Can electrical microstimulation be used to steer cortical population activity on- and off-manifold? Our new preprint says yes — using data-driven control in macaque PFC. Joint work with @gbarzon.bsky.social, Anandita De, Isaac Moran, Conner Carnahan, and Luca Mazzucato.
Can the voice in our heads revolutionize communication for people who can't speak?
Learn how inner speech is decoded from brain activity and the concerns it raises about protecting our private thoughts: pennneuroknow.com/2026/02/17/t... (by @kara-mcgaughey.bsky.social)
#PsychSciSky #SciComm 🧠🟦 🧪
The biggest problem holding neuroscience back right now isn’t data or tools, thanks in large part to the BRAIN Initiative.
It’s fragmentation across species. I wrote this to hopefully spark discussion around an issue that can only be solved as a community👇
www.thetransmitter.org/animal-model...
The basal ganglia output is often framed as a motor gate: corticostriatal circuits select an action, then GPi/SNr-thalamus helps release it. In humans, we find this same pathway carries cognitive variables embedded in movement signals—and even produces learning-relevant signals after feedback. 1/10
Writing a book worth reading *should* take time. It should take effort. The crafting of it and the thinking in it go hand in hand. And the rewards, for both the author and the readers, come from that effort. That the AI bros don't understand this is disturbing and revealing.
Thrilled that my paper is out in the @nature.com. We explored how the brain builds complex tasks by compositionally combining simpler sub-task representations. The brain flexibly performs multiple tasks by dynamically reusing neural subspaces for sensory inputs and motor actions
rdcu.be/eRVUk
Ever wondered what it would be like to see through the eyes of another animal?
Explore the fascinating diversity of eye designs across the animal kingdom in this week's post by @catrinahacker.bsky.social: pennneuroknow.com/2026/02/10/m...
#PsychSciSky #SciComm 🧠🟦 🧪
BREAKING: The Oregon Health & Science University board of directors has voted to begin negotiations with the NIH about potentially transitioning the university’s primate research center to a sanctuary for the animals.
By @callimcflurry.bsky.social
#neuroskyence
bit.ly/4a6mycK
Our paper is out in @natneuro.nature.com!
www.nature.com/articles/s41...
We develop a geometric theory of how neural populations support generalization across many tasks.
@zuckermanbrain.bsky.social
@flatironinstitute.org
@kempnerinstitute.bsky.social
1/14
2026 is proving to be a wonderful year for first time fungi finds so far. Looks like this is the rarely recorded Henningsomyces candidus - tiny little macaroni-like tubes found on a very rotten piece of wood in Southeast England. #fungifriends #fungi #mycology #naturephotography
Sensory adaptation supports flexible evidence accumulation during perceptual decision making https://www.biorxiv.org/content/10.64898/2026.02.03.703553v1
Imagine wearing a #jellyfish as a helmet!?!
Well, that’s exactly what this juvenile jack is doing! Mostly immune to its sting, the jack has taken the jellyfish prisoner.
Shot using #scuba, out over the deep abyss, drifting at night.
#blackwater #blackwaterdiving #scubadiving #gug
You might think mind control is science fiction, but for some fungi it’s just what they do.
Explore the fascinating world of parasitic fungi and how they control infected insects in this week's post by @catrinahacker.bsky.social: pennneuroknow.com/2026/01/27/w...
#PsychSciSky #SciComm 🧠🟦 🧪
Our new paper (with @biotay.bsky.social) is out and on the cover story of @currentbiology.bsky.social !!!! Veronika, a Carinthian mountain cow flexibly uses a “multi-purpose tool” to scratch herself. A video and more information will follow in the comments.
www.cell.com/current-biol...
Writing is thinking
Outsourcing the entire task of writing to LLMs will deprive us of the essential creative task of interpreting our findings and generating a deeper theoretical understanding of the world.
Puzzling red spots in photos from the James Webb Space Telescope are probably young supermassive black holes obscured by dense cocoons of gas
Really thrilled that this paper led by @neurozz.bsky.social is now published in its final version in @elife.bsky.social!!
This is a memory-focused (as opposed to RL-focused) account of the detailed characteristics of forward and backward awake and sleep replay!
elifesciences.org/articles/99931
super excited to share my preprint with @meganakpeters.bsky.social stimulus familiarity shapes hierarchical structure learning and metacognitive dynamics🚀😊!!
osf.io/preprints/ps...
Now on @sciam.bsky.social: A new study uses tools from string theory to improve models of branching neurons, blood vessels, and more. But was string theory's arcane math actually needed for the job?
www.scientificamerican.com/article/does...
Finally out! We studied the retinas of the longest-living vertebrate, the Greenland shark, and found that the retinas remain remarkably healthy in animals around 150 years old. What is the mechanism? It may be a highly efficient DNA repair system. Enjoy!
www.nature.com/articles/s41...
Sea anemones and jellyfish don’t have brains, but the way their neurons behave during sleep shows some surprising similarities to humans
Happy to see the final version of our article out! Brain–computer interfaces as a causal probe for scientific inquiry: Trends in Cognitive Sciences doi.org/10.1016/j.tics.2025.06.017
Our new paper in @sfnjournals.bsky.social shows different neural systems for integrating views into places--PPA integrates views *of* a location (e.g., views of a landmark), while RSC integrates views *from* a location (e.g., views of a panorama). Work by the bluesky-less Linfeng Tony Han.
Thank you! We don't extrapolate our results to consider fMRI, but I've been curious about it and would love to hear if you have any thoughts about the implications.
This work wouldn’t have been possible without the support, expertise, and patience of @nicolecrust.bsky.social and @brettlfoster.bsky.social, the generosity and helpfulness of @simonbohn.bsky.social, and the support of countless others.
(10/10)
A bridge connecting the left side labeled "Animal models, spikes, neural coding mechanisms" with pictures of a mouse, rat, and monkey, to the right side labeled "humans, field potentials, clinical application" with pictures of human patients and someone with a deep brain stimulator. A circle of arrows pointing both directions labeled "basic translational neuroscience" is over the bridge.
These results provide a framework for translating between spikes and LFPs, highlighting the scenarios likely to be fruitful for translation.
I call this “basic translational neuroscience” and I’m excited to continue with this approach in my research moving forward!
(9/10)
Table showing several previous studies that have and have not found alignment between spikes and LFPs. The table shows that variables encoded as magnitude codes and clustered pattern-of-spikes codes have consistently been shown to be aligned between spikes and LFPs, whereas those encoded as salt and pepper pattern-of-spikes codes have not.
And this rule generalizes beyond visual memory!
Sorting previous studies by whether they examined magnitude or pattern-of-spikes codes demonstrates that magnitude codes have consistently been found to be aligned between spikes and LFPs, while heterogenous pattern-of-spikes codes have not.
(8/10)
Schematic showing neural representations as vectors in high-dimensional space. Variables that change the vector magnitude are magnitude codes, whereas those that change the relative angles between vectors are pattern-of-spikes codes. The visual compares these two types of representations in spikes to field potentials in two cases. One where pattern-of-spikes codes are encoded by neurons where those with similar tuning are anatomically clustered (clustered) and another where they are not (salt and pepper). Magnitude codes and clustered pattern-of-spikes codes are aligned between spikes and HGA, whereas salt and pepper pattern-of-spikes codes are not.
We propose that it’s the neural coding scheme of the underlying spiking representation. HGA captures an average of local spikes. This increases signal for variables encoded as overall changes in local magnitude and “washes out” signals encoded as a pattern of heterogeneous responses.
(7/10)
Representational similarity matrix for five categories in spiking activity (left) and high gamma activity (right). The categorical representations (blocks along the diagonal) are clear and strong in spikes but not in high gamma activity.
But when we looked at the neural representations of object category, which are very strong in spiking activity, we found much weaker representations in HGA.
Why is alignment so striking for novelty, recency, and memorability, but not for category? 🤔
(6/10)
A plot of the performance of a decoder trained to distinguish novel from repeated images as a function of how many channels of high-gamma activity or neurons' spiking activity are included in the analysis. Performance grows noticeably faster for high-gamma activity than for spikes.
Not only were the signals well aligned, but we found that novelty signals were STRONGER in HGA than in spikes, requiring at least 4-fold less data to reached matched discriminability of novel from repeated images. In this case, you're better off with one channel of HGA than one neuron.
(5/10)
