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Predicting effective connectivity from resting-state networks in healthy elderly and patients with prodromal Alzheimer's disease

Authors

  • Susanne Neufang,

    Corresponding author
    1. Department of Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
    • Susanne Neufang, Department of Neuroradiology, Klinikum Rechts der Isar, Technische Universität Munich, Ismaningerstrasse 22, 81675 Munich, Germany. E-mail: Neufang@lrz.tu-muenchen.de

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  • Atae Akhrif,

    1. Department of Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
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  • Valentin Riedl,

    1. Department of Neurology, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
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  • Hans Förstl,

    1. Department of Psychiatry, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
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  • Alexander Kurz,

    1. Department of Psychiatry, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
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  • Claus Zimmer,

    1. Department of Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
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  • Christian Sorg,

    1. Department of Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
    2. Department of Psychiatry, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
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  • Afra M. Wohlschläger

    1. Department of Neuroradiology, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
    2. Department of Neurology, Klinikum Rechts der Isar, Technical University Munich, 81675 Munich, Germany
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Abstract

Using functional neuroimaging techniques two aspects of functional integration in the human brain have been investigated, functional connectivity and effective connectivity. In this study we examined both connectivity types in parallel within an executive attention network during rest and while performing an attention task. We analyzed the predictive value of resting-state functional connectivity on task-induced effective connectivity in patients with prodromal Alzheimer's disease (AD) and healthy elderly. We found that in healthy elderly, functional connectivity was a significant predictor for effective connectivity, however, it was frequency-specific. Effective top-down connectivity emerging from prefrontal areas was related with higher frequencies of functional connectivity (e.g., 0.08–0.15 Hz), in contrast to effective bottom-up connectivity going to prefrontal areas, which was related to lower frequencies of functional connectivity (e.g., 0.001–0.03 Hz). In patients, the prediction of effective connectivity by functional connectivity was disturbed. We conclude that functional connectivity and effective connectivity are interrelated in healthy brains but this relationship is aberrant in very early AD. Hum Brain Mapp 35:954–963, 2014. © 2013 Wiley Periodicals, Inc.

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