The nature of the link between our physical bodies and our behavior has perplexed people for centuries.
While the antiquated notion that our skulls shape our personality, known as phrenology, has long been discarded as pseudoscience, we still look for clues to behavior, disease, and mental illness in the brain.
Whether we want to study how the brain makes decisions or uses language, or the underpinnings of diseases such as dementiaTrusted Source, the existence of MRI scanners allows us to do this.
However, looking for differences in brain structure to explain differences in behavior is not without controversy.
In fact, a study published last month in the journal Nature argued that the majority of brain-wide association studies, which compare MRI scans to detect structural differences in the brain, have sample sizes that are too small to draw conclusions from.
One reason for these small studies is that MRI scans are time-consuming and expensive to produce.
That is why researchers Dr. Richard Bethlehem and Dr. Jakob Seidlitz decided to see if they could get other scientists to share their MRI scan datasets in an attempt to develop reference standards for the brain.
Dr. Seidlitz explained that he and his co-author of the new study, also published in NatureTrusted Source, had always wanted to see the results of different studies overlaid on top of each other.
He told Medical News Today in an interview: “We basically started plotting some historical datasets that were published 10, 15, 20, 30 years ago on different brain features, like different volumes.”
“And even if you were just plotting those historical values […], by extracting data points from previous papers in the literature, we started to see these curves emerge.”
Plotting scientific data allows researchers to create a graph of different data points so they can visualize differences or other relationships between variables of data.
The COVID-19 pandemic acted as a catalyst for the project as they realized they could not collect new data, and would have to use existing datasets for research.