New Browser Allows Sharing of MRI Data on ALS, Other Neurodegenerate Disorders

Difficulty sharing vast amounts of information — the so-called big data — can slow the pace of scientific advancement, experts say.

A University of Washington team has come up with a way to help neuroscience researchers share huge swaths of MRI information about ALS and similar disorders. The information deals with the movement of fluids through the body.

Since the new tool is open source, any scientist can use it.

The study, “A browser-based tool for visualization and analysis of diffusion MRI data,” appeared in the journal Nature Communications.

Not being able to share data, especially in complex fields such as neuroscience research, contributes to what scientists call the replication crisis — an inability to reproduce the experimental results that researchers in other locations have achieved.

“There has been a lot of talk among researchers about the replication crisis,” Jason Yeatman, an assistant professor in the University of Washington’s Department of Speech & Hearing Sciences, said in a press release.

“We wanted a tool — ready, widely available and easy to use — that would actually help fight the replication crisis,” said Yeatman, a co-lead author of the study, who is also with the university’s Institute for Learning & Brain Sciences.

The AFQ-Browser allows scientist to upload, look at and share diffusion-weighted MRI data.

Diffusion-weighted MRI measures the movement of fluid in the body, including the brain and spinal cord. It has contributed significantly to neuroscientists’ understanding of brain connectivity.

With it, they can learn about the way the brain’s white matter is organized. This organization is crucial to memory, learning and other capabilities.

Since AFQ is a standard internet browser, it does not require additional software or equipment.

“One major barrier to data transparency in neuroscience is that so much data collection, storage and analysis occurs on local computers with special software packages,” said Ariel Rokem, a senior data scientist in the University of Washington eScience Institute.

“Using AFQ-Browser, we eliminate those requirements and make uploading, sharing and analyzing diffusion-weighted MRI data a simple, straightforward process,” said Rokem, the other co-lead author of the study.

Diffusion-weighted MRI can help scientists diagnose complex neurological conditions such as multiple sclerosis and ALS. It is also used in research on dyslexia and learning disabilities.

“This is a widely used technique in neuroscience research, and it is particularly amenable to the benefits that can be gleaned from big data, so it became a logical starting point for developing browser-based, open-access tools for the field,” Yeatman said.

The AFQ-Browser’s interactive tools allow researchers to compare the white matter of several people. The similarities and differences can lead to new hypotheses for future research.

“We wanted this tool to be as generalizable as possible, regardless of research goals,” Rokem said. “The format is easy for scientists from a variety of backgrounds to use and understand — so that neuroscientists, statisticians and other researchers can collaborate, view data and share methods toward greater reproducibility.”

Several researchers and graduate students tested the browser using diffusion-weighted MRI datasets of ALS and MS.

Researchers hope to improve the browser to the point that it may even be able to be used to help in diagnoses.

The AFQ-Browser “is really just the start of what could be a number of tools for sharing neuroscience data and experiments,” Yeatman said. “Our goal here is greater reproducibility and transparency, and a more robust scientific process.”