It is official🚨: I am joining the department of Psychiatry and Addictology at Université de Montréal! I will be studying the subjective experience of emotions using real-time brain imaging and machine learning. A big thank you to everyone who made this dream come true!

🌟JOB ALERT: Two Lecturer posts. We are excited to announce that we have 2 open academic positions for R&T in Cognitive NeuroImaging/Computational Modelling CCNi_UofGlasgow @UofGPsychology. Closing date: 27 Sept 2021. Please RT. See at my.corehr.com/pls/uogrecruit…

NSD is here. The massive 7T fMRI dataset is now freely available on Amazon S3. Published paper to come soon. Pre-print: biorxiv.org/content/10.110… More info: naturalscenesdataset.org

New paper out in Frontiers - Psychology : Psychophysical features for face-age categorization. In collaboration with Juliane Kloess Ian Charest College of Life and Environmental Sciences Simon Faghel-Soubeyrand, Ph.D.

What type of deep neural nets computations are implemented in the brain such that it modulates our real-world ability to recognize faces? Go check our text and graphical abstract for the #MAIN2021 conference (main2021.org/abstracts) to find out! MAIN Community

Congratulations to PhD student from the lab Simon Faghel-Soubeyrand, Ph.D. for winning a the #MAIN2021 graduate abstract award! Another prize (best postdoctoral award) was also won by a lab alumni, Laurent Caplette; Félicitations à vous deux!

Check out this cool preprint from a lab alumnus Laurent Caplette: a generalization of reverse correlation in terms of both inputs (stimuli made of random CNN features) and outputs (label responses mapped to semantic features) to reconstruct *a lot* of representations.

I show with Marge Livingstone and talia konkle how "face cells" owe their face selectivity to a graded tuning for domain-general attributes rather than to face-specific features such as face parts! biorxiv.org/content/10.110…

We completely revamped this preprint, adding additional theory, background and validation. Please take a look! Basically, it's a method to improve SNR in all experiments comparing some variable across correct and incorrect trials. psyarxiv.com/3s9du/

Come see our VSS poster #36.343 tomorrow PM! We extend our previous method to now uncover the level of abstraction of visual representations in different tasks/contexts. #VSS2022

#VSS2022, my 7th (!) in-person VSS, was amazing!! Lots of cool people and cool science. Poster is now online and ready for V-VSS. Also here it is, if you're curious about our method to investigate the abstraction level of visual representations!

New preprint from the lab with Simon Faghel-Soubeyrand, Ph.D.: We studied the brain computations of "Super-recognisers" using decoding and deep learning models; we reveal that mid-level visual and late semantic processes are enhanced in these individuals with superior face recognition abilities.

New preprint from my PhD (yes I know, 2.5 years later...)! We disentangled information sampling and processing in the brain, observed that information is rhythmically sampled across stimulus time in early visual areas, and more! 🧵👇 [1/9] bit.ly/3OZhmtC

Come check out our poster #346 at #VSS2023 tomorrow AM in Banyan! We propose a method to fit encoding models that generalize to new individuals. This should allow any researcher to reconstruct representations in their expts, given a short common movie or stimulus set

Our paper "Rhythmic information sampling in the brain during visual recognition" is now published in Journal of Neuroscience!t.ly/t6cj We observed rhythmic sampling across stimulus time in the brain and disentangled it from more typical rhythmic processing. 🧵👇1/10

Our paper Reclassifying guesses to increase SNR in psychological experiments is now published in Behavior Research Methods! t.ly/8Xbyq Tremendous work by Gosselin Lab for which I had the pleasure of playing a small part. This can be applied to *many* datasets. [1/3]

Come see our #OHBM2023 poster (#500) Sunday and Monday: Functional alignment of MEG activity during naturalistic movie viewing. We align MEG data of multiple participants in a shared latent space using SRM and improve prediction of new subjects' data. #OHBM

I'm delighted to share with you this Journal Club I wrote for Nature Reviews Psychology on an experimental method that greatly influenced my field and my own research: reverse correlation (and the bubbles method proposed by Gosselin Lab and PhilippeSchyns)! ⬇️⬇️

New paper from the lab now out in PNAS Nexus : Decoding face recognition abilities in the human brain. With Simon Faghel-Soubeyrand, Ph.D., Ian Charest & al.

New paper from the lab now out in Cerebral Cortex. We reveal the time course of brain computations in a well-known case of prosopagnosia, brain-lesioned patient PS. #facerecognition #prosopagnosia #eeg #deepneuralnetworks