Metabolic connectivity as index of verbal working memory

Na Zou, Gael Chetelat, Mustafa G. Baydogan, Jing Li, Florian U. Fischer, Dmitry Titov, Juergen Dukart, Andreas Fellgiebel, Mathias Schreckenberger, Igor Yakushev

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Positron emission tomography (PET) data are commonly analyzed in terms of regional intensity, while covariant information is not taken into account. Here, we searched for network correlates of healthy cognitive function in resting state PET data. PET with [ 18 F]-fluorodeoxyglucose and a test of verbal working memory (WM) were administered to 35 young healthy adults. Metabolic connectivity was modeled at a group level using sparse inverse covariance estimation. Among 13 WM-relevant Brodmann areas (BAs), 6 appeared to be robustly connected. Connectivity within this network was significantly stronger in subjects with above-median WM performance. In respect to regional intensity, i.e., metabolism, no difference between groups was found. The results encourage examination of covariant patterns in FDG-PET data from non-neurodegenerative populations.

Original languageEnglish (US)
Pages (from-to)1122-1126
Number of pages5
JournalJournal of Cerebral Blood Flow and Metabolism
Issue number7
StatePublished - Jul 1 2015


  • connectivity modeling
  • covariance analysis
  • neural network
  • neuroimaging
  • positron emission tomography

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine


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