The 2026 SfN Outstanding Career and Research Achievements awards recognize those whose research has significantly advanced the field of neuroscience and open new avenues of exploration. Nominate a colleague, friend, or peer by Thursday, May 7. 🔗 vist.ly/4wx9j #neurosky

📢📢 Announcing this year's conference on the Mathematics of Neuroscience & AI (Rome, 9-12th June). We’ve got a stellar line-up and venue, and invite everyone to join: www.neuromonster.org

Thank you for having me on BrainInspired, Paul @braininspired.bsky.social! It was such an honor to be on my favorite show—a rare place where we can leisurely talk about manifolds, latent circuits, power laws, and other esoteric ideas, and still be taken seriously in knowing they are all real.

Paul Middlebrooks@braininspired.bsky.social · 8mo ago

Are manifolds real? Are latent circuits real? Tatiana @engeltatiana.bsky.social uses one, infers the other, and says yes to both. Also, how timescales are different and the same across the entire brain... braininspired.co/podcast/226/

Our work with @pawa-pawa.bsky.social is out in Nature Machine Intelligence! The choice of activation function affects the representations, dynamics, and circuit solutions that emerge in RNNs trained on cognitive tasks. Activation matters! www.nature.com/articles/s42...

Single-unit activations confer inductive biases for emergent circuit solutions to cognitive tasks - Nature Machine Intelligence

Recurrent neural networks are widely used to model brain dynamics. Tolmachev and Engel show that single-unit activation functions influence task solutions that emerge in trained networks, raising the ...

nature.com

Pavel Tolmachev@pawa-pawa.bsky.social · 9mo ago

Excited to share our new work with @engeltatiana.bsky.social! RNNs are often used to explore how the brain may solve specific tasks. We show that, depending on the architecture, RNNs find distinct circuit solutions, behaving differently when exposed to novel stimuli. www.nature.com/articles/s42...

A study led by Cina Aghamohammadi is now out in ‪@natcomms.nature.com‬! We developed a mathematical framework for partitioning spiking variability, which revealed that spiking irregularity is nearly invariant for each neuron and decreases along the cortical hierarchy. www.nature.com/articles/s41...

Two flagship papers from the International Brain Laboratory, now out in ‪@Nature.com‬: 🧠 Brain-wide map of neural activity during complex behaviour: doi.org/10.1038/s41586-025-09235-0 🧠 Brain-wide representations of prior information in mouse decision-making: doi.org/10.1038/s41586-025-09226-1 +

Princeton’s @ilanawitten.bsky.social, @engeltatiana.bsky.social, and @jpillowtime.bsky.social have created the first-ever brain-wide activity map during decision making in mice as part of an international group effort known as the @intlbrainlab.bsky.social. 🔗 pni.princeton.edu/news/2025/fi...

New work with @shiyanliang.bsky.social‬, @roxana-zeraati.bsky.social, @intlbrainlab.bsky.social, Anna Levina. We uncover the principles that organize single-neuron timescales across the entire brain, unifying regional specialization with universal brain-wide dynamics: www.biorxiv.org/content/10.1...

Yanliang Shi@shiyanliang.bsky.social · 11mo ago

Excited to share our new preprint on the brain-wide organization of intrinsic timescales at single neuron resolution. Work w/ @roxana-zeraati.bsky.social, @intlbrainlab.bsky.social, Anna Levina, @engeltatiana.bsky.social : www.biorxiv.org/content/10.1...

Out today in @nature.com: we show that individual neurons have diverse tuning to a decision variable computed by the entire population, revealing a unifying geometric principle for the encoding of sensory and dynamic cognitive variables. www.nature.com/articles/s41...

“Like a group of skiers descending a mountain, each [neuron] prefers a slightly different path, but all are shaped by the same slope,” says PNI's @engeltatiana.bsky.social‬ on her lab’s new ‪@nature.com‬ study revealing how the brain makes decisions. 📰: pni.princeton.edu/news/2025/al...

Into population dynamics? Coming to #CNS2025 but not quite ready to head home? Come join us! at the Symposium on "Neural Population Dynamics and Latent Representations"! 🧠 📆 July 10th 📍 Scuola Superiore Sant’Anna, Pisa (and online) 👉 Free registration: neurobridge-tne.github.io #compneuro

Our new paper with @chrismlangdon is just out in @natureneuro.bsky.social! We show that high-dimensional RNNs use low-dimensional circuit mechanisms for cognitive tasks and identify a latent inhibitory mechanism for context-dependent decisions in PFC data. www.nature.com/articles/s41...

Latent circuit inference from heterogeneous neural responses during cognitive tasks - Nature Neuroscience

The latent circuit model identifies low-dimensional mechanisms of task execution from heterogenous neural responses. This approach reveals a latent inhibitory mechanism for context-dependent decisions...

nature.com

Christopher Langdon@cmlangdon.bsky.social · last yr.

(1/5) Excited to share my work with @engeltatiana.bsky.social , out now in Nat Neuro! We show that RNNs use low-d latent circuit mechanisms for cognitive tasks. We find that context-dependent decisions in both RNNs and PFC arise from latent inhibitory mechanisms. www.nature.com/articles/s41...

The latent circuit model identifies low-dimensional mechanisms of task execution from heterogeneous neural responses. This approach revealed a latent inhibitory mechanism for context-dependent decisions in neural network models and prefrontal cortex 🧪🧠 www.nature.com/articles/s41...

Latent circuit inference from heterogeneous neural responses during cognitive tasks - Nature Neuroscience

The latent circuit model identifies low-dimensional mechanisms of task execution from heterogenous neural responses. This approach reveals a latent inhibitory mechanism for context-dependent decisions...

nature.com