Decoding predicted future states from the brainβs βphysics engineβ
Using fMRI in humans, this study provides evidence for future state prediction in brain regions involved in physical reasoning.
Thrilled to announce our new publication titled 'Decoding predicted future states from the brain's physics engine' with @emiecz.bsky.social, Cyn X. Fang, @nancykanwisher.bsky.social, @joshtenenbaum.bsky.social
www.science.org/doi/full/10....
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17.06.2025 18:23 β π 48 π 19 π¬ 1 π 2
What shapes the topography of high-level visual cortex?
Excited to share a new pre-print addressing this question with connectivity-constrained interactive topographic networks, titled "Retinotopic scaffolding of high-level vision", w/ Marlene Behrmann & David Plaut.
π§΅ β 1/n
16.06.2025 15:11 β π 64 π 24 π¬ 1 π 0
VSS SymposiaSymposia β Vision Sciences Society
Super excited for our #VSS2025 symposium tomorrow, "Model-optimized stimuli: more than just pretty pictures".
Join us to talk about designing and using synthetic stimuli for testing properties of visual perception!
May 16th @ 1-3PM in Talk Room #2
More info: www.visionsciences.org/symposia/?sy...
15.05.2025 20:31 β π 25 π 6 π¬ 1 π 0
a man in a blue shirt and tie is pointing at a woman and saying " too legit to quit " .
Alt: a man in a blue shirt and tie is pointing at a woman and saying " too legit to quit " .
Whelp. See you later 1.8 Million in NSF research funds -- all designed to better understand learning mechanisms in early childhood so we can develop effective early childhood educational interventions.
Proud of Harvard for standing up to fascism, though.
We will persist.
15.05.2025 22:31 β π 394 π 63 π¬ 17 π 5
Discriminating image representations with principal distortions
Image representations (artificial or biological) are often compared in terms of their global geometric structure; however, representations with similar global structure can have strikingly...
We are presenting our work βDiscriminating image representations with principal distortionsβ at #ICLR2025 today (4/24) at 3pm! If you are interested in comparing model representations with other models or human perception, stop by poster #63. Highlights in π§΅
openreview.net/forum?id=ugX...
24.04.2025 05:12 β π 38 π 13 π¬ 1 π 0
in sum, we used dominant components of the neural response to get an **axis-sensitive** measure of similarity.
this work fits into a broader look at (R)epresentational alignment (cf. work by @taliakonkle.bsky.social, @itsneuronal.bsky.social, @sucholutsky.bsky.social, & others)
12/n
22.04.2025 20:35 β π 1 π 0 π¬ 1 π 0
we also used connectivity matrices to capture behaviorally-relevant information. a lot like rsa! but with a sparse coding structure
11/n
22.04.2025 20:35 β π 0 π 0 π¬ 1 π 0
using sca and a few different pre-trained models, we found markedly higher alignment to the ventral stream.
rotationally invariant methods were less sensitive to this finding, providing an answer to question 2: DNNs are more similar to the ventral stream along a native axis of neural tuning
10/n
22.04.2025 20:35 β π 0 π 0 π¬ 1 π 0
the resulting matrices represent the activity of sparse sub-populations of neurons/units and, unlike some methods, are quite sensitive to rotations in neural space
you can thus interpret sca as measuring similarity along a specific set of tuning axes
9/n
22.04.2025 20:35 β π 0 π 0 π¬ 1 π 0
we applied the same decomposition to DNN activations and used them in a method we call **sparse component alignment** (sca). sca compares representations at the population level using image x image connectivity matrices.
(see the paper for complete derivation)
8/n
22.04.2025 20:35 β π 0 π 0 π¬ 1 π 0
these response profiles gave an answer to question 1: there are interpretable and functionally-distinct representations across the brain's three visual pathways.
nice to see! but also heightens the mystery of question 2: why aren't these differences picked up by standard similarity metrics
7/n
22.04.2025 20:35 β π 0 π 0 π¬ 1 π 0
to find out, we used a data-driven method to identify dominant components of the neural response to natural images.
some of the most consistent components had pretty clear selectivities, which we cross-validated with behavioral saliency ratings
5/n
22.04.2025 20:35 β π 0 π 0 π¬ 1 π 0
this left us with two big questions:
1. what distinguishes visual representations in the dorsal, ventral, & lateral streams?
2. why does alignment to DNNs often fail to reflect these differences?
4/n
22.04.2025 20:35 β π 0 π 0 π¬ 1 π 0
yet neural networks trained to perform a single task seem to model all three pathways pretty well. so perhaps the representations in these streams are not so different after all?
3/n
22.04.2025 20:35 β π 0 π 0 π¬ 1 π 0
it's commonly thought that the brain processes distinct visual information along separate functional pathways (the dorsal, ventral, & lateral streams)
2/n
22.04.2025 20:35 β π 1 π 0 π¬ 1 π 0
A 19-year-old university student from Gaza I know, who is brilliant and charming and usually upbeat, just wrote back: "we are not OK. The bombing is continuous and non-stop. Please pray for us. Happy Eid to you."
30.03.2025 14:18 β π 19 π 5 π¬ 0 π 0
Technical Associate I, Kanwisher Lab
MIT - Technical Associate I, Kanwisher Lab - Cambridge MA 02139
Iβm hiring a full-time lab tech for two years starting May/June. Strong coding skills required, ML a plus. Our research on the human brain uses fMRI, ANNs, intracranial recording, and behavior. A great stepping stone to grad school. Apply here:
careers.peopleclick.com/careerscp/cl...
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26.03.2025 15:09 β π 64 π 48 π¬ 5 π 3
Science communicator on youtube (I guess?) π¨π¦(https://www.youtube.com/@not_David)
Vision | Neuroscience | Neuroimaging | Aalto University
PhD candidate in CogCompNeuro at JLU Giessen
Exploring brains, minds, and worlds π§ ππΊοΈ
https://levandyck.github.io/
CS+Neuro @cmu.edu⬠PhD Student with Xaq Pitkow and @anayebi.bsky.social⬠working on autonomous embodied AI.
postdoc β’ neuroscience, psychedelics, RL & decision-making, ML @ McGill University / MILA Quebec AI Institute
β’past Google DeepMind London / Montreal
https://veronicachelu.github.io
__
β’meditation enthusiast
β’yogi/200h RYT
β’handbalancer/contortionist
Cognitive scientist, philosopher, and psychologist at Berkeley, author of The Scientist in the Crib, The Philosophical Baby and The Gardener and the Carpenter and grandmother of six.
Research Scientist @META | Guest Researcher @FlatironCCN | Visiting Scholar @NYU | PhD @ZuckermanBrain @Columbia | Neuro & AI Enthusiast
Assistant Professor at UCSD Cognitive Science and CSE (affiliate) | Past: Postdoc @MIT, PhD @Cornell, B. Tech @IITKanpur | Interested in Biological and Artificial Intelligence
Flatiron Research Fellow | Theoretical Neuroscience and Computational Vision
https://www.cns.nyu.edu/~fiquet/
| Cellular/Molecular-turned-Computational Neuroscientist |
| What do neurons even do?? | Neural Computation with Dendrites |
| Biophysical Optimization | AI <-> Neuro |
| Postdoctoral Research Fellow at the Harvard Kempner Institute |
| www.ilenna.com
Official account for the Bergelson Lab at Harvard, sporadically maintained by the PI:).
Just a lab, trying to figure out how babies learn language, somehow caught in the crosshairs of gov't admin battles.
Assistant Professor @UvA_Amsterdam | Cognitive neuroscience, Scene perception, Computational vision | Chair of CCN2025 | www.irisgroen.com
Computational Cognitive Science PhD @JHUCogSci with Leyla Isik | BS @Stanford|
On the faculty job market!
Doing ML/DL with small data - Postdoc @PrincetonU
Making mining sustainable - VP Research @Stratum.AI
Trying to re-democratize AI
Computational Cognitive Neuroscientist at CiNet & Osaka University. Category learning to concepts & everything between (semantic/episodic memory). Cognitive aging/damage in models & brains. To understand the brain & AI.
PhD student in the Object Vision Group at CIMeC, University of Trento. Interested in fMRI and object perception. He/him π³οΈβπ
https://davidecortinovis-droid.github.io/
Assistant Professor at UCLA | Alum @MIT @Princeton @UC Berkeley | AI+Cognitive Science+Climate Policy | https://ucla-cocopol.github.io/
asst prof @Stanford linguistics | director of social interaction lab π± | bluskies about computational cognitive science & language
PhD student Georgia Tech π and LIT Lab. Interested in how brains and machines learn, organize, and use knowledge about the world.
https://w-decker.github.io/