Open source software tracks neurons in real time

Editorial

Rebecca Pool

Friday, March 1, 2019 - 14:45
Calcium imaging: Open source software automatically differentiates between individual neurons (yellow) with nearly the same accuracy as a human (red). [Giovannucci et al./eLife 2019]
 
Researchers from the Flatiron Institute in New York City, US, have honed software to achieve near-human accuracy in detecting the locations of active neurons based on calcium imaging data. 
 
So-called CaImAn - an abbreviation of calcium imaging analysis - is open source and combines computational methods and machine learning to automate the process of differentiating individual neurons.
 
As Dmitri Chklovskii, who leads the neuroscience group at the Center for Computational Biology (CCB) at the Flatiron Institute, says: "People have spent more time analysing their data to extract activity traces than actually collecting it."
 
CaImAn has been freely available for a few years and has already proved invaluable to the calcium imaging community, with more than 100 labs using the software.
 
While the software was initially developed to help researchers handle the enormous datasets produced during calcium imaging, the latest iteration can now analyse data in real time, so researchers can analyse results as they perform experiments.
 
The researchers recently tested CaImAn's accuracy by comparing its results with a human-generated dataset.
 
The comparison proved that the software is nearly as accurate as humans in identifying active neurons but much more efficient.
 
Its speed allows researchers to adapt their experiments on the fly, improving studies of how specific bundles of neurons contribute to different behaviours.
 
The human dataset also revealed high variability from person to person, highlighting the benefit of having a standardised tool for analyzing imaging data.
 
Research is published in eLife.
 
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