Contributors - Open Call
Call for ReFiNe replication project - form to contribute: link
Open community call
ReFiNe (Replicability of Findings in Neuroimaging) is an open community initiative to systematically evaluate which neuroimaging findings replicate in independent datasets.
We invite researchers, cohorts, and consortia with existing neuroimaging data to take part in coordinated direct replication studies. The goal is to reproduce original analyses as closely as possible, document where adaptations are needed, and build a clearer picture of which findings are robust across datasets, methods, populations, and modalities.
How to contribute
First: register your availability: link!
Then, you can contribute by:
- selecting a replication target from the eligible studies list;
- checking whether your dataset has the required imaging, clinical, behavioural, or demographic variables;
- using the ReFiNe replication protocol and preregistration template;
- contacting the original authors where needed;
- running the replication and documenting any deviations from the original analysis;
- sharing the outcome using the ReFiNe reporting template.
Contributions can focus on a single replication study, a set of related findings, or broader methodological questions such as robustness across preprocessing pipelines, diagnostic definitions, imaging modalities, or phenotype operationalisations.
Authorship and publication plan
ReFiNe is designed to support both individual replication papers and a larger community meta-analysis.
Individual replication teams will lead and receive appropriate authorship credit for the studies they conduct. Across replications, the ReFiNe community will also work towards a coordinated meta-analysis evaluating replication rates, sources of heterogeneity, and predictors of replication success.
The publication plan will be transparent and discussed openly with contributors as the project develops.
Current replication activity
The project is currently building a shared list of eligible replication targets and matching them to available datasets. Initial work focuses on structural MRI findings in major depressive disorder, with the aim of expanding over time to additional topics, disorders, and neuroimaging modalities.