Task-evoked simultaneous FDG-PET and fMRI data for measurement of neural metabolism in the human visual cortex

Author:

Jamadar Sharna D.ORCID,Zhong Shenjun,Carey Alexandra,McIntyre RichardORCID,Ward Phillip G. D.,Fornito AlexORCID,Premaratne Malin,Jon Shah N,O’Brien Kieran,Stäb Daniel,Chen ZhaolinORCID,Egan Gary F.

Abstract

AbstractUnderstanding how the living human brain functions requires sophisticated in vivo neuroimaging technologies to characterise the complexity of neuroanatomy, neural function, and brain metabolism. Fluorodeoxyglucose positron emission tomography (FDG-PET) studies of human brain function have historically been limited in their capacity to measure dynamic neural activity. Simultaneous [18 F]-FDG-PET and functional magnetic resonance imaging (fMRI) with FDG infusion protocols enable examination of dynamic changes in cerebral glucose metabolism simultaneously with dynamic changes in blood oxygenation. The Monash vis-fPET-fMRI dataset is a simultaneously acquired FDG-fPET/BOLD-fMRI dataset acquired from n = 10 healthy adults (18–49 yrs) whilst they viewed a flickering checkerboard task. The dataset contains both raw (unprocessed) images and source data organized according to the BIDS specification. The source data includes PET listmode, normalization, sinogram and physiology data. Here, the technical feasibility of using opensource frameworks to reconstruct the PET listmode data is demonstrated. The dataset has significant re-use value for the development of new processing pipelines, signal optimisation methods, and to formulate new hypotheses concerning the relationship between neuronal glucose uptake and cerebral haemodynamics.

Funder

Department of Education and Training | Australian Research Council

Department of Education and Training | ARC | Centre of Excellence for Integrative Brain Function, Australian Research Council

Department of Health | National Health and Medical Research Council

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

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