Health
Brain imaging studies, findings hampered by small datasets
For 20 years, researchers have used brain imaging technology to identify how the structure and function of the human brain is associated with a variety of mental health disorders, from anxiety and depression to suicidal tendencies. did.
but, New paper, The study, published in Nature on Wednesday, questioned whether much of this study actually yielded valid discoveries. Many of the studies found by the authors of the paper tend to include less than 20 participants, well below the number needed to produce credible results.
“We need thousands of individuals,” said Scott Marek, a psychiatric researcher and author of the paper at Washington University in St. Louis School of Medicine. He described this finding as a “gut punch” in typical studies that use imaging to better understand mental health.
Studies using magnetic resonance imaging usually soften the conclusion by noting that the sample size is small. However, attendee participation can be time consuming and costly, ranging from $ 600 to $ 2,000 per hour, said Nico, a neurologist at the University of Washington School of Medicine and another author of the paper. Dr. Dosenbach said. He added that the median number of subjects in mental health-related studies using brain images was about 23.
However, Nature’s paper shows that the data obtained from only 20 subjects are generally inadequate to be reliable and can actually lead to “significantly inflated” findings. ” Dr. Dosenbach said.
For their analysis, researchers examined three of the largest studies using brain imaging technology to reach conclusions about brain structure and mental health. All three studies are underway. Human Connectome Project with 1,200 participants. Adolescent brain cognitive development (ABCD) study with 12,000 participants. A survey by UK Biobank involved 35,700 people.
The authors of Nature’s paper examined a subset of the data in these three studies to determine if small slices were misleading or “reproducible.” In other words, the findings can be considered scientifically valid.
For example, ABCD’s research specifically examines whether brain gray matter thickness correlates with mental health and problem-solving abilities. The authors of Nature’s paper examined a small subset within a large study and found that the subset produced unreliable results when compared to the results obtained by the complete dataset.
On the other hand, the authors found that when the results were generated from a sample size containing thousands of subjects, the results were similar to the results for the complete dataset.
The author performed millions of calculations using different sample sizes and hundreds of brain regions investigated in different major studies. Over and over again, researchers have found that a subset of the data of less than a few thousand people do not produce results that match the results of the complete dataset.
Dr. Marek said the findings of this paper were “absolutely” applied beyond mental health. Other disciplines, such as genomics and cancer research, have their own ideas about the limits of small sample sizes and are trying to modify the course, he said.
“My premonition is more about artificial science than any of these areas,” he said.
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