Advanced methods for time-varying effective connectivity estimation in memory processes

L. Astolfi, J. Toppi, G. Wood, S. Kober, M. Risetti, L. Macchiusi, S. Salinari, F. Babiloni, D. Mattia

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

Abstract

Memory processes are based on large cortical networks characterized by non-stationary properties and time scales which represent a limitation to the traditional connectivity estimation methods. The recent development of connectivity approaches able to consistently describe the temporal evolution of large dimension connectivity networks, in a fully multivariate way, represents a tool that can be used to extract novel information about the processes at the basis of memory functions. In this paper, we applied such advanced approach in combination with the use of state-of-the-art graph theory indexes, computed on the connectivity networks estimated from high density electroencephalographic (EEG) data recorded in a group of healthy adults during the Sternberg Task. The results show how this approach is able to return a characterization of the main phases of the investigated memory task which is also sensitive to the increased length of the numerical string to be memorized.

Original languageEnglish
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages2936-2939
Number of pages4
DOIs
Publication statusPublished - 2013
Event2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan
Duration: Jul 3 2013Jul 7 2013

Other

Other2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
CountryJapan
CityOsaka
Period7/3/137/7/13

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Advanced methods for time-varying effective connectivity estimation in memory processes'. Together they form a unique fingerprint.

  • Cite this

    Astolfi, L., Toppi, J., Wood, G., Kober, S., Risetti, M., Macchiusi, L., Salinari, S., Babiloni, F., & Mattia, D. (2013). Advanced methods for time-varying effective connectivity estimation in memory processes. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 2936-2939). [6610155] https://doi.org/10.1109/EMBC.2013.6610155