A testing pipeline that allows us to run a behavioural phenotyping of our virtual worm running the same test statistics the Schafer Lab used on their worm data.
In my last paper (http://rsif.royalsocietypublishing.org/content/12/113/20150899) I have argued that behaviour is not a set of discrete states, but rather a continuous spectrum. When presenting my results people often assigned the observed continuity as an artefact of my method rather than as a feature of behaviour. I have been criticized that other omega turn detection algorithms or experts could pick out omegas unambiguously.
I wanted to put this claim to the test and this survey is a part of this effort. I have already compared 4 omega turn detection algorithms (Laurent 2015, Yemini 2013, Huang 2006, Salvador 2014) and they often have a disagreement for over 50% of the events!!! I am just collecting the expert annotation now, but based on what i have seen so far that is going to be pretty diverse as well.
By highlighting that neither expert annotation nor the algorithms are consistent with each other I hope to emphasize that behavioural annotation is actually inconsistent in the literature. Furthermore I think that if we can not agree on an omega detection algorithm and expert opinion is diverse as well, then that would be a strong argument to consider the 'behaviour is a continuous spectrum' framework as an alternative to the currently dominant 'behaviour is a set of discrete states' paradigm.
