NeuroDISK: An AI Approach to Automate Continuous Inquiry-Driven Discoveries in Neuroimaging Genetics. Garijo, D., Yang, Q., Vargas, H., Gadewar, S. P., Low, K., Ratnakar, V., Osorio, M., Zhu, A. H., McMahon, A., Gil, Y., & Jahanshad, N. bioRxiv, Cold Spring Harbor Laboratory, 2025. ![NeuroDISK: An AI Approach to Automate Continuous Inquiry-Driven Discoveries in Neuroimaging Genetics [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Collaborative and multi-site neuroimaging studies have greatly accelerated the rate at which new and existing data can be aggregated to answer a neuroscientific question. New research initiatives are continuously collecting more data, allowing opportunities to refine previous published findings through continuous and dynamic updates. Yet, we lack a practical framework for researchers to systematically, automatically, and continuously update published findings. We developed NeuroDISK, an automated artificial intelligence based framework that: 1) performs automated and inquiry-driven analyses, and 2) continuously updates these analyses as new data becomes available. NeuroDISK was evaluated using published results from the ENIGMA consortium's work on the genetic architecture of the cerebral cortex. We incorporate both meta-analysis and meta-regression options to showcase our framework on the effect of specific genotypes and moderators on select brain regions. Initial NeuroDISK meta-analysis results replicate the original publication, and we show result updates after adding new data. The NeuroDISK framework can be generalized for users to define question(s), run corresponding workflow(s) and access results interactively and continuously.Competing Interest StatementThis work was supported by NIH awards R01AG059874 (PI: Jahanshad) and R01MH134004 (PI: Jahanshad), ONR award N00014-21-1-2437 (PI: Gil), NSF awards IIS-1344272 (PI: Gil) and ICER-1541029 (PI: Gil), and pilot funding from the Kavli Foundation.
@article {Garijo2025.02.14.638360,
author = {Garijo, Daniel and Yang, Qifan and Vargas, Hern{\'a}n and Gadewar, Shruti P. and Low, Kevin and Ratnakar, Varun and Osorio, Maximiliano and Zhu, Alyssa H. and McMahon, Agnes and Gil, Yolanda and Jahanshad, Neda},
title = {NeuroDISK: An AI Approach to Automate Continuous Inquiry-Driven Discoveries in Neuroimaging Genetics},
year = {2025},
doi = {10.1101/2025.02.14.638360},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Collaborative and multi-site neuroimaging studies have greatly accelerated the rate at which new and existing data can be aggregated to answer a neuroscientific question. New research initiatives are continuously collecting more data, allowing opportunities to refine previous published findings through continuous and dynamic updates. Yet, we lack a practical framework for researchers to systematically, automatically, and continuously update published findings. We developed NeuroDISK, an automated artificial intelligence based framework that: 1) performs automated and inquiry-driven analyses, and 2) continuously updates these analyses as new data becomes available. NeuroDISK was evaluated using published results from the ENIGMA consortium's work on the genetic architecture of the cerebral cortex. We incorporate both meta-analysis and meta-regression options to showcase our framework on the effect of specific genotypes and moderators on select brain regions. Initial NeuroDISK meta-analysis results replicate the original publication, and we show result updates after adding new data. The NeuroDISK framework can be generalized for users to define question(s), run corresponding workflow(s) and access results interactively and continuously.Competing Interest StatementThis work was supported by NIH awards R01AG059874 (PI: Jahanshad) and R01MH134004 (PI: Jahanshad), ONR award N00014-21-1-2437 (PI: Gil), NSF awards IIS-1344272 (PI: Gil) and ICER-1541029 (PI: Gil), and pilot funding from the Kavli Foundation.},
URL = {https://www.biorxiv.org/content/early/2025/02/19/2025.02.14.638360},
eprint = {https://www.biorxiv.org/content/early/2025/02/19/2025.02.14.638360.full.pdf},
journal = {bioRxiv}
}
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