Thrilled to share the culmination of >4,000 hours of #XROMM analysis, out #OA in @PNASNews! Here we propose a new role for joint mobility in reconstructing vertebrate locomotor evolution -- a small contribution toward reframing this fundamental problem 🦖 pnas.org/content/118/7/…
It’s been a real journey. To collect the necessary data, my life from 2016-2020 became a blur of perpetual point-tracking...
At first, I had myself convinced that joint mobility wasn’t very informative at all (and gave a couple of pretty inflammatory conference talks to that effect -- um, whoops).
But soon I realized that we’ve all been studying mobility based on distorted plots. In early COVID quarantine, I did some ~math~ and figured out that a 16th c. world map could be used to solve the problem.
So I replotted all the data, and here we (finally) are today! These results came as a huge but pleasant surprise to me, and I can’t wait to dig into their morphological basis.
PS, this paper is just the first of many to come from this dataset, and I’ve got some exciting projects in the works -- so keep an eye out for more on #jointsjointsjoints soon! CC @EEB_Brown@BrownMedicine@SICB_DCB_DVM @IntWomxnBiomech
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***disclaimer, I don’t claim to be an expert on any of this, but I’ve made my fair share of mistakes over the past three years, and hopefully learned from some of them 🤞🏽
#XROMM studies like to include graphs with a whole lot of joint angles. Let’s talk about where those numbers come from, because it’s not as simple as you might think — and that actually matters.