Cortical network topology during successful memory encoding in a lifelike experiment

F. De Vico Fallani, L. Astolfi, F. Cincotti, D. Mattia, R. Soranzo, S. Salinari, M. G. Marciani, A. Colosimo, F. Babiloni

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

Abstract

In the present work, we estimated the functional networks in the frequency domain from a set of high-resolution EEG data in a group of healthy subjects during the showing of commercial spots within a neutral documentary. Then, we evaluated the differences in the cortical network associated with later remembered and not-remembered commercials by calculating the global-E g and local-efficiency El indexes. During the visualization of the video-clips that will be forgotten (FRG), the cortical network exhibited high values of globaland local-efficiency, reflecting a small-world configuration. During the visualization of the video-clips that will be remembered (RMB), the same indexes appeared significantly lower. Such a difference seems not depending on the spectral content of the cortical activity. This result shows how the network communication efficiency would be affected by the presence of attentional and semantic processes that are behind a successful memory encoding in a lifelike situation.

Original languageEnglish
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"
Pages4007-4010
Number of pages4
Publication statusPublished - 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: Aug 20 2008Aug 25 2008

Other

Other30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
CountryCanada
CityVancouver, BC
Period8/20/088/25/08

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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