Julia Belluz in Vox (Semnic/Shutterstock):
When neuroscientists stuck a dead salmon in an fMRI machine and watched its brain light up, they knew they had a problem. It wasn't that there was a dead fish in their expensive imaging machine; they'd put it there on purpose, after all. It was that the medical device seemed to be giving these researchers impossible results. Dead fish should not have active brains.
The researchers shared their findings in 2009 as a cautionary tale: If you don't run the proper statistical tests on your neuroscience data, you can come up with any number of implausible conclusions — even emotional reactions from a dead fish.
In the 1990s, neuroscientists started using the massive, round fMRI (or functional magnetic resonance imaging) machines to peer into their subjects' brains. But since then, the field has suffered from a rash of false positive results and studies that lack enough statistical power — the likelihood of finding a real result when it exists — to deliver insights about the brain.
When other scientists try to reproduce the results of original studies, they too often fail. Without better methods, it'll be difficult to develop new treatments for brain disorders and diseases like Alzheimer's and depression — let alone learn anything useful about our most mysterious organ.
To address the problem, the Laura and John Arnold Foundation just announced a $3.8 million grant to Stanford University to establish the Center for Reproducible Neuroscience. The aim of the center is to clean up the house of neuroscience and improve transparency and the reliability of research. On the occasion, we spoke to Russ Poldrack, director of the center, about what he thinks are neuroscience's biggest problems and how the center will tackle them.