Brain Topography

, Volume 19, Issue 3, pp 107–123

Estimate of Causality Between Independent Cortical Spatial Patterns During Movement Volition in Spinal Cord Injured Patients

Authors

  • Laura Astolfi
    • IRCCS “Fondazione Santa Lucia”
    • Department of Informatica e SistemisticaUniversity of Rome “La Sapienza”
  • Hovagim Bakardjian
    • Laboratory for Advanced Brain Signal ProcessingRiken Brain Science Institute
  • Febo Cincotti
    • IRCCS “Fondazione Santa Lucia”
  • Donatella Mattia
    • IRCCS “Fondazione Santa Lucia”
  • Maria Grazia Marciani
    • IRCCS “Fondazione Santa Lucia”
  • Fabrizio De Vico Fallani
    • IRCCS “Fondazione Santa Lucia”
    • Centro di Ricerca de “La Sapienza” per l’Analisi dei Modelli e dell’Informazione nei Sistemi Biomedici
  • Alfredo Colosimo
    • Centro di Ricerca de “La Sapienza” per l’Analisi dei Modelli e dell’Informazione nei Sistemi Biomedici
  • Serenella Salinari
    • Department of Informatica e SistemisticaUniversity of Rome “La Sapienza”
  • Fumikazu Miwakeichi
    • Laboratory for Dynamics of Emergent IntelligenceRiken Brain Science Institute
  • Yoko Yamaguchi
    • Department of Medical System Engineering, Faculty of EngineeringChiba University
  • Pablo Martinez
    • Laboratory for Advanced Brain Signal ProcessingRiken Brain Science Institute
  • Andrzej Cichocki
    • Laboratory for Advanced Brain Signal ProcessingRiken Brain Science Institute
  • Andrea Tocci
    • Department of Informatica e SistemisticaUniversity of Rome “La Sapienza”
    • IRCCS “Fondazione Santa Lucia”
    • Dipartimento di Fisiologia umana e FarmacologiaUniversity of Rome “La Sapienza”
    • Department of Human Physiology and PharmacologyUniversity of Rome “La Sapienza”
Original Paper

DOI: 10.1007/s10548-007-0018-1

Cite this article as:
Astolfi, L., Bakardjian, H., Cincotti, F. et al. Brain Topogr (2007) 19: 107. doi:10.1007/s10548-007-0018-1

Abstract

Static hemodynamic or neuroelectric images of brain regions activated during particular tasks do not convey the information of how these regions communicate to each other. Cortical connectivity estimation aims at describing these interactions as connectivity patterns which hold the direction and strength of the information flow between cortical areas. In this study, we attempted to estimate the causality between distributed cortical systems during a movement volition task in preparation for execution of simple movements by a group of normal healthy subjects and by a group of Spinal Cord Injured (SCI) patients. To estimate the causality between the spatial distributed patterns of cortical activity in the frequency domain, we applied a series of processing steps on the recorded EEG data. From the high-resolution EEG recordings we estimated the cortical waveforms for the regions of interest (ROIs), each representing a selected sensor group population. The solutions of the linear inverse problem returned a series of cortical waveforms for each ROI considered and for each trial analyzed. For each subject, the cortical waveforms were then subjected to Independent Component Analysis (ICA) pre-processing. The independent components obtained by the application of the ThinICA algorithm were further processed by a Partial Directed Coherence algorithm, in order to extract the causality between spatial cortical patterns of the estimated data. The source-target cortical dependencies found in the group of normal subjects were relatively similar in all frequency bands analyzed. For the normal subjects we observed a common source pattern in an ensemble of cortical areas including the right parietal and right lip primary motor areas and bilaterally the primary foot and posterior SMA areas. The target of this cortical network, in the Granger-sense of causality, was shown to be a smaller network composed mostly by the primary foot motor areas and the posterior SMA bilaterally. In the case of the SCI population, both the source and the target cortical patterns had larger sizes than in the normal population. The source cortical areas included always the primary foot and lip motor areas, often bilaterally. In addition, the right parietal area and the bilateral premotor area 6 were also involved. Again, the patterns remained substantially stable across the different frequency bands analyzed. The target cortical patterns observed in the SCI population had larger extensions when compared to the normal ones, since in most cases they involved the bilateral activation of the primary foot movement areas as well as the SMA, the primary lip areas and the parietal cortical areas.

Keywords

ThinICADistributed current density estimatesBrodmann areasInverse problemHigh-resolution EEGFunctional connectivityPartial Directed Coherence

Copyright information

© Springer Science+Business Media, LLC 2007