CHRISTOPHER MADAN CHRISTOPHER.MADAN@NOTTINGHAM.AC.UK
Assistant Professor
Scan Once, Analyse Many: Using large open-access neuroimaging datasets to understand the brain
Madan, Christopher R
Authors
Abstract
We are now in a time of readily available brain imaging data. Not only are researchers now sharing data more than ever before, but additionally large-scale data collecting initiatives are underway with the vision that many future researchers will use the data for secondary analyses. Here I provide an overview of available datasets and some example use cases. Example use cases include examining individual differences, more robust findings, reproducibility–both in public input data and availability as a replication sample, and methods development. I further discuss a variety of considerations associated with using existing data and the opportunities associated with large datasets. Suggestions for further readings on general neuroimaging and topic-specific discussions are also provided.
Journal Article Type | Review |
---|---|
Acceptance Date | Mar 7, 2021 |
Online Publication Date | May 11, 2021 |
Publication Date | 2022-01 |
Deposit Date | Mar 8, 2021 |
Publicly Available Date | May 12, 2022 |
Journal | Neuroinformatics |
Print ISSN | 1539-2791 |
Electronic ISSN | 1559-0089 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 20 |
Pages | 109-137 |
DOI | https://doi.org/10.1007/s12021-021-09519-6 |
Keywords | brain imaging; secondary data; connectome; sample size; functional connectivity; fMRI; naturalistic neuroimaging |
Public URL | https://nottingham-repository.worktribe.com/output/4930368 |
Publisher URL | https://link.springer.com/article/10.1007/s12021-021-09519-6 |
Files
Scan Once, Analyse Many: Using Large Open-Access Neuroimaging Datasets to Understand the Brain
(14.9 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
You might also like
Insights into the accuracy of social scientists’ forecasts of societal change
(2023)
Journal Article
Risky choice and memory for effort: Hard work stands out
(2022)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search