Fred Crevecoeur
@fredericcrevec1
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Using behavior and models to study brain functions. Personal-scientific account: science, events and occasionally opinions @fredcrevecoeur.bsky.social
Namur, Belgium
Joined October 2014
In Munich for the 2nd European Motor Control Conference, many thanks to the organisers ! @franklin_lab
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I don't know the media and I did not fact check all things that I don't know for sure, but I've witnessed much of what is described here, and we're in trouble: 👇.
"Scientific fraud has become an industry. And it’s growing faster than legitimate peer-reviewed science journals can keep up with.".
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RT @JCashaback: A very cool new finding from our lab! During a cooperative sensorimotor task, we show that involuntary visuomotor feedback….
biorxiv.org
We have a remarkable ability to seamlessly and rapidly coordinate actions with others, from double dutch to dancing. Humans use high-level partner representations to jointly control voluntary...
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Besides: critical damping as shown in Fig. 1 of the paper can be achieved without FF controller (depends on the mechanical parameters. ).
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Where is the catch? State estimation uses internal models, which if inaccurate produce errors and unintended movement deviations. What do movement errors indicate: wrong IM in the feedback loop or inadequate FF control? We don't know !.
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. aspects of state estimation and their link with cerebellar functions, yet "Kalman filter" or "state estimation" do not even appear in the paper. This is difficult to understand imho. The problem is that feedforward control is largely assumed, never questioned, still unproven.
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Important review on cerebellar circuits, however the theoretical basis is wrong: the obvious error is that feedback driven controllers do perform very well even with long delays, if there is a **state estimator**. There is extended literature on computational and behavioural. .
Cerebellar circuit computations for predictive motor control — a Review by Katrina P. Nguyen & Abigail L. Person.
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Lab outing, visits, outdoors, science, food and lots of fun ! Group pic credit @delhayeben, & Bouillon castle 👇
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This simple model (1) explains a lot of data, (2) makes direct prediction about population activity and low dimensional factors for any task and (3) provides a conceptual framework linking neural population activity and sensorimotor control. .
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🚨Tweeprint by @hariteja11 for our work on neural population dynamics: we show that features of neural population activity during reaching emerge from a simple linear body-network system 🧵👇.
biorxiv.org
Modern large-scale recordings have revealed that motor cortex activity during reaching follows low-dimensional dynamics, thought to reflect sensorimotor computations. However, the origin of these...
🧠What do random neural networks have in common with the motor cortex?. Turns out, a lot!. Both exhibit similar low‑dimensional dynamics across sensorimotor tasks.👇🧵
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Excerpt from longer exchange but this matters, also for committees/panels that use bib metric 👇.
@andpru d) We spend too much time doing things and too little time thinking about it. Lets publish fewer papers. We can do that.
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RT @Harvard: The university will not surrender its independence or relinquish its constitutional rights. Neither Harvard nor any other priv….
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@CosyneMeeting Wondering if the results of the double blind review process presented in the opening remarks are or could be shared publicly? @CosyneMeeting.
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One important thing: @CosyneMeeting has double blind review process and transparent selection rules. Guess what? Reputation biases disappeared. .
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Amazing #cosyne25 @CosyneMeeting !! Exciting science going on, lots of feedback, tons of ideas, wonderful exchanges.
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In Delaware for lab visit and talk with @JCashaback and @NEneeSW .Wonderful time, lots of science going on !!
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RT @GDerosiere: 1/5 Thrilled to share our Perspective in @NatureComms! Collaborating with @SolaimanShokur & @PTVassiliadis on this was such….
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