Gosselin Lab

Frédéric Gosselin's lab @ University of Montreal // Studying face, object and scene recognition using behavioral methods, eye-tracking and neuroimaging

[Gosselin Lab @GosselinLabo]

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

[Gosselin Lab @GosselinLabo]

New paper from the lab now out in @PNASNexus : Decoding face recognition abilities in the human brain. With @SoubeyrandF, @IanCharest & al.

[Laurent Caplette @laucaplette]

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

[Laurent Caplette @laucaplette]

Our paper Reclassifying guesses to increase SNR in psychological experiments is now published in Behavior Research Methods! https://t.co/2NFlYuPSHy Tremendous work by @GosselinLabo for which I had the pleasure of playing a small part. This can be applied to *many* datasets. [1/3]

[Laurent Caplette @laucaplette]

Our paper "Rhythmic information sampling in the brain during visual recognition" is now published in Journal of Neuroscience!https://t.co/GLVXjfz5Ot We observed rhythmic sampling across stimulus time in the brain and disentangled it from more typical rhythmic processing. 🧵👇1/10

[Laurent Caplette @laucaplette]

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

[Laurent Caplette @laucaplette]

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] https://t.co/3dIVYgVXWV

[Gosselin Lab @GosselinLabo]

New preprint from the lab with @SoubeyrandF: 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.

[Laurent Caplette @laucaplette]

#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!

[Laurent Caplette @laucaplette]

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

[Laurent Caplette @laucaplette]

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.
https://t.co/0JW5oZTMEC

[Kasper Vinken @kasper_vinken]

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! https://t.co/r7j58GRU1R

[Gosselin Lab @GosselinLabo]

Check out this cool preprint from a lab alumnus @laucaplette: 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.

[Laurent Caplette @laucaplette]

Our preprint "Computational reconstruction of mental representations using human behavior" is finally out! 😊We developed a general framework to reconstruct many visual representations. https://t.co/jdM0HJZrj1 [1/8]

[Gosselin Lab @GosselinLabo]

Congratulations to PhD student from the lab @SoubeyrandF for winning a the #MAIN2021 graduate abstract award! Another prize (best postdoctoral award) was also won by a lab alumni, @laucaplette; Félicitations à vous deux!

[Gosselin Lab @GosselinLabo]

New paper out in @FrontPsychol : Psychophysical features for face-age categorization. In collaboration with @JulianeKloess @IanCharest @LES_UniBham @SoubeyrandF

[cvnlab @cvnlab]

NSD is here. The massive 7T fMRI dataset is now freely available on Amazon S3. Published paper to come soon. Pre-print: https://t.co/ckwMq24LlY More info: https://t.co/ItDgijuCwq

[CCNi_UofGlasgow @CCNi_UofG]

🌟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_UofG @UofGPsychology. Closing date: 27 Sept 2021. Please RT.
See at https://t.co/tN1fNHHijR

[Vincent Taschereau-Dumouchel @Vincent_T_D]

It is official🚨: I am joining the department of Psychiatry and Addictology at @UMontreal! 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!

[Gosselin Lab @GosselinLabo]

New paper! We probed the precise time course of SF use during scene recognition and show that there's no clear coarse-to-fine pattern and that it depends on the task. With @laucaplette, S. Wiesmann, V. Willenbockel and Melissa Võ. https://t.co/9V6LquD7Ht