Turing Medical Co-Founders Publish in Nature

Turing Medical (Turing), formerly Nous Imaging, is proud to share that research led by our co-founders, Nico Dosenbach, M.D., PhD and Damien Fair, PA-C, PhD has been published on March 16 in Nature.

This research by Dosenbach, Fair, and their teams at Washington University in St. Louis (WashU) and University of Minnesota respectively has important implications on the future of brain-wide association studies (BWAS) leveraging magnetic resonance imaging (MRI). These studies have historically enrolled a small number of participants, leading to under-powered studies with findings that are difficult to reproduce.  

Specifically, the team found that brain-behavior correlations identified using a sample size of 25—the median sample size in published papers—usually failed to replicate in a separate sample. The research team leveraged publicly-available data, including approximately 50,000 participants across robust neuroimaging datasets, to assess correlations between brain structure and function and link them to a variety of characteristics such as personality, behavior, cognition, neurological conditions, and mental illness. With this much larger sample size, the team found that correlations are more likely to be reproduced. 

We commend the work of our co-founders, as this study has important implications on the future of functional brain mapping studies, highlighting the need for data and resource sharing across organizations to improve future neuropsychiatric research and outcomes. Our FIRMM technology, which was referenced in the publication¹, also has the potential to contribute to these efforts through the improvement of neuroimaging data collection and access across platforms. We look forward to sharing more in the near future about our subsequent efforts in this space. 

Media Contact: 

Julia Fuller 

Ford Hutman Media 



Press Release from Washington University in St. Louis 

Press Release from University of Minnesota 

[1] Dosenbach, N. U. F. et al. Real-time motion analytics during brain MRI improve data quality and reduce costs. Neuroimage 161, 80–93 (2017).