Brain-Imaging Studies Hampered by Small Data Sets, Study Finds

For two decades, researchers have used brain-imaging technology to try to identify how the structure and function of a person’s brain connects to a range of mental-health ailments, from anxiety and depression to suicidal tendencies. But a new paper, published Wednesday in Nature, calls into question whether much of this research is actually yielding valid findings. The New York Times reports: Many such studies, the paper’s authors found, tend to include fewer than two dozen participants, far shy of the number needed to generate reliable results. “You need thousands of individuals,” said Scott Marek, a psychiatric researcher at the Washington University School of Medicine in St. Louis and an author of the paper. He described the finding as a “gut punch” for the typical studies that use imaging to try to better understand mental health.

Studies that use magnetic-resonance imaging technology commonly temper their conclusions with a cautionary statement noting the small sample size. But enlisting participants can be time-consuming and expensive, ranging from $600 to $2,000 an hour, said Dr. Nico Dosenbach, a neurologist at Washington University School of Medicine and another author on the paper. The median number of subjects in mental-health-related studies that use brain imaging is around 23, he added. But the Nature paper demonstrates that the data drawn from just two dozen subjects is generally insufficient to be reliable and can in fact yield ‘massively inflated’ findings,” Dr. Dosenbach said. The findings from the Nature paper can “absolutely” be applied to other fields beyond mental health, said Marek. “My hunch this is much more about population science than it is about any one of those fields,” he said.