Global study shows longer brain scans lower research costs, provide more accurate predictions

July 17, 2025
8:18 am

Artificial intelligence (AI) models trained on large datasets are increasingly seen as the key to unlocking personalized treatments for brain disorders. An important bottleneck for scaling AI is the cost of data collection. This raises a fundamental dilemma: is it more cost-effective to scan more people for a short time, or fewer people for longer?

A study, published in the journal Nature, led by Associate Professor Thomas Yeo from the Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore (NUS Medicine), now offers a clear answer: 30-minute functional MRI (fMRI) scans deliver up to 22% in cost savings while still retaining or even improving prediction accuracy.

Traditional thinking in neuroscience emphasizes collecting massive datasets by scanning thousands of people for brief durations, usually around 10 minutes for fMRI. AI models can then be trained to use the brain scans to make predictions of individual-level traits or outcomes. These traits and outcomes might include cognitive abilities (e.g. memory, executive function), mental health indicators and clinical outcomes (e.g. risk of Alzheimer’s disease).

Global study shows longer brain scans lower research costs, provide more accurate predictions

Sign up for Blog Updates