Sensory processing disorders, which can make people overly sensitive to certain stimuli, tend to go hand-in-hand with autism, attention deficit hyperactivity disorder and schizophrenia. Neuroscientists at Indiana University are studying how neurons process sensory signals during a child’s development in hopes it will lead to improved treatments, but the new technique they are using generates massive amounts of data for analysis, requiring complex programming skills that are outside the scope of what most neuroscientists can do.
The research team in neuroscientist Hui-Chen Lu’s lab turned to DataJoint, a company that works exclusively with neuroscientists, to establish user-friendly, shareable data analysis tools in hopes of reducing barriers to collaboration and sophisticated analysis tools.
Using a new procedure, Lu, a professor in the College of Arts and Sciences' Department of Psychological and Brain Sciences and director of the Gill Center for Biomolecular Science at IU Bloomington, and her colleagues can visualize activity from a large number of neurons in the primary somatosensory cortex, the brain region where touch and pain signals are processed, in a live, awake and behaving baby mouse. The team collects activity patterns from hundreds of neurons simultaneously as the mouse moves and exhibits behaviors throughout the toddler and teenage stages of its development.
Specifically, Lu wants to understand how stress, environmental factors and other neural processes, such as touch or smell, influence the establishment of neural assemblies, and subsequently affect sensory processing and cognitive behaviors.
Analysis for this type of science is extremely complicated and requires complex computer programming. Jui-Yen Huang, an associate scientist at the Gill Center and a lead researcher on this project, spent a great deal of time developing a data analysis workflow in collaboration with other data scientists. Huang worked with DataJoint to fine-tune some of the programming she had already done.
With DataJoint, neuroscientists can upload their original data into a standardized electronic lab notebook with annotations about their experimental details, then have it analyzed with DataJoint’s tools. This open science approach will not only reduce the barrier for scientists to analyze neural activities with their own models, it will also allow future comparisons of data from laboratories across the world, Lu said.
“We are biologists, not IT professionals,” Lu said. “A lot of scientists like us are struggling with this kind of data. We have already done this programming, and we want to share it with other biologists to reduce barriers for them to do experiments and analyze data of their own, so they don’t struggle like we have for the last two years or longer. We want to make it easy for other scientists to put in their data and not have to worry about the programming.”
Additionally, DataJoint can develop the code from here on out, so biologists can focus on biological questions and interpreting the data instead of writing the code to analyze it, Huang said.
DataJoint has worked with numerous major research institutes across the world and received a National Institutes of Health Brain Initiative grant to make open-source software for data science and engineering available to researchers who specialize in neurophysiology. This work holds the promise of benefiting research in areas like autism, Alzheimer's disease and amyotrophic lateral sclerosis (ALS, or Lou Gehrig's disease), Lu said.
“DataJoint choosing to work with our lab speaks to the importance of the work we’re doing,” Lu said. “Not many people look at the young developing brain. Only a handful of labs in the world do this, and we’re one.”