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

Susanne Neufang, Atae Akhrif, Valentin Riedl, Hans Förstl, Alexander Kurz, Claus Zimmer, Christian Sorg, Afra M. Wohlschläger

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

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.

Original languageEnglish
Pages (from-to)954-963
Number of pages10
JournalHuman Brain Mapping
Volume35
Issue number3
DOIs
StatePublished - Mar 2014
Externally publishedYes

Keywords

  • Effective connectivity
  • Executive attention network
  • Prodromal Alzheimer's disease
  • Resting-state functional connectivity

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