Sreejan Kumar

@ishmailsaboor.bsky.social

Check out our newly released dataset!

Botos Csabi@botoscsabi.bsky.social

[Hugging Face release] We’re releasing the dataset behind Reason to Play! I’m incredibly proud of our team for reaching this milestone.

Sreejan Kumar reposted

Ishmail Abdus-Saboor

Excited to share my lab’s latest preprint led by postdoc @yukihaba.bsky.social and grad student Ryan Schwark. We surprisingly find that spontaneous behavior in isolation predicts a naked mole-rat’s identity, its colony membership, and even rank within its colony. www.biorxiv.org/content/10.6...

arxiv.orgLearning Options for Compositional Motor Control with Adapter BanksLearning flexible motor primitives is a hallmark of skilled motor control. Recent neuroscience theory proposes that motor primitives may be implemented as low-rank perturbations of a shared recurrent ...

Proud to share our new work with @marcelomattar.bsky.social and @leaduncker.bsky.social, newly accepted to #NeurIPS2026 arxiv.org/abs/2609.17042. This paper is a precursor to a forthcoming follow up work that I hope will be one of the biggest papers of my career.

Sreejan Kumar reposted

Botos Csabi

@botoscsabi.bsky.social

11 May

Jeee 🐦‍⬛ I am very proud of our joint effort with @sreejan.bsky.social on the project "Reason to Play" LRMs show human-like rule discovery, and their hidden states predict human brain activity during gameplay 10x better than previous methods Interactive demo + paper: botcs.github.io/reason-to-pl...

botcs.github.ioReason to Play - Behavioral and Brain Alignment32 fMRI-scanned humans and 8 frontier open weight LLMs play ARC-AGI like games with no rules given. The reasoning models match the human learning trajectories and their hidden states predict human bra...

@jonathannicholas.bsky.social

11 Mar

will be at #Cosyne2026 presenting this new work on Saturday's posters session starting 1:15p! Come learn about how many seemingly disparate sensorimotor functions in the brain can be explained by a single anatomical motif and computational framework.

Sreejan Kumar reposted

Jonathan Nicholas

23 Jan

Our experiences have countless details, and it can be hard to know which matter. How can we behave effectively in the future when, right now, we don't know what we'll need? Out today in @nathumbehav.nature.com , @marcelomattar.bsky.social and I find that people solve this by using episodic memory.

nature.comEpisodic memory facilitates flexible decision-making via access to detailed events - Nature Human BehaviourNicholas and Mattar found that people use episodic memory to make decisions when it is unclear what will be needed in the future. These findings reveal how the rich representational capacity of episod...

Sreejan Kumar reposted

Owen Marschall

@omarschall.bsky.social

15 Dec 2025

1/X Excited to present this preprint on multi-tasking, with @david-g-clark.bsky.social and Ashok Litwin-Kumar! Timely too, as “low-D manifold” has been trending again. (If you read thru the end, we escape Flatland and return to the glorious high-D world we deserve.) www.biorxiv.org/content/10.6...

biorxiv.orgA theory of multi-task computation and task selectionNeural activity during the performance of a stereotyped behavioral task is often described as low-dimensional, occupying only a limited region in the space of all firing-rate patterns. This region has...

Sreejan Kumar reposted

Alireza Modirshanechi

@modirshanechi.bsky.social

28 Sept 2025

New in @pnas.org: doi.org/10.1073/pnas... We study how humans explore a 61-state environment with a stochastic region that mimics a “noisy-TV.” Results: Participants keep exploring the stochastic part even when it’s unhelpful, and novelty-seeking best explains this behavior. #cogsci #neuroskyence

Sreejan Kumar reposted

Kris Jensen

@kristorpjensen.bsky.social

24 Sept 2025

I’m super excited to finally put my recent work with @behrenstimb.bsky.social on bioRxiv, where we develop a new mechanistic theory of how PFC structures adaptive behaviour using attractor dynamics in space and time! www.biorxiv.org/content/10.1...

biorxiv.orgSensory Compression as a Unifying Principle for Action Chunking and Time Coding in the BrainThe brain seamlessly transforms sensory information into precisely-timed movements, enabling us to type familiar words, play musical instruments, or perform complex motor routines with millisecond pre...

I'm excited to share that my new postdoctoral position is going so well that I submitted a new paper at the end of my first week! www.biorxiv.org/content/10.1... A thread below

Second, it's known that we build compressed abstractions of our environments that allow us to generalize. What's maybe not known is that this process is intrinsically tied to forming habits and complex action plans!

trackingskills.bsky.socialAlexander Mathis (@trackingskills.bsky.social)Hacker, Computational Neuroscience, ML beyond logistic regression, bear and muscle spindle aficionado. Passionate about open source. #deeplabcut and see https://mathislab.org for more.

Thanks for reading! Special and huge thanks to my co-first author Mathieu Le Cauchois and senior authors @marcelomattar.bsky.social and Jonathon R. Howlett, as well as co-authors @trackingskills.bsky.social l and @leaduncker.bsky.social! The work wouldn't be possible without all of them.

I'm excited to share that my new postdoctoral position is going so well that I submitted a new paper at the end of my first week! www.biorxiv.org/content/10.1... A thread below

This is because sensory compression produces intrinsic, task-independent time encoding trajectories and these dynamics act as a scaffold to implement timing of task-specific behaviors where sensory stimuli guide the *progression* along these trajectories.

What are the implications? First, sensory compression is not just in DLS. It's also in other areas such as Hippocampus and Cerebellum. So we predict that wherever there is sensory compression happening, there is also time encoding and support of time-sensitive behaviors.

I'm excited to share that my new postdoctoral position is going so well that I submitted a new paper at the end of my first week! www.biorxiv.org/content/10.1... A thread below

We then show that this model accounts for seemingly paradoxical findings in time representations in the DLS. First, we show our model explains results that encoding of time in rat DLS is invariant to task relevancy and stimulus properties.

Second, it accounts for another result that shows something contradictory: the DLS actively uses sensory stimuli to time and execute motor habits.

I'm excited to share that my new postdoctoral position is going so well that I submitted a new paper at the end of my first week! www.biorxiv.org/content/10.1... A thread below

We show that a model with a sensory bottleneck accounts for many behavioral effects that @gershbrain.bsky.social and @lucylai.bsky.social characterize in their work on human action chunking, whereas a non-bottleneck baseline does not.

We then see that bottleneck models engage these stable neural trajectories that implicitly encode time by where you are in the trajectory.

I'm excited to share that my new postdoctoral position is going so well that I submitted a new paper at the end of my first week! www.biorxiv.org/content/10.1... A thread below

The DLS is known to be a "bottleneck" in sensorimotor processing. Millions of cortical neurons project onto orders of magnitude fewer striatal cells, producing highly favorable conditions for compression.

To test our hypothesis on the effect of sensory compression on action chunking and time coding, we developed an RNN model with sensory bottlenecks and trained it on RL tasks that involve chunking.

I'm excited to share that my new postdoctoral position is going so well that I submitted a new paper at the end of my first week! www.biorxiv.org/content/10.1... A thread below

What's another function the DLS is involved in? Time encoding! According to a review paper by Edvard and May-Britt Moser (2014 Nobel prize winners), the brain tracks time through "stable neural trajectories" where cell populations fire predictably along a trajectory.

If these functions are co-located, one might believe there's a common mechanism for them. Our work suggests that this mechanism is sensory compression!

I'm excited to share that my new postdoctoral position is going so well that I submitted a new paper at the end of my first week! www.biorxiv.org/content/10.1... A thread below

A primary way this manifests in behavior is through action chunking, where predictable action sequences become compressed into cohesive, reusable units. Think of typing a familiar password, phone number, or playing a well-practiced song on an instrument.

A region of the brain that's a big driver of action chunking is the Dorsolateral Striatum (DLS)

I'm excited to share that my new postdoctoral position is going so well that I submitted a new paper at the end of my first week! www.biorxiv.org/content/10.1... A thread below

Columbia University's Zuckerman Institute

Why do we brush our teeth without having to think about it? Our brain can learn habits through repetition. Habits become automatized in that, once they’re formed slowly over many repetitions, we can execute them automatically without having to “think” about them.

Sreejan Kumar reposted

@zuckermanbrain.bsky.social

29 Apr 2025

Congratulations to all our Columbia scientists recognized with NYAS 2025 Leon Levy Scholarships in Neuroscience: Matthew Eroglu, @yukihaba.bsky.social , @sreejan.bsky.social , Yuta Mabuchi and Keshav Suresh. 👏👏👏 Read more about the Scholars: bit.nyas.org/3Yoa6Pf