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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationBIOSIGNALS 2011 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing
Pages91-97
Number of pages7
Publication statusPublished - 2011
EventInternational Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2011 - Rome, Italy
Duration: Jan 26 2011Jan 29 2011

Other

OtherInternational Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2011
CountryItaly
CityRome
Period1/26/111/29/11

Keywords

  • Functional connectivity
  • High resolution EEG
  • MEG
  • Neuromarketing
  • SSVEP

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering

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  • Cite this

    Vecchiato, G., Astolfi, L., De Vico Fallani, F., Toppi, J., Aloise, F., Cincotti, F., Mattia, D., & Babiloni, F. (2011). Understanding cerebral activations in neuromarketing: A neuroelectrical perspective. In BIOSIGNALS 2011 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing (pp. 91-97)