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    Simultaneous BOLD-fMRI and constant infusion FDG-PET data of the resting human brain

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    Author
    Jamadar, SD; Ward, PGD; Close, TG; Fornito, A; Premaratne, M; O'Brien, K; Stab, D; Chen, Z; Shah, NJ; Egan, GF
    Date
    2020-10-21
    Source Title
    Scientific Data
    Publisher
    NATURE RESEARCH
    University of Melbourne Author/s
    Egan, Gary
    Affiliation
    Anatomy and Neuroscience
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Jamadar, S. D., Ward, P. G. D., Close, T. G., Fornito, A., Premaratne, M., O'Brien, K., Stab, D., Chen, Z., Shah, N. J. & Egan, G. F. (2020). Simultaneous BOLD-fMRI and constant infusion FDG-PET data of the resting human brain. SCIENTIFIC DATA, 7 (1), https://doi.org/10.1038/s41597-020-00699-5.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/251742
    DOI
    10.1038/s41597-020-00699-5
    Open Access at PMC
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578808
    Abstract
    Simultaneous [18 F]-fluorodeoxyglucose positron emission tomography and functional magnetic resonance imaging (FDG-PET/fMRI) provides the capability to image two sources of energetic dynamics in the brain - cerebral glucose uptake and the cerebrovascular haemodynamic response. Resting-state fMRI connectivity has been enormously useful for characterising interactions between distributed brain regions in humans. Metabolic connectivity has recently emerged as a complementary measure to investigate brain network dynamics. Functional PET (fPET) is a new approach for measuring FDG uptake with high temporal resolution and has recently shown promise for assessing the dynamics of neural metabolism. Simultaneous fMRI/fPET is a relatively new hybrid imaging modality, with only a few biomedical imaging research facilities able to acquire FDG PET and BOLD fMRI data simultaneously. We present data for n = 27 healthy young adults (18-20 yrs) who underwent a 95-min simultaneous fMRI/fPET scan while resting with their eyes open. This dataset provides significant re-use value to understand the neural dynamics of glucose metabolism and the haemodynamic response, the synchrony, and interaction between these measures, and the development of new single- and multi-modality image preparation and analysis procedures.

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