I am a CNRS researcher at the Department of Cognitive Science of Ecole Normale Supérieure. My group investigates the computational bases of human intelligence, and in particular our perceptual and language processes, using machine learning for electrophysiology, neuroimaging and computational modeling.
In my spare time, I am a core developer of MNE-Python, an open source package for processing human electrophysiological data.
Want to work on the topic with us? Contact me!
Caucheteux & King, bioRxiv 2020
tl;dr: Do deep nets become increasingly correlated with brain activity as they learn to process language? Short answer: only their middle layers do.
Back-to-back regression: Disentangling the influence of correlated factors from multivariate observations
King, Charton, Lopez-Paz & Oquab, Neuroimage 2020
tl;dr: We introduce a simple method to combine the advantages of decoding and encoding analyses.
Back-to-back regression: Disentangling the influence of correlated factors from multivariate observations.— Jean-Rémi King (@jrking0) July 9, 2020
Our latest paper with @f_charton, David Lopez Paz & Maxime Oquab at @facebookai is now freely available at Neuroimage: https://t.co/2hBgODEeAw
Here's the summary thread ⤵️ pic.twitter.com/i1ZLF2dZ5e
Peiffer-Smadja, Maatoug, Lescure, D’Ortenzio, Pineau & King, Nature Machine Intelligence 2020
tl;dr: We’re teaming up with the AP-HP hospital to review the promises and pitfalls of Machine Learning.
"#MachineLearning for #COVIDー19 needs global collaboration and data-sharing"
#ArtificialIntelligence #SARSCoV2 pic.twitter.com/lZsZh8Hqvm</p>— Nathan Peiffer-Smadja (@nathanpsmad) May 22, 2020
Gwilliams, King, Marantz & Poeppel, bioRxiv 2020
tl;dr: Decoding the neural dynamics underlying phonetic representations shows how the brain can keep up multiple phonemes until the corresponding word is identified.
our new paper "Neural dynamics of phoneme sequencing" is now on bioRxiv!https://t.co/jeTipPTXuf— Laura Gwilliams (@GwilliamsL) April 6, 2020
conducted with dream-team @jrking0 @AlecMarantz @davidpoeppel, we use MEG to study how phonemes are processed in continuous naturalistic speech
short summary in thread below:
Wyart and King, bioRxiv 2019
tl;dr: We measure brain responses to image sequences, and show how the brain recruits a hierarchy of neural processes in order to efficiently represents multiple snapshots of the past. Check-out our tweet thread for the illustrated summary
Gwilliams and King bioRxiv 2019
tl;dr: When an image is ambiguous, the brain slowly recruits a hierarchy of recurrent processes to generate categorical percepts. Check-out our tweet thread for the illustrated summary
0/9: "Recurrent Processes Emulate a Cascade of Hierarchical Decisions", by @GwilliamsL and I, the tl;dr thread:— Jean-Rémi King (@jrking0) November 15, 2019
3/9 Their average brain response confirm a fast feedforward recruitment of their visual hierarchies pic.twitter.com/Y39WYwJ2Yx— Jean-Rémi King (@jrking0) November 15, 2019
Claassen et al, New England Journal of Medicine 2019
tl;dr: Acute brain injury patients can sometimes be behaviorally unresponsive. Yet, we show that 15% of them still demonstrate motor-command brain responses.