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jhennig.bsky.social
Jay Hennig
@jhennig.bsky.social
1.3K followers 410 following 69 posts
Computational neuroscientist interested in how we learn, and dad to twin boys Asst prof at Baylor College of Medicine https://www.henniglab.org/
www.henniglab.org
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · 12h
Playing devil's advocate, but for computation through dynamics, the dynamics don't necessarily have to play out via population spiking activity right? E.g., there could in theory be computations via plasticity dynamics, right?
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · 1d
Congrats Juan!
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Reposted by Jay Hennig
carlosbrody.bsky.social
Carlos Brody @carlosbrody.bsky.social · 3d
Excellent analysis of the Trump compact for universities -- read it, recommend it, share it.

Among the big points: take away the law's predictability and fairness, and instead become entirely subjugated to arbitrary whims of the DOJ.

Dangerous and un-American.

balkin.blogspot.com/2025/10/the-...
Balkinization: The Art of Replacing the Law with the Deal
A group blog on constitutional law, theory, and politics
balkin.blogspot.com
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · 7d
beautiful logo!! nice job
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fannycazettes.bsky.social
Fanny Cazettes @fannycazettes.bsky.social · 8d
Did you know that facial expressions reveal more than meets the eye? 🤯

Our new study shows that even a mouse's face 🐭 can reflect hidden neural computations🧠. Turns out, facial expressions are more than just emotions!

We're so excited to see this paper out @natneuro.nature.com 🎉
🔗: rdcu.be/eIQzO
Facial expressions in mice reveal latent cognitive variables and their neural correlates
Nature Neuroscience - The face reveals more than just emotion. Cazettes, Reato and colleagues show that subtle facial movements reveal hidden cognitive states, reflecting the brain’s ongoing...
rdcu.be
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · 12d
Really intriguing result from the Saxena lab in a multi-tasking RNN for motor control: "Across tasks, population activity occupied a shared, low-dimensional manifold, whereas activity across task epochs resides in orthogonal subspaces." @shreyasaxena.bsky.social

www.biorxiv.org/content/10.1...
Multitasking Recurrent Networks Utilize Compositional Strategies for Control of Movement
The brain and body comprise a complex control system that can flexibly perform a diverse range of movements. Despite the high-dimensionality of the musculoskeletal system, both humans and other specie...
www.biorxiv.org
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Reposted by Jay Hennig
mattgolub.bsky.social
Matt Golub @mattgolub.bsky.social · 13d
(1/n) How can we infer single-trial communication between 🧠 regions? Check out our ICML 2025 paper: “Accurate Identification of Communication Between Multiple Interacting Neural Populations,” by Belle Liu and @jsacks.bsky.social in my lab: arxiv.org/abs/2506.19094
Accurate identification of communication between multiple interacting neural populations
Neural recording technologies now enable simultaneous recording of population activity across many brain regions, motivating the development of data-driven models of communication between brain region...
arxiv.org
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · 14d
stimulus is singular!
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · 14d
haha me too exactly!
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · 14d
one of my favorite games is silently tallying how people pronounce "stimuli"

some say "stim-you-LYE," others say "stim-you-LEE", and then there's those (like me!) who switch randomly
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kristorpjensen.bsky.social
Kris Jensen @kristorpjensen.bsky.social · 14d
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...
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benhayden.bsky.social
Ben Hayden @benhayden.bsky.social · 16d
New manuscript from the lab!

"Mirror manifolds: partially overlapping neural subspaces for speaking and listening"

Led by superstar grad student Anilu Chavez (not on Bluesky)!

www.biorxiv.org/content/10.1...
Mirror manifolds: partially overlapping neural subspaces for speaking and listening
Participants in conversations need to associate words their speakers but also retain those words general meanings. For example, someone talking about their hand is not referring to the other speakers ...
www.biorxiv.org
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Reposted by Jay Hennig
gershbrain.bsky.social
Sam Gershman @gershbrain.bsky.social · 19d
This is one of the most outstanding examples of circuit understanding I've seen in a long time. The unification of theory and experiment is beautiful.

When Malcolm presented this in my lab, the audience was cheering at the end, and one person shouted (non-ironically) "You did it!"
malcolmgcampbell.bsky.social
Malcolm Campbell @malcolmgcampbell.bsky.social · 19d
🚨Our preprint is online!🚨

www.biorxiv.org/content/10.1...

How do #dopamine neurons perform the key calculations in reinforcement #learning?

Read on to find out more! 🧵
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Reposted by Jay Hennig
neurovenki.bsky.social
Venki Murthy @neurovenki.bsky.social · 19d
(edited repost) Thrilled to see our computational work on adaptive shaping of behavior (we call it outcome-based curriculum learning) in PLoS Comp Biol! @wl-tong.bsky.social, @gautamreddy.bsky.social & I formalize curricula in any RL task that can be framed as sequential simple-to-complex behavior.
Adaptive algorithms for shaping behavior
Author summary Animals are commonly trained by ‘shaping’ their behavior using a sequence of simpler tasks towards a complex behavior. Numerous schools of thought have proposed heuristics for shaping b...
journals.plos.org
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Reposted by Jay Hennig
malcolmgcampbell.bsky.social
Malcolm Campbell @malcolmgcampbell.bsky.social · 19d
🚨Our preprint is online!🚨

www.biorxiv.org/content/10.1...

How do #dopamine neurons perform the key calculations in reinforcement #learning?

Read on to find out more! 🧵
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · 28d
Very cool work showing how hippocampal representations could span space, and associative/episodic memories. Thanks for the presentation today Sarthak!
sarthakc.bsky.social
Sarthak Chandra @sarthakc.bsky.social · Jan 17
1/ Super-excited to share our new work “Episodic and associative memory from spatial scaffolds in the hippocampus”, that just appeared in Nature! www.nature.com/articles/s41... Key insights and ideas 👇#tweeprint
Episodic and associative memory from spatial scaffolds in the hippocampus - Nature
A neocortical–entorhinal–hippocampal network model based on grid cell states recapitulates experimental results and reconciles the spatial, associative and episodic memory roles of the hippocampus.
www.nature.com
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cogscikid.bsky.social
cogscikid.bsky.social @cogscikid.bsky.social · 28d
Excited to share recent work on an AI model that doubles as a scalable cognitive theory.

Basic idea: when learning one task, "preplay" other tasks to learn implicit goal-oriented maps that support fast performance later.

This improves AI and predicts human behavior in naturalistic experiments!
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · Sep 4
same plot now colored by general region (with jitter for visibility)
jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · Sep 4
That point with the largest stimulus decoding is CL, the central lateral nucleus, in thalamus
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · Sep 4
Here's a better way of showing this. Each dot shows the average decodability of the stimulus identity (x) and the mouse's decision (y) across neurons within that brain region.
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · Sep 4
Eg, the red bar in the "stimulus" group shows that brain regions that can decode "stimulus" are more likely to decode "choice", with a correlation of R=0.54

This is like mixed selectivity at the brain region level
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · Sep 4
Corollary: If a brain region cares about one aspect of the task it probably cares about other aspects too!

This bar plot shows the correlation between how decodable different task features are across brain areas

(src: github.com/int-brain-la...)
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jhennig.bsky.social
Jay Hennig @jhennig.bsky.social · Aug 25
this is really cool! an rnn paired with continual synaptic plasticity ends up exhibiting a sort of longterm memory that requires the ongoing plasticity
david-g-clark.bsky.social
David G. Clark @david-g-clark.bsky.social · Aug 25
(7/26) The most surprising phenomenology happens after input cessation at t≥0: neurons continue oscillating long after stimulation ends, with lifetimes exceeding any intrinsic system timescale, including the plasticity forgetting timescale, by an order of magnitude (panel iii).
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olveczky.bsky.social
Bence Ölveczky @olveczky.bsky.social · Aug 25
Wrote a eulogy for the yellow letters in my office window. www.thecrimson.com/article/2025...
My Lab Displayed A Message of Solidarity on Our Windows. Harvard Took It Down. | Opinion | The Harvard Crimson
If we continue down this path, we risk not only Harvard’s future as an institution of free inquiry and expression but also its integrity and trustworthiness.
www.thecrimson.com
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sromeropinto.bsky.social
Sandra Romero Pinto @sromeropinto.bsky.social · Aug 13
My first paper with @naoshigeuchida.bsky.social is finally out in @natcomms.nature.com ! rdcu.be/eACGf

TL;DR: asymmetric learning rates can be induced by shifts in tonic dopamine giving rise to pessimistic/optimistic biases in agents or animals undergoing reinforcement learning .
Tonic dopamine and biases in value learning linked through a biologically inspired reinforcement learning model
Nature Communications - Accurate future predictions are essential for guiding behavior, and disruptions in this process are associated with psychiatric disorders. Here the authors show that changes...
rdcu.be
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