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...

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...

Super thrilled to finally share the results of our team effort, from the lab of the one and only @ayab.bsky.social. Hopefully it will stir interesting discussions about how the brain balances continuity and segmentation

Aya Ben-Yakov@ayab.bsky.social · 6mo ago

Excited to share a new paper spearheaded by the wonderful @baror-shira.bsky.social: tinyurl.com/bd8xdcum @erc.europa.eu @nathumbehav.nature.com We test the link between serial dependence (as an index of continuity) and event boundaries (indexing segmentation). A few key findings in the thread:

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...

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...

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,...

cell.com

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

Happy to share this early Christmas present 🎄: our paper about geometry- and locomotion-dependence of 3D memory got published in PNAS! Joint work with co-first-author Volker Reisner (@reisnerv.bsky.social) as well as Leonard König, Misun Kim & Christian Doeller www.pnas.org/doi/10.1073/

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

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...

arxiv.org

Our new paper, now published in @natcomms.nature.com , asks a simple question: when two tasks share a common structure, does the brain learn them more efficiently? Surprisingly, this was not the case. Thread below (1/7) rdcu.be/eSwvU

The effects of task similarity during representation learning in brains and neural networks

Nature Communications - Here, the authors show learning tasks with similar structures can initially cause interference and slow down learning, but both the brain and artificial networks gradually...

rdcu.be

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...

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), ...

biorxiv.org

🚨 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...

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...

biorxiv.org

Huge congratulations 🥳 to @sofievalk.bsky.social & @reznikdan.bsky.social for receiving ERC Starting Grants 2025! We're proud of you! Learn more about their projects: www.cbs.mpg.de/2397348/2025...

Sofie Valk and Daniel Reznik receive ERC Starting Grants

Sofie Valk and Daniel Reznik receive ERC Starting Grants

cbs.mpg.de

New theory: Categorization is Baked Into the Brain Categorization is not a late stage of sensory processing but a core computation that begins at the earliest stages, occurring throughout the cortex as predictive feedback shapes feedforward processing. doi.org/10.31234/osf... #neuroscience

🚨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

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 ...

arxiv.org

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

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...

doi.org

📣 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

New preprint! We explored how learned movement patterns affect our sense of traveled distance and proposed a neurocomputational model that leverages embodied memories to denoise spatial codes. 🔗 www.biorxiv.org/cgi/content/...

Re-enacting steps supports human path integration consistent with motor-corrected grid cell drift

Efficient navigation, especially in the absence of vision, requires path integration - the continuous updating of spatial position from self-motion cues. However, path integration is prone to cumulati...

biorxiv.org

🧠 Can a short period of awake, quiet rest help you generalize better? In our new study, we tested this with a learning paradigm comparing offline vs online wake period. www.sciencedirect.com/science/arti...

Delayed emergence of EEG-based task-relevant representations

This paper examines the effect of a period of quiet wakefulness (an “offline wake” state) on the performance of a decision making task. An initial fee…

sciencedirect.com

Our paper in @natcomms.nature.com, we show how cognitive maps in the hippocampal system could solve the general problem of representing and relating multiple alternative action plans.  doi.org/10.1038/s414... With @doellerlab.bsky.social, Patrick Haggard, @vigano.bsky.social, Daniel Reznik