Ahead of @thetransmitter.bsky.social's first-ever University Roadshow in the United Kingdom, here’s a roundup of news and perspectives featuring U.K.-based neuroscientists. #neuroskyence

2025: A Review of the Year in Neuroscience Enlightening the brain

Highly recommend this series by @markdhumphries.bsky.social if you are interested in neuroscience. I have been irregularly reading it for about 5 years. Always great!
medium.com/the-spike/20...

Job!

My lab is hiring a pre-doctoral research assistant to work on the neural computations of foraging, seeking common cross-species algorithms. In collaboration with @brainapps.bsky.social & Nathan Lepora.

Closes April 21st

Pls share!

jobs.nottingham.ac.uk/vacancy.aspx...

How can we build better experiment-theory collaborations in neuroscience?

We're hosting a series of 6 in-person, interactive workshops to discuss this.

Come along!

www.eventbrite.co.uk/e/understand...

#Cosyne2026

How does motor cortex control discrete and rhythmic movements of the arm - the same or different?

Find out at our poster 3-014 this afternoon!

Work led by
@andreacolins.bsky.social

Congratulations Adrien and team, a cool paper. Particularly like the excellent use of the train-decoder-now, test-decoder-later trick!

New paper alert! 🚨

We found that the brain's compass is remarkably stable at two scales

1️⃣ the system maintains its internal organization for weeks
2️⃣ It "remembers" its orientation for weeks, even after a single visit

This may be key to how the brain aligns its other maps.

Paper: rdcu.be/e3waP

Epstein’s ugly world of science As with Peter Mandelson, so in the science world: the Epstein files are not telling us anything that most ordinary punters didn’t already know, but are revealing the full, rotten, appalling extent …

Just added this to my WordPress site, so it's free to read.
homunculusmusic.wordpress.com/2026/02/14/e...

I missed some exciting stuff last year!

I can't believe it took me this long to find @markdhumphries.bsky.social on Bluesky, but his annual review makes up for the lost time. On excellent form as always.

Thanks Anastasia. I’ve been a lot quieter of late!

Great read as always. There is clearly accelerating tension between ever more complex computational approaches applied to brain data and actually figuring stuff out about the brain.

2025: A Review of the Year in Neuroscience Enlightening the brain

Just published my review of neuroscience in 2025, on The Spike.

The 10th of these, would you believe?

This year we have foundation models, breakthroughs in using light to understand the brain, a gene therapy, and more

Enjoy!

medium.com/the-spike/20...

Fair point! Yes, I think a lot of the problem is in the hype of what they promise, not the interesting and often innovative technical work underneath

Thanks Nicole. Not sure I’ll manage another 10!

Always full of insightful laughs! Thank you for keeping it up for 10 years, @markdhumphries.bsky.social.

" ... It can though predict with fair accuracy the activity of held-out neurons during videos of natural scenes. Scenes like driving through a desert. As mice do ... "

That’s a great quote!

Great summary, thanks for writing this!

One nit, we started the 'core' merely as a shared feature space for (translation invariant) visual neurons*. Simple idea, not to be conflated with all the 'foundation model' and 'digital twin' marketing later 😜

* proceedings.neurips.cc/paper/2017/f...

Thanks David, and thanks for sharing your NeuriPs paper - good to see the smart ideas underneath the behemoth.
Especially fun to see you proposed the barcode idea at the end!

2025: A Review of the Year in Neuroscience Enlightening the brain

Just published my review of neuroscience in 2025, on The Spike.

The 10th of these, would you believe?

This year we have foundation models, breakthroughs in using light to understand the brain, a gene therapy, and more

Enjoy!

medium.com/the-spike/20...

🚨Funded PhD studentship project🚨
"Leveraging population activity trajectories to optimise Brain-computer interfaces for arm movement" with myself & @katjakornysheva.bsky.social

By: Jan 9th 2026

Info on project, funding & how to apply:  more.bham.ac.uk/mrc-aim/phd-... (submit to Nottingham)

Read yet another review today that ascribes GECIs' larger SNR vs GEVIs to their being evolved earlier (suggesting the GECIs are better optimized). This assumption is understandable but incorrect. GEVIs' photonic response per molecule per AP have been as good as GECIs since ASAP3.

Terrific work led by @emmaroscow.bsky.social showing that hippocampal replay reflects events with large prediction errors, all the better to bootstrap learning as we slumber

Congratulations to Matt Jones & Nathan Lepora for seeing this through to the end!

www.nature.com/articles/s41...

🧪Preprint!
How foragers depart from optimal models can tell us a lot about how they compute their decisions.

A strong but underexplored departure is that foragers widely vary when they leave identical patches.

A 🧵
doi.org/10.1101/2025...

With
@emmavscholey.bsky.social @brainapps.bsky.social

Excited to share our preprint on variability in patch leaving decisions! Check out the 🧵 below

Super pleased with this one, led by the amazing PhD student and foraging expert @emmavscholey.bsky.social!

A nice example of how sequential and simultaneous choice can fundamentally differ: in the latter, the longer a subject waits to decide, the more variable their decision time.

We show foraging decisions can have independence of decision time and variability, or even an inverted relationship!

End 🧵

In another weird prediction, we show that if the reward in a patch decays linearly when harvested, then the forager should be *more* variable the *earlier* they leave

Also exactly what we see in data: foragers leave earlier in rich environments but are more variable (data, solid; model, dashed)

Perhaps the weirdest prediction is that, under a wide range of conditions, foragers’ stochasticity is independent of when they leave. In other words, their variability is decoupled from their reward information

And that’s exactly what we see in the data (solid lines; model predictions: dashed)

We ask if foragers’ variability can be explained by them making deliberately stochastic leaving choices: basically, whether they flip a biased coin

We show deliberately stochastic choice makes weird predictions for how foragers’ respond to their environment, and test them across tasks and species