Jonathan A. Michaels

@jonathanamichaels.bsky.social

How do we move? I study brains and machines at York University (Assistant Professor). Full-time human.

Neural Control & Computation Lab
www.ncclab.ca

@jonathanamichaels.bsky.social

Over time I have realized that I have extremely overdrived theory of mind (often to my detriment), but it has been extremely useful in research.

Tom McCoy@rtommccoy.bsky.social

Since many are starting grad school soon, let me re-share my One Big Tip™️ for research! Research involves many skills - collaborating, writing, presenting, etc. But many of these skills can be unified under a single overarching ability: theory of mind Blog post link in reply

Illustration of the blog post's main argument, summarized as: "Theory of Mind as a Central Skill for Researchers: Research involves many skills.If each skill is viewed separately, each one takes a long time to learn. These skills can instead be connected via theory of mind – the ability to reason about the mental states of others. This allows you to transfer your abilities across areas, making it easier to gain new skills."
@jonathanamichaels.bsky.social

I'm open to ideas, but likely projects would use ATHENA-C – our new markerless motion tracking system – to investigate motor control in different populations (autism, children, stroke, aging), or study learning and motor control in NHPs with our latest high-density neural recording techniques.

@jonathanamichaels.bsky.social

Looking for a postdoc in motor control / systems neuroscience? I'm seeking candidates to develop a Connected Minds Fellowship proposal with me at York University: $70K/yr for 2 years + benefits, plus an $8.5K/yr research allowance. Deadline: Sept 27, 2026. 🧵

@jonathanamichaels.bsky.social

The generic prospective student emails are getting out of hand. I just received virtually identical emails from the first and second author of a paper. One genuine email is worth 1000 generic ones. If you can convince me you're a real human I will very likely want to talk to you.

@jonathanamichaels.bsky.social

These days I like to think of my models as “cartoons”. Realistic enough to capture the core patterns we’re interested in, but simple enough to be meaningfully understood.

Philip Ball@philipcball.bsky.social

"The central challenge is no longer building models that reproduce biological behavior, but building models from which causal structure can be inferred." Very sensible paper about not just throwing everything into your simulation or model. arxiv.org/abs/2608.06998

arxiv.orgSimulating is not always understanding: When model complexity obscures biologyIn cell biology, computational models of biological systems range from minimal representations with a handful of parameters to whole-cell simulations tracking thousands of molecular species across a c...
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