The group of neurologists from Centre for Computational Biology (CCB) at the Flatiron Institute in New York City have developed an innovative tool called CaImAn. This device automatically collects the database of neurons activity through calcium imaging.
The case study was published in eLife journal on 17 January 2019.
The CaImAn tool is based on the technique of calcium imaging analysis. It can identify the activities of a specific neuron that contributes to the different behaviors. The device works by adding a special dye to the brain tissue or to neurons in a dish. This dye secures the calcium ions which is responsible for activating the neurons.
When these formulated calcium ions are exposed under the ultraviolet light they emit the fluorescence light. This process can only happen if the dye binds with calcium ions which make the researchers possible to track down the activity of the neurons.
A comparative study was done by the scientist to test the accuracy of CaImAn with the human-generated dataset. The results of this experiment proved that CaImAn is more accurate and more efficient than manually identifying the active neurons.
According to Pnevmatikakis, the research scientist at the Flatiron Institute’s, said, “It was elegant mathematically and did a decent job, but we realized it didn’t generalize well to different datasets. We wanted to transform it into a software suite that the community can use.”
Giovannucci, a team member of CCB neuroscience group said, “Existing analysis tools were not powerful enough to disentangle the activity of this population of neurons and implied that they were all doing the same thing.”
According to the reports researchers have used the training database of human-annotated results. This will help in developing the machine-learning tools for the advancement of CaImAn package. Scientists have now made this database public, and it has already proven to be beneficial for further research.
Researchers have claimed that today more than 100 labs are using CaImAn software, as it is compatible for any standard laptop and fully analyze data in real time. Researchers can now track the details while running an experiment, in a way they can resourcefully use CaImAn.