Metabolic connectivity as index of verbal working memory.

Zou N; Chetelat G; Baydogan MG; Li J; Fischer FU; Titov D; Dukart J; Fellgiebel A; Schreckenberger M; Yakushev I

doi:10.1038/jcbfm.2015.40

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Journal article

Metabolic connectivity as index of verbal working memory.

Zou N Department of Industrial Engineering, Arizona State University, Tempe, Arizona, USA.
Chetelat G Inserm-EPHE-Université de Caen, Caen, France.
Baydogan MG Department of Industrial Engineering, Bogazici University, Istanbul, Turkey.
Li J Department of Industrial Engineering, Arizona State University, Tempe, Arizona, USA.
Fischer FU Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Mainz, Germany.
Titov D Department of Nuclear Medicine, Technische Universität München, Munich, Germany.
Dukart J 1] Service of Neurology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland [2] Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Fellgiebel A Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Mainz, Germany.
Schreckenberger M Department of Nuclear Medicine, University Medical Center Mainz, Mainz, Germany.
Yakushev I 1] Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Mainz, Germany [2] Department of Nuclear Medicine, Technische Universität München, Munich, Germany [3] Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Munich, Germany.

2015-03-19

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Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism. - 2015

English 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.

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