Thanks for the invite! Really looking forward to this

1/N: Dear colleagues, I would like to share a new paper on the subiculum, part of my PhD with the Neural Computation Group @andrejbicanski.bsky.social @mpicbs.bsky.social . We present “A theory of subicular function and generalized vector coding” that we call Disco. www.biorxiv.org/content/10.6...

For our next Mind Meeting, we will have @virginievanw.bsky.social (Paris-Saclay University, France).
She will give a talk titled "Making Sense of Time (in the brain)."

🗓 April 2 | 3:00 PM
📍 In person (Zoom available)

Dieser Mann kennt das Navi in Ihrem Kopf | MDR.DE Unser Gehirn hat ein eingebautes Navigationssystem: Es hilft uns, Wege zu finden und sogar Wissen zu ordnen. Der Neurowissenschaftler Christian Doeller hat dieses System entschlüsselt und erhält dafür...

Mehr zu unserem #Leibniz Preisträger Christian Doeller @doellerlab.bsky.social hier zum Reinhören 😀💫🏅: www.mdr.de/wissen/leibn...

Can whole-brain fMRI responses to naturalistic video stimuli be predicted using only transcripts?

Last year, I gave a tutorial on exactly that. Since the response was very positive, I’ve now released both the tutorial notebook and the trained models publicly.

1/N: Dear cognitive map fans, I’d like to share a model I’ve been working on for a while (clearing backlog :). I show how a vector navigation architecture (VNA) and a “positional inference network” (PIN) can build Universal Cognitive Maps (UCMs) for abstract spaces.

www.biorxiv.org/content/10.6...

Now out in Hippocampus. Fei Wang‘s model of Trace Vector Cells and intra-subiculum processing, consistent with know effects in CA1.

onlinelibrary.wiley.com/share/CPZPYM...

Our new preprint is out on bioRxiv! @doellerlab.bsky.social
We show that eye-movement sequences actively organize information by aligning with underlying structure and flexibly adapting to cognitive demands in working memory.

www.biorxiv.org/content/10.6...

Reminder: This is happening tomorrow. @lukaskunz.bsky.social will be giving a talk, titled: Probing the cellular correlates of cognitive maps through human single-neuron recordings.

🧠 The Mind Meeting Series is back!
Organized by us & Bicanski Lab, featuring leading scientists in cognitive and computational neuroscience.

Our first speaker is @lukaskunz.bsky.social (University Hospital Bonn).

🗓 February 12 | 3:00 PM
📍 In person (Zoom available)

We look forward to seeing you!

How do we achieve few-shot generalization? New work led by @fabianrenz.bsky.social dives into the role of replay in learning and using structure to generalize reward. Dream team effort with Shany Grossman @nathanieldaw.bsky.social Peter Dayan & @doellerlab.bsky.social
www.biorxiv.org/content/10.6...

Efficient coding in working memory is adapted to the structure of the environment Huang et al. show that the brain optimizes working memory by compressing information when environmental regularities exist. MEG reveals distinct neural systems for abstract structure and item details,...

Our new paper, now published in Cell Reports, asks how the brain adaptively shapes its representations according to the statistical structure of the environment to overcome the limits of working memory capacity.

www.cell.com/cell-reports...

New preprint: Inference over hidden contexts shapes the geometry of conceptual knowledge for flexible behaviour.

In this pre-reg study, our core claim was that we don’t just learn stimulus-reward. We infer hidden context and that inference re-wires attention and neural state space on the fly.
1/8

Not playing around: Why neuroscience needs toy models Amid the rise of billion-parameter models, I argue that toy models, with just a few neurons, remain essential—and may be all neuroscience needs.

Amid the rise of billion-parameter models, I argue that toy models, with just a few neurons, remain essential—and may be all neuroscience needs, writes @marcusghosh.bsky.social.

#neuroskyence

www.thetransmitter.org/theoretical-...

We’re very happy to share that our work on 3D spatial memory was published in PNAS just before the end of the year! 🎉
Link: www.pnas.org/doi/10.1073/...
(1/8)

Congratulations @maxhinrichs.bsky.social on winning the Best Presentation Award last week at the MPUTC Symposium: Frontiers in Neuroscience & Technology - Emerging Minds.

Probabilistic Foundations of Fuzzy Simplicial Sets for Nonlinear Dimensionality Reduction Fuzzy simplicial sets have become an object of interest in dimensionality reduction and manifold learning, most prominently through their role in UMAP. However, their definition through tools from alg...

New preprint! Have you ever wondered, what are these fuzzy simplicial sets, the theoretical framework behind e.g. UMAP? Here we show that you may simply see them as marginal distributions over simplicial sets. This provides a generative model for UMAP. (1/2)

arxiv.org/abs/2512.03899

Interesting findings with important applications

Work co-first authored with @vigano.bsky.social, together with @bottinilab.bsky.social and @doellerlab.bsky.social
Preprint: doi.org/10.1101/2025...

Entorhinal grid-like codes for visual space during memory formation Nature Communications - Eye movements during scene viewing are tied to grid-like codes in the entorhinal cortex. Grid signals are specific to later remembered scenes, covary with activity in...

✨My first first-author paper is out✨
Entorhinal grid-like codes for visual space during memory formation in @natcomms.nature.com ➡️ rdcu.be/eLRm2
Big thanks to everyone ‪@isabellacwagner.bsky.social‬, @tobiasstaudigl.bsky.social, @olejensen.bsky.social, @doellerlab.bsky.social, @clauslamm.bsky.social

⏳ Deadline approaching! Apply by 13 Oct for the Postdoc in Cognitive Neuroscience at MPI Leipzig.

Dynamic updating of cognitive maps via traces of experience in the subiculum In the classical view of hippocampal function, the subiculum is assigned the role as the output layer. In spatial paradigms, some subiculum neurons manifest as so-called boundary vector cells (BVCs), ...

New preprint from the lab and great work by Fei Wang. We show how subiculum trace vector cells can be modeled consistent with known effects in CA1. Traces are driven by a mismatch learning rule to keep associative memories in line with experience.
www.biorxiv.org/content/10.1...

Join us at the Max Planck Institute in Leipzig as a Postdoc to explore cognitive maps in the human brain: learning, memory & the formation of structural representations. Excellent infrastructure with a leading scientific network. Apply by 13 October: postdocprogram.mpg.de/node/21187

Impact of Task Similarity and Training Regimes on Cognitive Transfer and Interference Learning depends not only on the content of what we learn, but also on how we learn and on how experiences are structured over time. To investigate how task similarity and training regime interact dur...

🚨 New preprint! Impact of Task Similarity and Training Regimes on Cognitive Transfer and Interference 🧠

We compare humans and neural networks in a learning task, showing how training regime and task similarity interact to drive transfer or interference.

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

Congratulations to
@reznikdan.bsky.social
and
@sofievalk.bsky.social
for this tremendous achievement!

Efficient coding in working memory is adapted to the structure of the environment Working memory (WM) relies on efficient coding strategies to overcome its limited capacity, yet how the brain adaptively organizes WM representations to maximize coding efficiency based on environment...

Happy to share our new preprint. We found that brain adaptively switches between relational and item-based coding strategies based on the structure of memory contents.
@doellerlab.bsky.social

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

Excellent outcome of #Algonauts2025 challenge by
@algonautsproject.bsky.social: Phase 1 winners, 2nd overall. Congratulations to everyone involved.

Impact of symmetry in local learning rules on predictive neural representations and generalization in spatial navigation Author summary The hippocampus is a brain region which plays a crucial role in spatial navigation for both animals and humans. Contemporarily, it’s thought to store predictive representations of the e...

Excited to share that our work on the interplay of symmetric learning rules and successor representations (SR) is published in @plos.org (comp.bio)

Work done together with @doellerlab.bsky.social, @caswell.bsky.social and Juergen Jost.

doi.org/10.1371/jour...
#neuroskyence #compneurosky

1/n

Who Does What in Deep Learning? Multidimensional Game-Theoretic Attribution of Function of Neural Units Neural networks now generate text, images, and speech with billions of parameters, producing a need to know how each neural unit contributes to these high-dimensional outputs. Existing explainable-AI ...

🚨Preprint Alert: Who Does What in Deep Learning? Multidimensional Contribution of Neural Units using Game Theory: arxiv.org/abs/2506.19732
The result of my MSc thesis is out with @kayson.bsky.social @fatemehhadaeghi.bsky.social @patrickmineault.bsky.social @kordinglab.bsky.social, Claus C. Hilgetag

📣 Very excited for our symposium on “Building Knowledge Structures” tomorrow at 16:30 at @pug2025.bsky.social

Together with amazing people:
@barnaveliirina.bsky.social
@lukaskunz.bsky.social @mirkothm.bsky.social
and Andrea Greve