AI Article Synopsis
- Understanding brain function requires advanced imaging techniques to analyze complex neural activities and metabolism in real-time.
- The Monash vis-fPET-fMRI dataset includes data from 10 healthy adults using a combined FDG-PET and fMRI approach, allowing researchers to study glucose metabolism alongside brain activity during a visual task.
- The dataset offers valuable raw data for researchers to develop new analysis methods and explore links between glucose uptake and blood flow in the brain.
Article Abstract
Understanding 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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8520012 | PMC |
| http://dx.doi.org/10.1038/s41597-021-01042-2 | DOI Listing |
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