From dbd2c91bfab81b9444b8716c3c210341967bc97c Mon Sep 17 00:00:00 2001 From: Peter Rupprecht Date: Sun, 24 Oct 2021 22:15:09 +0200 Subject: [PATCH] Change FAQ as suggested in issue #22. --- README.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/README.md b/README.md index 880b762c..9c0d56a5 100644 --- a/README.md +++ b/README.md @@ -163,6 +163,10 @@ Any more questions? Probably you will find the answer below! >The output **spike_prob** is the _expected number of spikes_ in this time bin, at the same resolution as the original calcium recording. This metric is also called _spike probability_ for brevity in the paper and elsewhere. If you sum over the trace in time, you will get the estimated **number of spikes**. If you multiply the trace with the frame rate, you will get an estimate of the instantaneous **spike rate**. Spike probability and spike rates can therefore be converted by multiplication with the frame rate. +#### Can **spike_prob** be larger than 1? + +>Yes. As described above ("What does the output of the algorithm mean?"), the output of the algorithm is strictly speaking not a probability and therefore not restricted to values between 0 and 1. A value >1 indicates that the estimated number of spikes in the time bin is larger than 1. + #### How large would a single spike be? >This depends on your frame rate (Hz) and on the smoothing (standard deviation, milliseconds) of your model. Use the following script to compute the spike probability shape for given parameters. >