Project Overview

The NeurOimaging DatabasE (NODE) is a neuroimaging repository that houses, organises and provides analysis capabilities for high quality research grade neuroimaging and associated scalar data from a range of research studies conducted at the Institute of Psychiatry, Psychology and Neuroscience (King’s College London), MRC London Institute of Medical Sciences and other centres between 2008 and the present day. The aim of the NODE is to support large-scale analysis across primarily psychiatric and neurological disorders.

NODE is organised into two components:
NODE-MRI, which includes hundreds of brain MRI scans with standard and
advanced sequences and NODE-PET, which gathers data from brain PET imaging studies with different radiotracers.

Datasets

NODE-MRI (NODE-MRI-info-20190719)

NODE-MRI currently holds 7 projects and data for 279 participants. It is assumed that each participant will have at least 1 hour of scan images.
There are plans to load more data as follows: 21 pilot studies with approximately 800 scan hours across the entire group of studies; new scan data from the Novel Neuroimaging Approaches studies which will include over 300 scan hours on predominantly healthy participants exploring new ways to improve neuroimaging acquisition and analysis methods.

NODE-PET (NODE-PET-info-20190719)

NODE-PET currently holds 8 projects and data for 287 participants and a total of 352 dynamic PET scans. Each participant has a dynamic PET scan and a document including technical information about the PET imaging protocol that are essential for running PET analyses (i.e. ancillary files). MRI is also available for some studies. Additional projects will be uploaded over the next months.

Data Access

NODE is protected by a university firewall and accessible only to staff and students affiliated to King’s College London via  intranet. External users please contact us if you wish to request access to datasets.

For any questions please contact the support team at node.information@kcl.ac.uk

Acknowledgements

This work is in supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, in collaboration with prof. Oliver Howes (MRC London Institute of Medical Sciences and King’s College London).

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