Fred Crevecoeur

Using behavior and models to study brain functions. Personal-scientific account: science, events and occasionally opinions
@fredcrevecoeur.bsky.social

[Fred Crevecoeur @fredericcrevec1]

🚨🚨 We're hiring !! Come work in an international, collaborative and stimulating environment on mechanisms of human upper limb motor control
👇👇👇
https://t.co/omP4Id0Dhc

[Fred Crevecoeur @fredericcrevec1]

This is not so clear... In fact the evidence that we have for finite horizon control in the sensorimotor system may not be what we think ! Especially, the effect of rewards and nonlinearities modulate feedback gains in finite and infinite horizons schemes...

[Fred Crevecoeur @fredericcrevec1]

Fun collaboration with @andpru @AntoineComite @hariteja11 on the merits of infinite horizon control model: how does the brain select a movement time?

Infinite horizon control captures modulation of movement duration in reaching movements https://t.co/IJGzC8wfHX

[Fred Crevecoeur @fredericcrevec1]

The computational approach developed here could be a powerful mean to assess goal-directed changes in gait control in clinical populations... (stay tuned ! 😉 )

[Fred Crevecoeur @fredericcrevec1]

Preprint alert 🚨:Measured and modelled transitions between self-paced walking and synchronization with rhythmic auditory cues
👇
https://t.co/rG6pLJHTw6

[Fred Crevecoeur @fredericcrevec1]

Here we show how these changes in control strategy are modulated by auditory inputs and how they can be simulated in theory: the model suggests that the change is really fast (1 stride?) but the consequence is only visible after long stride series...

[Fred Crevecoeur @fredericcrevec1]

In Munich for the 2nd European Motor Control Conference, many thanks to the organisers ! @franklin_lab

[Fred Crevecoeur @fredericcrevec1]

https://t.co/7ardb0OiYh

[Fred Crevecoeur @fredericcrevec1]

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: 👇

[Retraction Watch @RetractionWatch]

"Scientific fraud has become an industry. And it’s growing faster than legitimate peer-reviewed science journals can keep up with."
https://t.co/LOJJocAHrY

[Josh Cashaback @JCashaback]

A very cool new finding from our lab! During a cooperative sensorimotor task, we show that involuntary visuomotor feedback responses reflect a representation of a partner. https://t.co/87z0NqV5O0
Led by the extremely talented, @SethSullivan_

[Fred Crevecoeur @fredericcrevec1]

In Maastricht for @ISPGR, come check our work this afternoon ! P02-M-100 by Clémence Vandamme

[Fred Crevecoeur @fredericcrevec1]

Besides: critical damping as shown in Fig. 1 of the paper can be achieved without FF controller (depends on the mechanical parameters...)

[Fred Crevecoeur @fredericcrevec1]

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...

[Nature Rev Neurosci @NatRevNeurosci]

Cerebellar circuit computations for predictive motor control — a Review by Katrina P. Nguyen & Abigail L. Person

https://t.co/nK1re6QZBU

[Fred Crevecoeur @fredericcrevec1]

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 !

[Fred Crevecoeur @fredericcrevec1]

Lab outing, visits, outdoors, science, food and lots of fun ! Group pic credit @delhayeben, & Bouillon castle 👇

[Fred Crevecoeur @fredericcrevec1]

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...

[Fred Crevecoeur @fredericcrevec1]

🚨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 🧵👇
https://t.co/QAFj1IEgcg

[Hari @hariteja11]

🧠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.👇🧵

[Fred Crevecoeur @fredericcrevec1]

Excerpt from longer exchange but this matters, also for committees/panels that use bib metric 👇

[Kording Lab 🦖 @KordingLab]

@andpru d) We spend too much time doing things and too little time thinking about it. Lets publish fewer papers. We can do that.