Where does computational neuroscience stand in the conversation about issues in neuroscience related to statistical power?

I recently read the Button et al. (2013) review “Power failure: why small sample size undermines the reliability of neuroscience” and a followup on it, “Power-up: A Reanalysis of ‘Power Failure’ in Neuroscience Using Mixture Modeling”. These reviews highlight that many sub-fields of neuroscience have low statistical power. I’m wondering where the various subfields of computational neuroscience sit on this spectrum, because I didn’t see it discussed in either of these reviews. If anyone has any good references or insights to share, I would be very appreciative.