UNDERSTANDING CEREBRAL ACTIVATIONS IN NEUROMARKETING - A Neuroelectrical Perspective

Giovanni Vecchiato, Laura Astolfi, Fabrizio De Vico Fallani, Jlenia Toppi, Fabio Aloise, Febo Cincotti, Donatella Mattia, Fabio Babiloni

Abstract

This paper aims to be a survey of recent experiments performed in the Neuromarketing field. Our purpose is to illustrate results obtained by employing the popular tools of investigation well known in the international neuroelectrical community such as the MEG, High Resolution EEG techniques and steady-state visually evoked potentials. By means of temporal and frequency patterns of cortical activations we intend to show how the neuroscientific community is nowadays sensible to the needs of companies and, at the same time, how the same tools are able to retrieve hidden information about the demands of consumers. These instruments could be of help both in pre- and post-design stage of a product, or a service, that a marketer is going to promote.

References

  1. Aftanas, L.I. et al., 2004. Analysis of evoked EEG synchronization and desynchronization in conditions of emotional activation in humans: temporal and topographic characteristics. Neuroscience and Behavioral Physiology, 34(8), 859-867.
  2. Astolfi, L. et al., 2005. Assessing cortical functional connectivity by linear inverse estimation and directed transfer function: simulations and application to real data. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 116(4), 920-932.
  3. Astolfi, L. et al., 2007. Imaging functional brain connectivity patterns from high-resolution EEG and fMRI via graph theory. Psychophysiology, 44(6), 880- 893.
  4. Astolfi, L. et al., 2004. 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, 22(10), 1457-1470.
  5. Astolfi, L. et al., 2008. Neural basis for brain responses to TV commercials: a high-resolution EEG study. IEEE Transactions on Neural Systems and Rehabilitation Engineering: A Publication of the IEEE Engineering in Medicine and Biology Society, 16(6), 522-531.
  6. Astolfi, L. et al., 2009. The track of brain activity during the observation of TV commercials with the highresolution EEG technology. Computational Intelligence and Neuroscience, 652078.
  7. Babiloni, F. et al., 2000. High-resolution electroencephalogram: source estimates of Laplaciantransformed somatosensory-evoked potentials using a realistic subject head model constructed from magnetic resonance images. Medical & Biological Engineering & Computing, 38(5), 512-519.
  8. Braeutigam, S. et al., 2001. Magnetoencephalographic signals identify stages in real-life decision processes. Neural Plasticity, 8(4), 241-254.
  9. Braeutigam, S., 2005. Neuroeconomics--from neural systems to economic behaviour. Brain Research Bulletin, 67(5), 355-360.
  10. Braeutigam, S. et al., 2004. The distributed neuronal systems supporting choice-making in real-life situations: differences between men and women when choosing groceries detected using magnetoencephalography. The European Journal of Neuroscience, 20(1), 293-302.
  11. Cahill, L. et al., 1996. Amygdala activity at encoding correlated with long-term, free recall of emotional information. Proceedings of the National Academy of Sciences of the United States of America, 93(15), 8016-8021.
  12. De Vico Fallani, F. et al., 2008. Structure of the cortical networks during successful memory encoding in TV commercials. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 119(10), 2231-2237.
  13. Grabenhorst, F., Rolls, E.T. & Parris, B.A., 2008. From affective value to decision-making in the prefrontal cortex. The European Journal of Neuroscience, 28(9), 1930-1939.
  14. Habib, R., Nyberg, L. & Tulving, E., 2003. Hemispheric asymmetries of memory: the HERA model revisited. Trends in Cognitive Sciences, 7(6), 241-245.
  15. Ioannides, A.A. et al., 2000. Real time processing of affective and cognitive stimuli in the human brain extracted from MEG signals. Brain Topography, 13(1), 11-19.
  16. Kimura, D., 1996. Sex, sexual orientation and sex hormones influence human cognitive function. Current Opinion in Neurobiology, 6(2), 259-263.
  17. Maddock, R.J., 1999. The retrosplenial cortex and emotion: new insights from functional neuroimaging of the human brain. Trends in Neurosciences, 22(7), 310-316.
  18. McClure, S.M. et al., 2004. Neural correlates of behavioral preference for culturally familiar drinks. Neuron, 44(2), 379-387.
  19. Silberstein, 1995. Steady State Visually Evoked Potentials, Brain Resonances and Cognitive Processes. In Neocortical Dynamics and Human EEG Rhythms. Oxford University Press.
  20. Silberstein, R.B. et al., 2000. Frontal steady-state potential changes predict long-term recognition memory performance. International Journal of Psychophysiology: Official Journal of the International Organization of Psychophysiology, 39(1), 79-85.
  21. Silberstein, R.B. et al., 1990. Steady-state visually evoked potential topography associated with a visual vigilance task. Brain Topography, 3(2), 337-347.
  22. Summerfield, C. & Mangels, J.A., 2005. Coherent thetaband EEG activity predicts item-context binding during encoding. NeuroImage, 24(3), 692-703.
  23. Tulving, E. et al., 1994. Hemispheric encoding/retrieval asymmetry in episodic memory: positron emission tomography findings. Proceedings of the National Academy of Sciences of the United States of America, 91(6), 2016-2020.
  24. Vecchiato, G. et al., 2010. Changes in brain activity during the observation of TV commercials by using EEG, GSR and HR measurements. Brain Topography, 23(2), 165-179.
  25. Werkle-Bergner, M. et al., 2006. Cortical EEG correlates of successful memory encoding: implications for lifespan comparisons. Neuroscience and Biobehavioral Reviews, 30(6), 839-854.
Download


Paper Citation


in Harvard Style

Vecchiato G., Astolfi L., De Vico Fallani F., Toppi J., Aloise F., Cincotti F., Mattia D. and Babiloni F. (2011). UNDERSTANDING CEREBRAL ACTIVATIONS IN NEUROMARKETING - A Neuroelectrical Perspective . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011) ISBN 978-989-8425-35-5, pages 91-97. DOI: 10.5220/0003354900910097


in Bibtex Style

@conference{biosignals11,
author={Giovanni Vecchiato and Laura Astolfi and Fabrizio De Vico Fallani and Jlenia Toppi and Fabio Aloise and Febo Cincotti and Donatella Mattia and Fabio Babiloni},
title={UNDERSTANDING CEREBRAL ACTIVATIONS IN NEUROMARKETING - A Neuroelectrical Perspective},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)},
year={2011},
pages={91-97},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003354900910097},
isbn={978-989-8425-35-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2011)
TI - UNDERSTANDING CEREBRAL ACTIVATIONS IN NEUROMARKETING - A Neuroelectrical Perspective
SN - 978-989-8425-35-5
AU - Vecchiato G.
AU - Astolfi L.
AU - De Vico Fallani F.
AU - Toppi J.
AU - Aloise F.
AU - Cincotti F.
AU - Mattia D.
AU - Babiloni F.
PY - 2011
SP - 91
EP - 97
DO - 10.5220/0003354900910097