Machine learning-based approach to analyze spontaneous synaptic currents

What is it about?

Spontaneous synaptic activity is complicated, and so is their analysis. In this paper we present three complimentary methods for a fully automated analysis of spontaneous excitatory postsynaptic currents measured in major cell types of the mouse retina and in a primary culture of mouse auditory cortex. Two approaches rely on classical threshold methods, while the third represents a novel machine learning-based algorithm.

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Photo by Luke Chesser on Unsplash

Photo by Luke Chesser on Unsplash

Why is it important?

So far, human observers were forced to resort to manual or semi-automated approached on subjective and likely error-prone, possibly human biased, analysis. With the methods presented in this paper, this is no longer necessary.