🚨New dataset just dropped🚨 Introducing Places in the Wild: 67,000 RAW-format photographs (45 mpix) densely sampled from 810 places (260 basic-level categories). This is 11x the number of pixels in ImageNet! Preprint is here: arxiv.org/abs/2606.02481 1/
Large image datasets have accelerated progress in cognitive neuroscience and computer vision. However, most datasets are low-resolution, internet-sourced JPEGs with unknown capture conditions and limi...
Now published - the #BANC! A full central nervous system (CNS) connectome of a limbed animal at single-synapse resolution, enabling us to follow sensory-motor arcs and understand how the CNS controls the body. rdcu.be/fncjS. #neuroscience. Video by @quorumetrix.bsky.social 1/18
I'm proud to say we are releasing LAION-fMRI, a densely sampled 7T fMRI dataset of natural images, with very broad stimulus sampling for testing countless hypotheses and for deeply exploring brain representations. The dataset is now available at
laion-fmri.hebartlab.com
What does LAION-fMRI offer? 🧵
I’m happy to share a protocol we’ve been working on for building modular, synchronized multimodal data acquisition systems for systems neuroscience behavior rigs. @mbd1mbd1.bsky.social @arkarupbanerjee.bsky.social
dx.doi.org/10.17504/pro...
Finally, today is the day: Josefine Zerbe will present and release our new multi-echo 7T fMRI dataset LAION-fMRI during #VSS2026, with >30 fMRI session per subject and unprecedented stimulus diversity. Come to Talk Room 1 (Scene perception) today at 5:15. Details will follow in a separate thread!
Story time friends...
Ring attractor networks rely on fine-tuned symmetric connectivity.
The fly head direction network has ring attractor dynamics but heterogeneous connectivity.
How is this possible? 1/🧵
Link: www.biorxiv.org/content/10.6...
Martin Hebart
Martin Hebart
Wei-Chung Allen Lee
Mike Zheng
Two simple ideas for building improved brain encoding models: 1. learn to use representations from all model layers via a gating mechanism + 2. start from natively multimodal features for multimodal predictions. State of the art performance; see mirage-brain.epfl.ch for details #NeuroAI 🧠🤖🧪
New preprint with @lingqiz.bsky.social: Neurodata Without Boredom: Benchmarking Agentic AI for Data Reuse arxiv.org/abs/2605.12808
1/10
A modular toolkit for synchronized multimodal data acquisition in systems neuroscience. Animal behavio. Read full protocol, steps, and materials on protocols.io
Inside bird eyes is a strange and mysterious structure called the pecten oculi. It looks like a pancake flipper, or maybe a radiator. Some 350 years after anatomists first described it, biologists finally figured out its purpose. www.quantamagazine.org/how-the-bird...
Neuropixels + Optogenetics = Neuropixels Opto
Combining high-resolution electrophysiology and optogenetics. 960 sites, 28 emitters, 2 colors.
Today in @natmethods.nature.com
doi.org/10.1038/s415...
Thanks to @wellcometrust.bsky.social, @alleninstitute.org, @hhmijanelia.bsky.social & team.
Video
Quanta Magazine
Matteo Carandini
🧠When you watch a movie, your brain blends sight, sound, and speech into a single experience.
Should models of the brain blend them too, or keep the senses separate until the very end?
We built MIRAGE to find out. It sets a new SOTA for predicting whole-brain fMRI from movies. 🧵
