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Computational Intelligence and Neuroscience
Volume 2010 (2010), Article ID 985867, 7 pages
doi:10.1155/2010/985867
Research Article

EEG Analysis of the Brain Activity during the Observation of Commercial, Political, or Public Service Announcements

Giovanni Vecchiato,1,2 Laura Astolfi,1,2,3 Alessandro Tabarrini,2,3 Serenella Salinari,3 Donatella Mattia,2 Febo Cincotti,2 Luigi Bianchi,2 Domenica Sorrentino,2 Fabio Aloise,2 Ramon Soranzo,1 and Fabio Babiloni1,2

1Department of Physiology and Pharmacology, University of Rome “Sapienza”, P.le A. Moro 5, 00185 Rome, Italy
2IRCCS Fondazione Santa Lucia, Laboratory of Neuroelectrical Imaging, Via Ardeatina 354, 00179 Rome, Italy
3Department of Computer Science and Informatics, University of Rome “Sapienza”, Via Ariosto 25, 00100 Rome, Italy

Received 24 July 2009; Accepted 29 September 2009

Academic Editor: Fabrizio De Vico Fallani

Copyright © 2010 Giovanni Vecchiato 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. P. L. Nunez, Electric Fields of the Brain: The Neurophysics of EEG, Oxford University Press, New York, NY, USA, 1981.
  2. P. L. Nunez, Neocortical Dynamics and Human EEG Rhythms, Oxford University Press, New York, NY, USA, 1995.
  3. F. De Vico Fallani, L. Astolfi, F. Cincotti, et al., “Cortical network topology during successful memory encoding in a lifelike experiment,” in Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS '08), pp. 4007–4010, 2008. View at Scopus
  4. T. Ambler, S. Braeutigam, J. Stins, S. P. R. Rose, and S. Swithenby, “Salience and choice: neural correlates of shopping decisions,” Psychology and Marketing, vol. 21, no. 4, pp. 247–261, 2004. View at Publisher · View at Google Scholar · View at Scopus
  5. S. Braeutigam, S. P. R. Rose, S. J. Swithenby, and T. Ambler, “The distributed neuronal systems supporting choice-making in real-life situations: differences between men and women when choosing groceries detected using magnetoencephalography,” European Journal of Neuroscience, vol. 20, no. 1, pp. 293–302, 2004. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  6. J. Cappo, The Future of Advertising: New Media, New Clients, New Consumers in the Post-Television Age, McGraw-Hill, New York, NY, USA, 2005.
  7. H. E. Krugman, “Brain wave measures of media involvement,” Journal of Advertising Research, vol. 11, pp. 3–10, 1971.
  8. A. A. Ioannides, L. Liu, D. Theofilou, et al., “Real time processing of affective and cognitive stimuli in the human brain extracted from MEG signals,” Brain Topography, vol. 13, no. 1, pp. 11–19, 2000. View at Publisher · View at Google Scholar · View at Scopus
  9. T. Ambler and T. Burne, “The impact of affect on memory of advertising,” Journal of Advertising Research, vol. 39, no. 2, pp. 25–34, 1999. View at Scopus
  10. M. Rotschild and J. Hyun, “Predicting memory for components of TV commercials from EEC,” Journal of Consumer Research, pp. 72–78, 1989.
  11. J. R. Rossiter, R. B. Silberstein, P. G. Harris, and G. A. Nield, “Brain-imaging detection of visual scene encoding in long-term memory for TV commercials,” Journal of Advertising Research, vol. 41, no. 2, pp. 13–21, 2001. View at Scopus
  12. C. Young, “Brain waves, picture sorts®, and branding moments,” Journal of Advertising Research, vol. 42, no. 4, pp. 42–53, 2002. View at Scopus
  13. Sands Research, http://sandsresearch.com/.
  14. Emory University, Centre For Neuropolicy, http://www.neuropolicy.emory.edu/.
  15. L. Biener, J. E. Harris, and W. Hamilton, “Impact of the Massachusetts tobacco control programme: Population based trend analysis,” British Medical Journal, vol. 321, pp. 351–354, 2000.
  16. S. Emery, M. Wakefield, Y. Terry-McElrath, G. Szczypka, P. M. O'Malley, L. D. Johnston, et al., “Televised state-sponsored anti-tobacco advertising and youth smoking beliefs and behavior in the United States, 1999–2000,” Archives Pediatric Adolescent Medicine, vol. 159, pp. 639–645, 2005.
  17. M. Wakefield, B. Flay, M. Nichter, and G. Giovino, “Effects of anti-smoking advertising on youth smoking: a review,” Journal of Health Communication, vol. 8, pp. 229–247, 2003. View at Publisher · View at Google Scholar
  18. L. Astolfi, F. De Vico Fallani, S. Salinari, et al., “Brain activity related to the memorization of TV commercials,” International Journal of Bioelectromegnetism, vol. 10, no. 3, pp. 1–10, 2008.
  19. J. Le and A. Gevins, “Method to reduce blur distortion from EEG's using a realistic head model,” IEEE Transactions on Biomedical Engineering, vol. 40, no. 6, pp. 517–528, 1993. View at Publisher · View at Google Scholar · View at PubMed
  20. A. Gevins, J. Le, N. K. Martin, P. Brickett, J. Desmond, and B. Reutter, “High resolution EEG: 124-channel recording, spatial deblurring and MRI integration methods,” Electroencephalography and Clinical Neurophysiology, vol. 90, no. 5, pp. 337–358, 1994. View at Publisher · View at Google Scholar
  21. F. Babiloni, C. Babiloni, F. Carducci, et al., “High resolution EEG: a new model-dependent spatial deblurring method using a realistically-shaped MR-constructed subject's head model,” Electroencephalography and Clinical Neurophysiology, vol. 102, no. 2, pp. 69–80, 1997. View at Publisher · View at Google Scholar
  22. F. Babiloni, C. Babiloni, L. Locche, F. Cincotti, P. M. Rossini, and F. Carducci, “High-resolution electro-encephalogram: source estimates of Laplacian-transformed somatosensory-evoked potentials using a realistic subject head model constructed from magnetic resonance images,” Medical and Biological Engineering and Computing, vol. 38, no. 5, pp. 512–519, 2000.
  23. A. M. Dale, A. K. Liu, B. R. Fischl, et al., “Dynamic statistical parametric mapping: combining fMRI and MEG for high-resolution imaging of cortical activity,” Neuron, vol. 26, no. 1, pp. 55–67, 2000.
  24. R. Grave de Peralta Menendez and S. L. Gonzalez Andino, “Distributed source models: standard solutions and new developments,” in Analysis of Neurophysiological Brain Functioning, C. Uhl, Ed., pp. 176–201, Springer, New York, NY, USA, 1999.
  25. L. Astolfi, F. Cincotti, D. Mattia, et al., “Comparison of different cortical connectivity estimators for high-resolution EEG recordings,” Human Brain Mapping, vol. 28, no. 2, pp. 143–157, 2006. View at Publisher · View at Google Scholar · View at PubMed
  26. 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 · View at PubMed
  27. W. Klimesch, M. Doppelmayr, and S. Hanslmayr, “Upper alpha ERD and absolute power: their meaning for memory performance,” Progress in Brain Research, vol. 159, pp. 151–165, 2006. View at Publisher · View at Google Scholar · View at PubMed
  28. A. Todorov, A. N. Mandisodza, A. Goren, and C. C. Hall, “Inferences of competence from faces predict election outcomes,” Science, vol. 308, pp. 1623–1626, 2005.
  29. C. C. Ballew II and A. Todorov, “Predicting political elections from rapid and unreflective face judgments,” Proceedings of the National Academy of Sciences of the United States of America, vol. 104, no. 46, pp. 17948–17953, 2007. View at Publisher · View at Google Scholar · View at PubMed
  30. M. Iacoboni, J. Freedman, J. Kaplan, et al., “This is your brain on politics,” The New York Times, November 2007, http://www.nytimes.com/2007/11/11/opinion/11freedman.html?pagewanted=1&_r=2&sq=marco%20iacoboni&st=cse&scp=8.
  31. 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. View at Publisher · View at Google Scholar · View at PubMed
  32. L. Astolfi, F. De Vico Fallani, F. Cincotti, et al., “Imaging functional brain connectivity patterns from high-resolution EEG and fMRI via graph theory,” Psychophysiology, vol. 44, no. 6, pp. 880–893, 2007. View at Publisher · View at Google Scholar · View at PubMed
  33. L. Astolfi, F. Cincotti, D. Mattia, et al., “Tracking the time-varying cortical connectivity patterns by adaptive multivariate estimators,” IEEE Transactions on Biomedical Engineering, vol. 55, no. 3, pp. 902–913, 2008. View at Publisher · View at Google Scholar · View at PubMed
  34. M. Oliveri, C. Babiloni, M. M. Filippi, et al., “Influence of the supplementary motor area on primary motor cortex excitability during movements triggered by neutral or emotionally unpleasant visual cues,” Experimental Brain Research, vol. 149, no. 2, pp. 214–221, 2003.
  35. C. Babiloni, F. Babiloni, F. Carducci, et al., “Mapping of early and late human somatosensory evoked brain potentials to phasic galvanic painful stimulation,” Human Brain Mapping, vol. 12, no. 3, pp. 168–179, 2001. View at Publisher · View at Google Scholar
  36. A. Urbano, C. Babiloni, P. Onorati, and F. Babiloni, “Dynamic functional coupling of high resolution EEG potentials related to unilateral internally triggered one-digit movements,” Electroencephalography and Clinical Neurophysiology, vol. 106, no. 6, pp. 477–487, 1998. View at Publisher · View at Google Scholar