Mode level cognitive subtraction (MLCS) quantifies spatiotemporal reorganization inlarge-scale brain topographies

Arpan Banerjee, Emmanuelle Tognoli, Collins G. Assisi, J.A. Scott Kelso, Viktor K. Jirsa

    Research output: Contribution to journalArticle

    14 Citations (Scopus)

    Abstract

    Contemporary brain theories of cognitive function posit spatial, temporal and spatiotemporal reorganization as mechanisms for neural information processing. Corresponding brain imaging results underwrite this perspective of large-scale reorganization. As we show here, a suitable choice of experimental control tasksallows the disambiguation of the spatial and temporal components of reorganization to a quantifiable degree of certainty. When using electro- or magnetoencephalography (EEG or MEG), our approach relies on the identification of lower dimensional spaces obtained from the high dimensional data of suitably chosen control task conditions. Encephalographic data from task conditions are reconstructed within these control spaces. We show that the residual signal (part of the task signal not captured by the control spaces) allows the quantification of the degree of spatial reorganization, such as recruitment of additional brain networks.
    LanguageEnglish
    Pages663-674
    JournalNeuroImage
    Volume42
    Issue number2
    DOIs
    Publication statusPublished - 2008

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    Electroencephalography
    Magnetoencephalography
    Brain
    Automatic Data Processing
    Neuroimaging
    Cognition

    Cite this

    Banerjee, Arpan ; Tognoli, Emmanuelle ; Assisi, Collins G. ; Kelso, J.A. Scott ; Jirsa, Viktor K. / Mode level cognitive subtraction (MLCS) quantifies spatiotemporal reorganization inlarge-scale brain topographies. 2008 ; Vol. 42, No. 2. pp. 663-674.
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    Mode level cognitive subtraction (MLCS) quantifies spatiotemporal reorganization inlarge-scale brain topographies. / Banerjee, Arpan; Tognoli, Emmanuelle; Assisi, Collins G.; Kelso, J.A. Scott; Jirsa, Viktor K.

    Vol. 42, No. 2, 2008, p. 663-674.

    Research output: Contribution to journalArticle

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