Fan L. Cheng

Currently postdoc @KriegeskorteLab | PhD @ykamit Lab | Math, Fudan U 🧐 🧠 💻 #Computational_neuroscience #AI #BMI

[Fan L. Cheng @LibraCheng]

Can we reconstruct our subjective experiences from brain signals? Check our latest paper in @ScienceAdvances w/ my PhD advisor @ykamit and colleagues. We explore how reconstruction methods can advance understanding of neural representations behind illusion.https://t.co/lDPcVXB1pi

[Fan L. Cheng @LibraCheng]

Visual illusions suggest that what we see is not always a direct reflection of the world, but rather a constructed representation. Is it possible to generate images mirroring illusory experiences directly from brain activity?
Check our preprint! https://t.co/KgV2H1dt4r

[Fan L. Cheng @LibraCheng]

You see rotation when you move your eyes, even though the image is 100% static.
Our #CVPR Findings paper uses motion illusions to (1) reveal gaps between human and AI motion processing and (2) identify architectures key for aligning vision models with human perception.
https://t.co/gls6P3Lx2T

[Fan L. Cheng @LibraCheng]

Check out our paper on AI-human comparisons in subjective motion perception!
https://t.co/xK2gzdfRzU

[Isabella Rosario @ierosario98]

Can AI "see" motion from static images like humans?

We tested 10 state-of-the-art vision models (multi-scale, recurrent, and bio-inspired) on the Rotating Snakes illusion, one of the most extensively characterized motion illusions in human and primate vision. Almost all failed — only one bio-inspired model, Dual, predicted motion most closely aligned with human perception, particularly under simulated eye movements.

Accepted to @CVPR Findings!
Paper: https://t.co/zSu4fKvpSq

w/
@LibraCheng @zitangsun @KriegeskorteLab
A 🧵:
#ComputerVision #Vision

[Binxu Wang 🐱 @WangBinxu]

1/
When diffusion generates images from text, before an image has objects, how does each noisy token know what it should become?

In our new work, we found that Diffusion Transformers solve spatial-relation prompts using a circuit motif reminiscent of developmental biology: morphogen-like spatial gradients.

At the start of sampling, image tokens are mostly uninformed noise — like an undifferentiated sheet in an embryo. Relation heads then write smooth spatial gradients onto the image canvas, guiding where objects should emerge.

Accepted as a @CVPR 2026 Highlight🌟: https://t.co/oIC6QKwQ3R
Beautiful collaboration with my friends and colleagues @fjxdaisy & Xu Pan!
A 🧵

[Fan L. Cheng @LibraCheng]

Rotating Snakes illusion (A. Kitaoka 2004)

[Fan L. Cheng @LibraCheng]

Look. The snakes rotate.
Hold still. They stop.
Glance away. They spin again.
We asked 10 visual-motion models to play this game with us. Only one could. 🐍

I'll present "Neural networks reveal candidate computational mechanisms underlying anomalous motion illusion" at #VSS2026

🗓️ May 19th, Tuesday 8:30–12:30
📍 Pavilion, Board 53.435

Welcome to drop by! 👋

w/ @IsabellaRosario @ZitangSun @KriegeskorteLab

[Eivinas Butkus @eivinasbutkus]

1/ New preprint + VSS poster! Attention has long been thought to enable efficient vision. But does it? First demonstration that attention—consuming just 4-5% of the energy budget—can cut the energetic costs of vision in half. #VSS2026

[JohnMark Taylor @johnmark_taylor]

🧵Excited to announce—

"Reimagining the binding problem(s) for the 21st century": A VSS Symposium

St. Pete Beach @VSSMtg
May 15th, 10:30am

Presenters: Peter Tse, JohnMark Taylor, Seda Karakose-Akbiyik, Ana Chica, Anne Sereno, & Jake Quilty-Dunn

https://t.co/sFPA1zuj3L

[Shunsuke Onoo @onoo999]

Our paper "Readout Representation: Redefining Neural Codes by Input Recovery" has been accepted at ICLR 2026🎉🥳

[Kempner Institute at Harvard University @KempnerInst]

🧠What do neurons “want”?✨

Kempner researchers @WangBinxu and @HombreCerebro have developed a way for neurons to train AI image models to match their “preferences.”

Read more about the research, out now in @NatureNeuro, here: https://t.co/p6FJ4FITRY

#neuroscience #NeuroAI

[Paul Linton @LintonVision]

Absolutely wonderful talk by Roland Fleming on “Grasping: measuring and modeling how we use our hands to pick things up” at @ZuckermanBrain

[Surya Ganguli @SuryaGanguli]

I am searching for postdocs interested in developing a deeper scientific understanding of any aspect of AI and using this understanding to improve AI systems. If interested please email me materials by Jan 10th 2026: a CV, 3 letters of reference, and a statement of research interests (can be short, just indicating what you would like to work on).

The positions are generously funded by grants from @schmidtsciences and @SimonsFdn. You will have the opportunity to collaborate with many labs across @StanfordHAI and also the Simons Collaboration on the Physics of Learning and Neural Computation (https://t.co/TfOKlQxCrE).

[Binghao Huang @binghao_huang]

Bringing our Tactile UMI and additional two tactile fingers to NeurIPS! All three authors @YunzhuLiYZ @XinyueYolandaZ and I will be at our poster for demo on Thu 12:00–15:00 in Exhibit Hall C/D/E, #2400.
Otherwise feel free to catch me around the venue Wed–Fri 🙂

[Pinyuan Feng @Pinyuan3]

I’ll be at #NeurIPS2025 in San Diego (Dec 2–6)!

Presenting our "Interpretable Brain Decoding" paper (@KriegeskorteLab,@adeli_hossein,@wenxuan_guo_,@ethanhwang_,@LibraCheng) at the Foundation Models for the Brain and Body Workshop on Dec 6, 3:45–5:00 pm.

Happy to chat!

[Tomoyasu Horikawa @HKT52]

Our "mind captioning" paper is now published in @ScienceAdvances.

The method generates descriptive text of what we perceive and recall from brain activity — a linguistic interpretation of nonverbal mental content rather than language decoding.

https://t.co/Lt48p2pUYS

[Jon Hernandez @JonhernandezIA]

This is gona be the best Ai detector..

It's an image not a video, try it on whatever Ai you want, they won't see the floating heart.

It's the human brain.

[Matthias Michel @MatthiasMichel_]

The MIT Consciousness Club will have a Zoom option for those who would like to join online. First session Friday, Sept 19, 12pm-1:30pm. For more, see: https://t.co/hThTIkJIFE. You can also register to the email list here: https://t.co/cSGzcknLHH.

[Jack Parker-Holder @jparkerholder]

Genie 3 feels like a watershed moment for world models 🌐: we can now generate multi-minute, real-time interactive simulations of any imaginable world. This could be the key missing piece for embodied AGI… and it can also create beautiful beaches with my dog, playable real time

[しらけん (Ken Shirakawa) @kencan7749]

And here’s an experimental podcast-style of paper summary, generated via Notebook LM directed by me!

Link: https://t.co/KwpA4pKeNO

[Fan L. Cheng @LibraCheng]

Realistic-looking images predicted from brain activity ≠ faithful reconstruction of visual experience

[しらけん (Ken Shirakawa) @kencan7749]

Our paper is now accepted at Neural Networks!
This work builds on our previous threads, updated with deeper analyses.

We revisit brain-to-image reconstruction using NSD + diffusion models—and ask: do they really reconstruct what we perceive?
Paper: https://t.co/sb7APaLBQN
🧵1/12

[Fan L. Cheng @LibraCheng]

Congrats, Paul!

[Paul Linton @LintonVision]

Absolute honor to be awarded the David Marr Medal by the Applied Vision Association

Looking forward to my talk “Five Illusions Challenge Our Understanding of Visual Experience”

Thanks so much to NOMIS Foundation, @ItalianAcademy, @columbiacss, @KriegeskorteLab, @ZuckermanBrain