@jkaufman wrote a nice post on the progress of C elegans modeling effort in 2011, with a followup post in 2014. Here we are, almost a decade later, and I still have the same question that I would have asked even in 2011 if I had dived into the project.
Considering that we do not know the signs of the connectome weights, what do you think about the strength of explanations that try to explain biological phenomenon (E.g. locomotion) in terms of neural dynamics (e.g. from this model, we propose that there's push-pull circuitry because we see that our model shows these fluctuating membrane potentials)?
My preliminary take: Weak and highly uncertain.
Cook et al., 2019 said "modelling the functions of the nervous system at the abstracted level of the connectivity network cannot be seriously undertaken if a considerable number of nodes or edges (for example, edges that represent electrical couplings) are missing." I would think that misdirected edges might just be as harmful as missing edges.
Why doubt the preliminary take?
I have seen commentaries in papers like Kunert et al., 2014 and Kim et al., 2019 that analyze neuronal dynamics from the model (E.g. oscillatory dynamics were observed in membrane potentials of neuron set A if neuron set B are stimulated). I don't doubt the methodological contributions of the paper, but I wonder if it's worthwhile to produce a study that is purely an analysis of the dynamics of such a model, given the uncertainties in the connectome.