title: Mode level cognitive subtraction (MLCS) quantifies spatiotemporal reorganization in large-scale brain topographies.
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 tasks allows 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.
authors.affiliation: Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, Florida 33431, USA. banerjee@ccs.fau.edu
authors.forename: Arpan
authors.initials: A
authors.lastname: Banerjee
authors.forename: Emmanuelle
authors.initials: E
authors.lastname: Tognoli
authors.forename: Collins G
authors.initials: CG
authors.lastname: Assisi
authors.forename: J A Scott
authors.initials: JA
authors.lastname: Kelso
authors.forename: Viktor K
authors.initials: VK
authors.lastname: Jirsa
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003071:Cognition / Q000502:physiology*; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*