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001034744 1001_ $$0P:(DE-HGF)0$$aPérez, Pauline$$b0
001034744 245__ $$aContent–state dimensions characterize different types of neuronal markers of consciousness
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001034744 520__ $$aIdentifying the neuronal markers of consciousness is key to supporting the different scientific theories of consciousness. Neuronal markers of consciousness can be defined to reflect either the brain signatures underlying specific conscious content or those supporting different states of consciousness, two aspects traditionally studied separately. In this paper, we introduce a framework to characterize markers according to their dynamics in both the “state” and “content” dimensions. The 2D space is defined by the marker’s capacity to distinguish the conscious states from non-conscious states (on the x-axis) and the content (e.g. perceived versus unperceived or different levels of cognitive processing on the y-axis). According to the sign of the x- and y-axis, markers are separated into four quadrants in terms of how they distinguish the state and content dimensions. We implement the framework using three types of electroencephalography markers: markers of connectivity, markers of complexity, and spectral summaries. The neuronal markers of state are represented by the level of consciousness in (i) healthy participants during a nap and (ii) patients with disorders of consciousness. On the other hand, the neuronal markers of content are represented by (i) the conscious content in healthy participants’ perception task using a visual awareness paradigm and (ii) conscious processing of hierarchical regularities using an auditory local–global paradigm. In both cases, we see separate clusters of markers with correlated and anticorrelated dynamics, shedding light on the complex relationship between the state and content of consciousness and emphasizing the importance of considering them simultaneously. This work presents an innovative framework for studying consciousness by examining neuronal markers in a 2D space, providing a valuable resource for future research, with potential applications using diverse experimental paradigms, neural recording techniques, and modeling investigations.
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001034744 7001_ $$0P:(DE-HGF)0$$aManasova, Dragana$$b1
001034744 7001_ $$0P:(DE-HGF)0$$aHermann, Bertrand$$b2
001034744 7001_ $$0P:(DE-Juel1)185083$$aRaimondo, Federico$$b3
001034744 7001_ $$0P:(DE-HGF)0$$aRohaut, Benjamin$$b4
001034744 7001_ $$0P:(DE-HGF)0$$aBekinschtein, Tristán A$$b5
001034744 7001_ $$0P:(DE-HGF)0$$aNaccache, Lionel$$b6
001034744 7001_ $$0P:(DE-HGF)0$$aArzi, Anat$$b7
001034744 7001_ $$0P:(DE-HGF)0$$aSitt, Jacobo D$$b8$$eCorresponding author
001034744 773__ $$0PERI:(DE-600)2815642-0$$a10.1093/nc/niae027$$gVol. 2024, no. 1, p. niae027$$pniae027$$tNeuroscience of consciousness$$v1$$x2057-2107$$y2024
001034744 8564_ $$uhttps://juser.fz-juelich.de/record/1034744/files/Perez_Manasova_2023_NCC.pdf$$yOpenAccess
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001034744 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a Department of Cognitive and Brain Sciences, Institut du Cerveau—Paris Brain Institute—ICM, Inserm, CNRS, Sorbonne Université, Paris 75013, France. E-mail: jacobo.sitt@icm-institute.org$$b8
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