#MultilingualCritical

Author: @bradpostle.bsky.social
Publisher: Wiley (' @wiley.com ')

New preprint w/ Malin Styrnal & @martinhebart.bsky.social

Have you ever computed noise ceilings to understand how well a model performs? We wrote a clarifying note on a subtle and common misapplication that can make models appear quite a lot better than they are.

osf.io/preprints/ps...

Very much looking forward to #CCN2025! Would love to see you at our lab's talks and posters, and meet me at the panel discussion in the Algonauts session on Wednesday!

🚨PhD opportunity Fall/Winter
2025🚨
Join me in Geneva Switzerland #unige to learn more about colour perception. Using neuroimaging & computational modelling, you'll be working with an international & interdisciplinary team to understand how we transform light into a colourful world!🧠👁️🌈 #neurojobs

🚨 Also, I’ll soon be looking for a job! Feel free to dm me if you know someone who knows someone who works on something cool. I’m excited to connect and learn about post-doc opportunities (in Europe and beyond)
(6/6)

THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior THINGS-data reflects three large-scale neuroimaging and behavioral datasets of object processing in humans, comprising densely sampled functional MRI and magnetoencephalographic recordings, as well as...

📊 I was involved in launching THINGS-data, containing thousands of fMRI, MEG, and behavioral responses to objects. We show how these can be used to test hypotheses about object vision and semantics. Very proud to have contributed! 💪
elifesciences.org/articles/82580
(5/6)

THINGS Initiative Large-scale behavioral and neuroscience data for object recognition and understanding.

🌐 This work is part of the THINGS initiative founded by @martinhebart.bsky.social and @cibaker.bsky.social . It’s a collaborative effort to improve our understanding of object vision in minds, brains, and models through large, curated datasets.
things-initiative.org
(4/6)

Distributed representations of behaviour-derived object dimensions in the human visual system - Nature Human Behaviour Contier et al. show that dimensions are superior to categories at predicting brain responses to visual objects.

🧠 My latest work focused on how the visual system is organized, and how this structure is linked to properties of objects that matter for perception and behavior. Check out our latest paper: www.nature.com/articles/s41562-024-01980-y
(3/6)

🌇 I work in @martinhebart.bsky.social ‘s lab at the Max Planck Institute in Leipzig, Germany - A fantastic environment to learn and engage with like-minded scientists👩🏻‍🔬👨‍💻! I’m already sad I might have to leave eventually.
(2/6)

🙋 Hello Neuro people! After switching platforms, I thought I should reintroduce myself: I’m a PhD student in cognitive neuroscience. I use fMRI to study how the brain represents the things we see.
#neuroskyence #neuroscience
(1/6)

Really happy to see this out! We show that behavioral judgments of the purpose and social content of observed actions capture a surprisingly large portion of variance in neural representational geometry throughout the action observation network and in ventral temporal cortex: doi.org/10.1101/2024...

I promised to write about my thoughts on the status of the field of neuroAI, some of the big challenges we are facing, and the approaches we are taking to address them. This is super selective on the topic of finding a good model but in my view it affects the field as a whole. Here we go. 🧵

Revealing the multidimensional mental representations of natural objects underlying human similarity judgements - Nature Human Behaviour Hebart et al. developed a computational model of similarity judgements for 1,854 natural objects. The model accurately predicted similarity and revealed 49 interpretable dimensions that reflect both p...

These dimensions are interpretable and capture both perceptual and conceptual properties underlying human similarity judgments. Here, @olivercontier.bsky.social ran an encoding model to identify where in the brain he would find information about these dimensions. 7/n
www.nature.com/articles/s41...

Distributed representations of behaviour-derived object dimensions in the human visual system - Nature Human Behaviour Contier et al. show that dimensions are superior to categories at predicting brain responses to visual objects.

How does our brain allow us to make sense of our visual world? Work led by @olivercontier.bsky.social w/ Chris Baker now out in Nature Human Behaviour provides support for a theoretical framework of behaviorally-relevant selectivity beyond high-level categorization. 🧵
www.nature.com/articles/s41...