There is already a greater starter thread accompanying the preprint here: bsky.app/profile/neur... But there are a few things we vamped up. 2/n
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The key is that we *very* systematically show how our Dynamical Independence framework works on simple synthetic data. Serving as a step-by-step tutorial on what you can do with it! 3/n
may 14, 2025, 9:12 am • 0 0 • view
An aspect we felt was key to any new method---and often missing---is a *really* transparent, self-contained, and complete example of how to use it. This was our attempt at providing that. 4/n
may 14, 2025, 9:12 am • 0 0 • view
Beyond the thread accompanying the preprint, the main take away should be restated, i.e., this dual aspect of our research program: We want to go #beyond #emergence and capture the dynamical structure of said emergent dynamics. 5/n
may 14, 2025, 9:12 am • 0 0 • view
We show that this dynamical structure is #maximally organised, but #minimally emergent at balanced points of #integration and #segregation, and otherwise, at the extremes of both of these dynamical forces. That is, the macros are maximally emergent, but minimally organised, i.e., fragmented. 6/n
may 14, 2025, 9:12 am • 0 0 • view
Fascinating results (for us anyway!!), that made us wonder about the #scale-integrated nature of #emergent #dynamics in neural systems. This has far reaching consequences for the way we understand brains and minds in humans and machines. And further, how they are structured. 7/n
may 14, 2025, 9:12 am • 1 0 • view
Finally, I think editors and reviewers get a lot of flack. But, to be honest, the review process here was incredibly stimulating and made the work much more complete. Without it, it would not be the work you see before you today. I'd like to thank the reviewers for there care and effort! 8/n
may 14, 2025, 9:12 am • 1 0 • view