Evidence map›Paper›PMID 34654823›Full record

ArticleScientific data2021

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

Sharna D Jamadar, Shenjun Zhong, Alexandra Carey, Richard McIntyre, Phillip G D Ward, Alex Fornito, Malin Premaratne, N Jon Shah, Kieran O'Brien, Daniel Stäb and 2 more

Open access · goldAbstract readDataset
In one paragraph

Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. PET-MRI Applications and Future Prospects in Psychiatry.Journal of magnetic resonance imaging : JMRI · 2025
    Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 5 institutions in 2 countries.

Sharna D Jamadar *Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia. sharna.jamadar@monash.edu.ORCID 0000-0001-7222-7181
Shenjun Zhong *Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia.
Alexandra CareyMonash Biomedical Imaging, Monash University, Melbourne, VIC, Australia.
Richard McIntyreMonash Biomedical Imaging, Monash University, Melbourne, VIC, Australia.ORCID 0000-0002-5613-0221
Phillip G D WardMonash Biomedical Imaging, Monash University, Melbourne, VIC, Australia.
Alex FornitoAustralian Research Council Centre of Excellence for Integrative Brain Function, Clayton, Australia.ORCID 0000-0003-0866-3477
Malin PremaratneDepartment of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC, Australia.
N Jon ShahInstitute of Neuroscience and Medicine - 4, Forschungszentrum Jülich, Jülich, Germany.
Kieran O'BrienMR Research Collaborations, Siemens Healthcare Pty Ltd, Clayton, Australia.
Daniel StäbMR Research Collaborations, Siemens Healthcare Pty Ltd, Clayton, Australia.
Zhaolin ChenMonash Biomedical Imaging, Monash University, Melbourne, VIC, Australia.ORCID 0000-0002-0173-6090
Gary F EganMonash Biomedical Imaging, Monash University, Melbourne, VIC, Australia.
Australian Research Council · AUMonash Medical Centre · AUMonash University · AUForschungszentrum Jülich · DENational Imaging Facility · AU

Funding

Department of Education and Training | ARC | Centre of Excellence for Integrative Brain Function, Australian Research Council (ARC Centre of Excellence for Integrative Brain Function) CE1401000007Department of Education and Training | Australian Research Council (ARC) DE150100406Department of Education and Training | Australian Research Council (ARC) LP170100494Department of Health | National Health and Medical Research Council (NHMRC) APP1174164
6 · The paper itself

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.

Indexed as

Functional NeuroimagingMagnetic Resonance ImagingPositron-Emission TomographyAdolescentAdultFemaleHumansMaleMiddle AgedVisual CortexYoung Adult

Identifiers

PMID34654823
PMCPMC8520012
OpenAlexW3206362227

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.