Cian O'Donnell
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cianodonnell.bsky.social
Cian O'Donnell
@cianodonnell.bsky.social
Computational neuroscientist.
Senior Lecturer at Ulster University in the Great City of Derry, Northern Ireland.
"not articulate enough"
https://odonnellgroup.github.io
predictive coding, RPE, successor representation, and RL more generally. These have been the great success stories of theoretical neuroscience from the past 20 years.

Hard to see how these discoveries could have arisen via experiment and conceptual modelling alone
All theory is wrong until verified by data. Greatly indebted to @mhyaghoubi.bsky.social, @markbrandonlab.bsky.social, @douglasresearch.bsky.social for finding the hippocampus encoding reward prediction! Grateful to my advisor @cpehlevan.bsky.social, @kempnerinstitute.bsky.social.
#RL #hippocampus
Nature research paper: Predictive coding of reward in the hippocampus

go.nature.com/49mB13V
January 19, 2026 at 9:46 AM
Reposted by Cian O'Donnell
All theory is wrong until verified by data. Greatly indebted to @mhyaghoubi.bsky.social, @markbrandonlab.bsky.social, @douglasresearch.bsky.social for finding the hippocampus encoding reward prediction! Grateful to my advisor @cpehlevan.bsky.social, @kempnerinstitute.bsky.social.
#RL #hippocampus
January 19, 2026 at 9:32 AM
the longer genAI has been around, the more and more 'professional' the work I am seeing students submit (code, reports, even presentations)

I'm sure they are learning some good practises from GenAI outputs, by osmosis if nothing else

BUT I'm not seeing basic understanding improving in parallel
And that is: asking a student to do a literature review isn’t really about the output, the final product. It’s about learning the process - assessing the quality of the evidence as you read it, learning how your question may evolve as you engage with the literature, learning how to spot SALIENCE 1/2
January 19, 2026 at 9:11 AM
Reposted by Cian O'Donnell
Reposted by Cian O'Donnell
Starting 2026 with a thread a very recent manuscripts at Ryan Lab @tcddublin.bsky.social @tbsi-tcd.bsky.social

"Extinction and subsequent updating of innate fear responses to a visual looming stimulus rely on hippocampus-dependent mechanisms"
journals.plos.org/plosbiology/...

@PLOSBiology
Extinction and subsequent updating of innate fear responses to a visual looming stimulus rely on hippocampus-dependent mechanisms
How does the brain balance innate responses with adaptive learning when reacting to threats? This study shows that repeated exposure to looming stimuli reduces innate defensive responses via hippocamp...
journals.plos.org
January 2, 2026 at 4:34 PM
Reposted by Cian O'Donnell
Can reward improve memory for what came before it? 🌟

In a registered report with @duncanlabuoft.bsky.social & @megschlichting.bsky.social, we reconcile mixed findings from past studies: reward retroactively boosts associative—but not item—memory, and only in reward-sensitive individuals!
OSF
osf.io
January 12, 2026 at 5:41 PM
Reposted by Cian O'Donnell
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
A unifying account of replay as context-driven memory reactivation
A context-driven memory model simulates a wide range of characteristics of waking and sleeping hippocampal replay, providing a new account of how and why replay occurs.
elifesciences.org
January 15, 2026 at 1:57 PM
my favourite thing about the rise of the xG metric is how much it has boosted statistical thinking among causal football fans

even the 'x' part being short for 'expected'... surely invented by some statistician who once wrote

E[G] = ...
such a great #dataviz showing that football chance creation (xG) is an excellent predictor of team points

if you squint a bit you can also see that good teams overperform xG because they have elite goalscorers, and vice versa

also enjoying the Villa outlier 💜💙

from www.bbc.co.uk/sport/footba...
January 15, 2026 at 1:11 PM
such a great #dataviz showing that football chance creation (xG) is an excellent predictor of team points

if you squint a bit you can also see that good teams overperform xG because they have elite goalscorers, and vice versa

also enjoying the Villa outlier 💜💙

from www.bbc.co.uk/sport/footba...
January 15, 2026 at 1:07 PM
Reposted by Cian O'Donnell
We recently did just that to validate a method to measure functional inter-area interactions, and it worked like a charm (academic.oup.com/nc/article/2...). It also puts the model results appear early in the story (in our case, in fig 3 of a 11-fig paper).
Functional connectivity drifts during sleep as a marker of fluctuations in the level of consciousness
Abstract. During the wake–sleep cycle, consciousness waxes and wanes, and this is thought to be reflected in varying levels of integration between brain ar
academic.oup.com
January 15, 2026 at 10:11 AM
Reposted by Cian O'Donnell
We're already in the phase that each of us (Iranians) by now know someone killed/injured in our circle of friends/family. And this is despite the continued internet blackout, when millions haven't still managed to hear from their family/friends since Thursday, January 8th. This tells a lot ... 😥😥
January 14, 2026 at 9:18 PM
Reposted by Cian O'Donnell
Personally I think this is actually very valuable. 'Conceptual models' can easily ignore important details and may not work in practice. Coding it up (i) makes the details explicit, (ii) ensures they are compatible, and (iii) clarifies to everyone else _exactly_ what the model is.
January 14, 2026 at 5:05 PM
Reposted by Cian O'Donnell
I am calling for a complete and total boycott of the Mercator projection in all news stories about Greenland until every member of the American public has seen this
January 13, 2026 at 5:32 PM
Reposted by Cian O'Donnell
I like the postdiction idea, but tbh feel a lot of 'Figure 7' models in otherwise experimental papers don't meet that bar.

Instead they are often used as confirmation that the main conceptual model put forward by the paper can be reproduced computationally, without necessarily adding extra insights
January 14, 2026 at 4:40 PM
Reposted by Cian O'Donnell
Was reading this: press.princeton.edu/books/hardco... Relevant for here: if there are always multiple theories that could fit with an experimental outcome and vice versa, a lot of back and forth is needed. In that sense it is silly to insist on either one order.
Why Trust Science?
Why the social character of scientific knowledge makes it trustworthy
press.princeton.edu
January 14, 2026 at 8:11 AM
Reposted by Cian O'Donnell
I think that’s a key point: how large is the space of possibilities and how much of it is covered by the modeling approach? That said, I also think of Barbara Webb saying “model early and often” to get true iteration in ideas and experiments and analysis. No one size fits all here.
January 12, 2026 at 6:02 PM
Reposted by Cian O'Donnell
This is the way. Starting very early, eg with parameter/model recovery, can even inform task design. Wish I was more consistent with this.

If you need something to point to, great tutorial paper by Anne Collins & Bob Wilson:
elifesciences.org/articles/49547
Ten simple rules for the computational modeling of behavioral data
Computational modeling of cognitive and neuroscience data is an insightful and powerful tool, but has many potential pitfalls that can be avoided by following simple guidelines.
elifesciences.org
January 12, 2026 at 1:10 PM
Reposted by Cian O'Donnell
On some level, this is just another version of the hypothesis-driven vs. discovery-driven science question. We rarely model first bc we don’t collect data with fine-grained hypotheses in mind. Our hypotheses are things like “mPFC activity will be different in groups A and B.” We collect the data,
January 12, 2026 at 1:45 PM
when doing neuroscience projects I often advocate for computational modelling, followed by data analysis to test model's predictions.

however a few times now I have had pushback from collaborators/reivewers suggesting it would be better to do the data analysis first, then the modelling.

thoughts?
January 12, 2026 at 12:47 PM
Reposted by Cian O'Donnell
Following coverage over the weekend of Sir Paul Nurse's comments that suggested that the only reason that a Fellow should be expelled from @royalsociety.org is scientific misconduct, I have written to him to explain the risks such an attitude poses of increasing sexual harassment in STEM.
January 12, 2026 at 8:59 AM
Reposted by Cian O'Donnell
I know it's hard to shock these days but Elon Musk going full Rhodesia defender and calling for the ethnic cleansing of the US should still shock you.

These are neo nazi views that were only previously shared on explicitly neo nazi sites.
January 11, 2026 at 2:43 PM
Reposted by Cian O'Donnell
Reposted by Cian O'Donnell
There's much talk these days about what's required for "real" intelligence, such as world models and the like. One thing we know about the human evolution of it: it required/requires emotion. That may have been better appreciated in 1938 than today.

archive.org/details/in.e...
January 11, 2026 at 7:51 AM
Such a great idea
For decades, imaging has forced the same trade-off:
Set a frame rate → sacrifice resolution or field of view to go fast.

We break that rule

Using an EVENT-BASED CAMERA, we record neural activity without frames. Signals are captured only where and when they occur:

www.biorxiv.org/content/10.6...
Ultrafast Frame-Free Imaging of Neural Activity with Event Cameras
Frame-based fluorescence imaging has long defined how neural activity is optically measured. This approach requires acquiring all pixels within an image, regardless of whether they carry meaningful ne...
www.biorxiv.org
January 10, 2026 at 2:27 PM
Reposted by Cian O'Donnell
For decades, imaging has forced the same trade-off:
Set a frame rate → sacrifice resolution or field of view to go fast.

We break that rule

Using an EVENT-BASED CAMERA, we record neural activity without frames. Signals are captured only where and when they occur:

www.biorxiv.org/content/10.6...
Ultrafast Frame-Free Imaging of Neural Activity with Event Cameras
Frame-based fluorescence imaging has long defined how neural activity is optically measured. This approach requires acquiring all pixels within an image, regardless of whether they carry meaningful ne...
www.biorxiv.org
January 10, 2026 at 1:41 PM