wendling, F. Bartolomei, J. J. Bellanger, and P. Chauvel, “Epileptic fast activity can be explained by a model of impaired GABAergic dendritic inhibition,” European Journal of Neuroscience, vol. 15, no. 9, pp. 1499–1508, 2002. View at Publisher · View at Google Scholar
  13. W. J. Freeman, “Simulation of chaotic EEG patterns with a dynamic model of the olfactory system,” Biological Cybernetics, vol. 56, no. 2-3, pp. 139–150, 1987. View at Publisher · View at Google Scholar
  14. F. Wendling, J. J. Bellanger, F. Bartolomei, and P. Chauvel, “Relevance of nonlinear lumped-parameter models in the analysis of depth-EEG epileptic signals,” Biological Cybernetics, vol. 83, no. 4, pp. 367–378, 2000. View at Publisher · View at Google Scholar
  15. O. David and K. J. Friston, “A neural mass model for MEG/EEG: coupling and neuronal dynamics,” NeuroImage, vol. 20, no. 3, pp. 1743–1755, 2003. View at Publisher · View at Google Scholar
  16. R. C. Sotero, N. J. Trujillo-Barreto, Y. Iturria-Medina, F. Carbonell, and J. C. Jimenez, “Realistically coupled neural mass models can generate EEG rhythms,” Neural Computation, vol. 19, no. 2, pp. 478–512, 2007. View at Publisher · View at Google Scholar
  17. R. J. Moran, K. E. Stephan, S. J. Kiebel et al., “Bayesian estimation of synaptic physiology from the spectral responses of neural masses,” NeuroImage, vol. 42, no. 1, pp. 272–284, 2008. View at Publisher · View at Google Scholar
  18. M. Ursino, M. Zavaglia, L. Astolfi, and F. Babiloni, “Use of a neural mass model for the analysis of effective connectivity among cortical regions based on high resolution EEG recordings,” Biological Cybernetics, vol. 96, no. 3, pp. 351–365, 2007. View at Publisher · View at Google Scholar
  19. M. Zavaglia, L. Astolfi, F. Babiloni, and M. Ursino, “A neural mass model for the simulation of cortical activity estimated from high resolution EEG during cognitive or motor tasks,” Journal of Neuroscience Methods, vol. 157, no. 2, pp. 317–329, 2006. View at Publisher · View at Google Scholar
  20. M. Zavaglia, L. Astolfi, F. Babiloni, and M. Ursino, “The effect of connectivity on EEG rhythms, power spectral density and coherence among coupled neural populations: analysis with a neural mass model,” IEEE Transactions on Biomedical Engineering, vol. 55, no. 1, pp. 69–77, 2008. View at Publisher · View at Google Scholar
  21. M. Zavaglia, L. Astolfi, F. Babiloni, and M. Ursino, “A model of rhythm generation and functional connectivity during a simple motor task: preliminary validation with real scalp EEG data,” International Journal of Bioelectromagnetism, vol. 10, no. 1, pp. 68–75, 2008. View at Google Scholar
  22. F. Wendling, A. Hernandez, J.-J. Bellanger, P. Chauvel, and F. Bartolomei, “Interictal to ictal transition in human temporal lobe epilepsy: insights from a computational model of intracerebral EEG,” Journal of Clinical Neurophysiology, vol. 22, no. 5, pp. 343–356, 2005. View at Google Scholar
  23. 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. View at Publisher · View at Google Scholar
  24. P. D. Welch, “The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms,” IEEE Transactions on Audio and Electroacoustics, vol. 15, no. 2, pp. 70–73, 1967. View at Publisher · View at Google Scholar
  25. R. C. Oldfield, “The assessment and analysis of handedness: the Edinburgh inventory,” Neuropsychologia, vol. 9, no. 1, pp. 97–113, 1971. View at Publisher · View at Google Scholar
  26. S. Salenius and R. Hari, “Synchronous cortical oscillatory activity during motor action,” Current Opinion in Neurobiology, vol. 13, no. 6, pp. 678–684, 2003. View at Publisher · View at Google Scholar
  27. J. Holland, Adaptation in Natural and Articial Systems, University of Michigan Press, Ann Arbor, Mich, USA, 1975.
  28. K. E. Stephan, L. M. Harrison, S. J. Kiebel, O. David, W. D. Penny, and K. J. Friston, “Dynamic causal models of neural system dynamics: current state and future extensions,” Journal of Biosciences, vol. 32, no. 1, pp. 129–144, 2007. View at Publisher · View at Google Scholar
  29. O. David, S. J. Kiebel, L. M. Harrison, J. Mattout, J. M. Kilner, and K. J. Friston, “Dynamic causal modeling of evoked responses in EEG and MEG,” NeuroImage, vol. 30, no. 4, pp. 1255–1272, 2006. View at Publisher · View at Google Scholar
  30. D. T. J. Liley and I. Bojak, “Understanding the transition to seizure by modeling the epileptiform activity of general anesthetic agents,” Journal of Clinical Neurophysiology, vol. 22, no. 5, pp. 300–313, 2005. View at Google Scholar
  31. J. B. Rowe, K. E. Stephan, K. Friston, R. S. J. Frackowiak, and R. E. Passingham, “The prefrontal cortex shows context-specific changes in effective connectivity to motor or visual cortex during the selection of action or colour,” Cerebral Cortex, vol. 15, no. 1, pp. 85–95, 2005. View at Publisher · View at Google Scholar
  32. G. Buzsàki, Rhythms of the Brain, Oxford University Press, New York, NY, USA, 2006.
  33. L. M. Ward, “Synchronous neural oscillations and cognitive processes,” Trends in Cognitive Sciences, vol. 7, no. 12, pp. 553–559, 2003. View at Publisher · View at Google Scholar
  34. H. Shibasaki and M. Hallett, “What is the Bereitschaftspotential?” Clinical Neurophysiology, vol. 117, no. 11, pp. 2341–2356, 2006. View at Publisher · View at Google Scholar
  35. T. Paus, “Primate anterior cingulate cortex: where motor control, drive and cognition interface,” Nature Reviews Neuroscience, vol. 2, no. 6, pp. 417–424, 2001. View at Publisher · View at Google Scholar
  36. N. Picard and P. L. Strick, “Motor areas of the medial wall: a review of their location and functional activation,” Cerebral Cortex, vol. 6, no. 3, pp. 342–353, 1996. View at Publisher · View at Google Scholar
  37. M. I. Posner, M. K. Rothbart, B. E. Sheese, and Y. Tang, “The anterior cingulate gyrus and the mechanism of self-regulation,” Cognitive, Affective & Behavioral Neuroscience, vol. 7, no. 4, pp. 391–395, 2007. View at Publisher · View at Google Scholar
  38. A. Stancák Jr. and G. Pfurtscheller, “Event-related desynchronisation of central beta-rhythms during brisk and slow self-paced finger movements of dominant and nondominant hand,” Cognitive Brain Research, vol. 4, no. 3, pp. 171–183, 1996. View at Publisher · View at Google Scholar
  39. C. M. Gómez, J. Marco-Pallarés, and C. Grau, “Location of brain rhythms and their modulation by preparatory attention estimated by current density,” Brain Research, vol. 1107, no. 1, pp. 151–160, 2006. View at Publisher · View at Google Scholar
  40. C. Neuper and G. Pfurtscheller, “Evidence for distinct beta resonance frequencies in human EEG related to specific sensorimotor cortical areas,” Clinical Neurophysiology, vol. 112, no. 11, pp. 2084–2097, 2001. View at Publisher · View at Google Scholar
  41. F. H. Lopes da Silva, J. E. Vos, J. Mooibroek, and A. van Rotterdam, “Relative contributions of intracortical and thalamo-cortical processes in the generation of alpha rhythms, revealed by partial coherence analysis,” Electroencephalography and Clinical Neurophysiology, vol. 50, no. 5-6, pp. 449–456, 1980. View at Publisher · View at Google Scholar
  42. Y. Gutfreund, Y. Yarom, and I. Segev, “Subthreshold oscillations and resonant frequency in guinea-pig cortical neurons: physiology and modelling,” The Journal of Physiology, vol. 483, part 3, pp. 621–640, 1995. View at Google Scholar
  43. R. R. Llinás, A. A. Grace, and Y. Yarom, “In vitro neurons in mammalian cortical layer 4 exhibit intrinsic oscillatory activity in the 10- to 50-Hz frequency range,” Proceedings of the National Academy of Sciences of the United States of America, vol. 88, no. 3, pp. 897–901, 1991. View at Publisher · View at Google Scholar
  44. J. G. R. Jefferys, R. D. Traub, and M. A. Whittington, “Neuronal networks for induced ‘40 Hz’ rhythms,” Trends in Neurosciences, vol. 19, no. 5, pp. 202–208, 1996. View at Publisher · View at Google Scholar
  45. K. J. Friston, L. Harrison, and W. Penny, “Dynamic causal modelling,” NeuroImage, vol. 19, no. 4, pp. 1273–1302, 2003. View at Publisher · View at Google Scholar
  46. F. de Vico Fallani, L. Astolfi, F. Cincotti et al., “Brain network analysis from high-resolution EEG recordings by the application of theoretical graph indexes,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 16, no. 5, pp. 442–452, 2008. View at Publisher · View at Google Scholar
  47. D. Mattia, F. Cincotti, L. Astolfi et al., “Motor cortical responsiveness to attempted movements in tetraplegia: evidence from neuroelectrical imaging,” Clinical Neurophysiology, vol. 120, no. 1, pp. 181–189, 2009. View at Publisher · View at Google Scholar
  48. P. J. Roback and R. A. Askins, “Judicious use of multiple hypothesis tests,” Conservation Biology, vol. 19, no. 1, pp. 261–267, 2005. View at Publisher · View at Google Scholar
  49. R. D. Traub, A. Bibbig, A. Fisahn, F. E. N. Lebeau, M. A. Whittington, and E. H. Buhl, “A model of gamma-frequency network oscillations induced in the rat CA3 region by carbachol in vitro,” European Journal of Neuroscience, vol. 12, no. 11, pp. 4093–4106, 2000. View at Publisher · View at Google Scholar
  50. K. J. Friston, W. Penny, C. Phillips, S. Kiebel, G. Hinton, and J. Ashburner, “Classical and Bayesian inference in neuroimaging: theory,” NeuroImage, vol. 16, no. 2, pp. 465–483, 2002. View at Publisher · View at Google Scholar