Spike inference paper published

Finally, our paper on “Benchmarking Spike Rate Inference in Population Calcium Imaging” has been published – as a NeuroResource in Neuron. spikeinference.png In the paper, we evaluate a range of algorithms for spike rate inference from calcium imaging data on a large ground-truth dataset. What’s important is that the recordings were all performed under realistic conditions for population imaging, that is without zooming in on individual cells. This makes the task much more difficult – the best algorithms achieve correlations of 0.5-0.6 when evaluated in time bins of 40 ms. It will be interesting to find out whether this can be improved upon by better algorithms or whether new indicators and imaging systems are needed for that. We provide our method, which performs very well under a wide range of recording conditions, for ready reuse.


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