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

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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.

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Graph theory

ASJC Scopus subject areas

  • Medicine(all)

Cite this

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title = "Advanced methods for time-varying effective connectivity estimation in memory processes",
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.",
author = "L. Astolfi and J. Toppi and G. Wood and S. Kober and M. Risetti and L. Macchiusi and S. Salinari and F. Babiloni and D. Mattia",
year = "2013",
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pages = "2936--2939",
journal = "Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference",
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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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T1 - Advanced methods for time-varying effective connectivity estimation in memory processes

AU - Astolfi, L.

AU - Toppi, J.

AU - Wood, G.

AU - Kober, S.

AU - Risetti, M.

AU - Macchiusi, L.

AU - Salinari, S.

AU - Babiloni, F.

AU - Mattia, D.

PY - 2013

Y1 - 2013

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