A Vanderbilt Health team has been named a winner of the National Institutes of Health (NIH) Replication Prize for developing tools that make brain imaging research more reliable.
The group, which calls itself Team RESI, is one of two Vanderbilt Health teams among the 15 teams and individuals NIH selected for the prize. As earlier reported, another VH team won for a tool that allows researchers to gauge the quality of data in large DNA biobanks.
The teams were chosen as “Replication Exemplars,” recognized for making replication — the ability of other scientists to reproduce a study’s results — a routine part of their work. NIH announced the winners May 13. Winners will receive a cash prize of up to $50,000.
Brain imaging, such as MRI, is a key tool for studying how the brain relates to behavior, memory and mental health. But many imaging studies have proven hard to repeat: A finding reported by one group often shrinks or disappears when another group tries the same thing. That unreliability has raised concerns across the field about how much of the published research can be trusted.
Part of the problem, the team argues, is how scientists decide whether a result matters. Researchers have leaned heavily on whether a finding is “statistically significant” — a yes-or-no test that can flag a result as real even when the underlying effect is tiny. A more informative question is how large the effect actually is. An “effect size” captures that strength, showing not just whether two things are related but how strongly.
The team’s central contribution is a measure called the robust effect size index, or RESI, that gauges effect size consistently across many kinds of studies and holds up even when the data is messy. Earlier effect size measures were harder to compare from one study to the next. The team also built free, open-source software so other researchers can adopt the approach easily and proposed practical changes to how studies are designed that can deliver more dependable results without larger budgets.
Team RESI includes biostatistics PhD candidate Xinyu Zhang, Megan Taylor Jones, PhD, who finished her doctorate in May and is headed to a postdoctoral position at Queens University in Kingston, Ontario, Kaidi Kang, PhD, who finished his doctorate in 2025 and is now Assistant Professor of Biostatistics and Data Science at Wake Forest University, and team leader Simon Vandekar, PhD, Associate Professor of Biostatistics.
The team’s research has been supported in part by NIH award R01MH123563.
