The electrical properties of a neuron paint a picture of its development and function. A new user-friendly and accessible tool developed at the Waisman Center at the University of Wisconsin-Madison, with the help of biomedical engineering researchers, allows scientists to analyze the electrical activity of individual neurons—rather than clusters—using a process known as spike sorting. The free tool is available online for other researchers to access.
The tool, called Semi-Automated MEA Spike sorting software (SAMS) is designed to separate electrical activity recorded from groups of human stem cell-derived neurons into signals from individual neurons. SAMS is specifically designed for data collected using a multi-electrode array (MEA), a device that uses microscopic electrodes to measure the electrical activity of cells.
SAMS was developed by the lab of Waisman investigator Xinyu Zhao, Jenni & Kyle Professor and Vilas Distinguished Achievement Professor of Neuroscience, and Waisman affiliates Ari Rosenberg, Professor of Computational Neuroscience and Retina Research Foundation Edwin & Dorothy Gamewell Professor, and Aviad Hai, Vilas Early Career Associate Professor of Biomedical Engineering.
Neurons communicate by generating and transmitting information using electricity. The electrical pulses they use to communicate are known as action potentials, or spikes. Analyzing the spiking characteristics of neurons through electrophysiology is important to better understand their development, function and dysfunction, and how these processes change in response to diseases, environmental conditions, or therapeutic treatments.
While MEAs allow scientists to record electrical activity from many neurons simultaneously, this approach has limitations.
“Some of the characteristics of neurons get disguised if you measure just the average,” Zhao says. Resolving the activity of single neurons requires a process called spike sorting.
Current spike sorting methods were not developed for analyzing data from human stem cell-derived neurons. They also involve a complex pipeline and time-consuming manual intervention. Scientist Carissa Sirois and doctoral student Xiaoxuan Ren from the Zhao and Hai labs developed SAMS as a tool to take the recordings and sort them into single spikes in an automated way.
When tested, SAMS produced accurate and consistent results while greatly reducing data-processing time. The software tool also enabled researchers to identify additional neuronal characteristics that they hadn’t detected before without spike sorting.
SAMS is openly accessible and user-friendly and does not require coding knowledge. The tool is free for any researcher to download.
“We hope the scientific community will want to use it,” Zhao says. As others start using it, they will continue to improve it and release new versions. “It’s just a tool we really needed,” Zhao says, “and now we actually have something that we can work with.”
This article was first published on the Waisman Center website.