“Brain’s ‘Background Noise’ May Hold Clues to Persistent Mysteries”
by Elizabeth Landau
Quanta, February 8, 2021
Hi [Name Redacted],
Hope you’re doing well! I’ve come across a story idea that I think would work well for Quanta:
Brain Wave Signal Opens New Neuroscience Possibilities
A huge challenge in neuroscience is distinguishing signal from noise. But a group at UCSD has developed an algorithm that allows scientists to analyze brain wave data in a whole new way, and it has already led to discoveries.
The algorithm separates out the periodic parts of brain oscillations from aperiodic parts. Traditionally, the aperiodic component of these oscillations has been considered unimportant — mere noise. But two years ago, Bradley Voytek and colleagues made an algorithm freely available to help neuroscientists find patterns in that randomness. It has already been used in many studies including investigations of sleep, autism, and ADHD medication efficacy. A paper describing this algorithm is being published for the first time in Nature Neuroscience on Nov. 23.
According to Voytek, this aperiodic signal could be a new biomarker that allows neuroscientists to get a fuller picture of the brain and its responses to medications, conditions, etc. I propose a feature that looks at what this signal is, the range of results the algorithm has enabled so far, as well as its limitations, and the direction scientists are heading next.
Let me know what you think. It would be great to have the opportunity to work with you again!