In neuroscience, numerous complementary techniques have been established to estimate human brain connections in vivo. We have created a tool that aligns complementary views of brain connectivity into a unified latent representation. This tool can then translate among patterns of white matter connectivity and functional coactivation, across myriad estimation techniques, preserving inter-individual variability.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$32.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout

References
Gu, Z. et al. Heritability and interindividual variability of regional structure-function coupling. Nat. Commun. 12, 4894 (2021). This paper reports that regional differences in the structure–function relationship vary with age, sex and cognition.
Pervaiz, U. et al. Optimising network modelling methods for fMRI. Neuroimage 211, 116604 (2020). This paper systematically compares many common strategies for estimating functional connectivity, demonstrating the impact on reproducibility and phenotypic prediction.
Sarwar, T. et al. Mapping connectomes with diffusion MRI: deterministic or probabilistic tractography? Magn. Reson. Med. 81, 1368–1384 (2019). This paper used realistic simulations to demonstrate the possibility of false-positive connections with probabilistic tractography.
Messé, A. Parcellation influence on the connectivity-based structure–function relationship in the human brain. Hum. Brain Mapp. 41, 1167–1180 (2020). This paper demonstrates that the structure–function relationship can appear to change when using different brain segmentation approaches.
Zalesky, A. et al. Predicting an individual’s functional connectivity from their structural connectome: Evaluation of evidence, recommendations, and future prospects. Netw. Neurosci. 8, 1291–1309 (2024). A review article that explores connectome prediction performance and recommends future work include individual identifiability when assessing predictions.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This is a summary of: Jamison, K. W. et al. Krakencoder: a unified brain connectome translation and fusion tool. Nat. Methods https://doi.org/10.1038/s41592-025-02706-2 (2025).
Rights and permissions
About this article
Cite this article
Krakencoder unifies diverse estimates of brain connectivity. Nat Methods 22, 1406–1407 (2025). https://doi.org/10.1038/s41592-025-02705-3
Published:
Issue date:
DOI: https://doi.org/10.1038/s41592-025-02705-3