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Dynamic causal modeling of spatiotemporal integration of phonological and semantic processes: an electroencephalographic study.


Integration of phonological and lexicosemantic processes is essential for visual word recognition. Here we used dynamic causal modeling of event-related potentials, combined with group source reconstruction, to estimate how those processes translate into context-dependent modulation of effective connectivity within the temporal-frontal language network. Fifteen healthy human subjects performed a phoneme detection task in pseudo-words and a semantic categorization task in words. Cortical current densities revealed the sequential activation of temporal regions, from the occipital-temporal junction toward the anterior temporal lobe, before reaching the inferior frontal gyrus. A difference of activation between phonology and semantics was identified in the anterior temporal lobe within the 240-300 ms peristimulus time window. Dynamic causal modeling indicated this increase of activation of the anterior temporal lobe in the semantic condition as a consequence of an increase of forward connectivity from the posterior inferior temporal lobe to the anterior temporal lobe. In addition, fast activation of the inferior frontal region, which allowed a feedback control of frontal regions on the superior temporal and posterior inferior temporal cortices, was found to be likely. Our results precisely describe spatiotemporal network mechanisms occurring during integration of phonological and semantic processes. In particular, they support the hypothesis of multiple pathways within the temporal lobe for language processing, where frontal regions would exert a top-down control on temporal regions in the recruitment of the anterior temporal lobe for semantic processing.


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    Brain Mapping
    Cerebral Cortex
    Evoked Potentials
    Image Processing, Computer-Assisted
    Magnetic Resonance Imaging
    Models, Neurological
    Nonlinear Dynamics
    Photic Stimulation
    Reaction Time
    Young Adult

    Pub Type(s)

    Journal Article
    Research Support, Non-U.S. Gov't



    PubMed ID