Casper Kerrén

Illustration of the hypothesized flows of information between perception, memory and cognitive control in a conceptual model of working memory. Stimuli attributes are processed to varying degrees of abstraction and parts of these representations can be loaded into working memory under the guidance of cognitive control. Familiar stimuli such as the letter B activate visually abstract representations while less familiar stimuli are limited to sensory representations. Information can be shifted both up and down levels of the perceptual hierarchy to build either more or less abstract representations of either perceived or imagined stimuli. Working memories can be shifted into or out of the hierarchy as needed.

We recently published a theoretical review about how compositional and generative mechanisms in working memory provide a flexible engine for creative perception and imagery.

Pre-print:
osf.io/preprints/ps...

Paper: www.sciencedirect.com/science/arti...

Adaptive episodic memory: how multiple memory representations drive behavior in humans and nonhumans | Physiological Reviews | American Physiological Society Episodic memory is a declarative long-term memory of a specific past experience. As such, it is multifaceted, encompassing both the objective and subjective components of that experience. These components can be flexibly represented at different levels of granularity, from precise, context-specific details to generalized, gistlike representations. In this review, we suggest that 1) multiple representations of an episodic memory at different levels of granularity are simultaneously encoded into a memory trace and 2) the relative weighting of these representations determines the extent to which a memory is reconstructed or reproduced at retrieval. We propose that this representational flexibility drives adaptive behavior by prioritizing reconstruction or reproduction depending on the age of the memory, its relationship to prior knowledge, current attentional goals or task demands, and individual differences. Drawing on research in humans and nonhuman animals, we show a close correspondence between psychological and neural representations of a memory across encoding, consolidation, and retrieval. Specifically, we discuss how hippocampal activity in humans and engram formation and activation in rodents support the reproduction of detailed memory representations, whereas schema formation across species, mediated by the medial prefrontal cortex, facilitates reconstruction and generalization to guide behavior. Finally, we consider how species- and individual-level differences shape episodic memory representations. By integrating findings across species, we illustrate how the correspondence between neural and psychological representations enables multiple memory representations to balance stability and flexibility, ultimately driving adaptive behavior.

How do memories guide behaviour?

Multiple memory representations, from detailed to gist-like, let us flexibly reconstruct or reproduce past experiences to behave adaptively across species.

Now out in Physiological Reviews with Morris Moscovitch, Melanie Sekeres & @brianlevine.bsky.social!

Building compositional tasks with shared neural subspaces Nature - The brain can flexibly perform multiple tasks by compositionally combining task-relevant neural representations.

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

New discovery! Value-based decisions reorganize neural state space. Options are first encoded in orthogonal subspaces Then the selected option rotates into a "readout subspace".
Neural subspace reorganization reflects value-based decision making.
www.biorxiv.org/content/10.6...
#neuroscience

1/7 Can infants recognise the world around them? 👶🧠 As part of the FOUNDCOG project, we scanned 134 awake infants using fMRI. Published today in Nature Neuroscience, our research reveals 2-month-old infants already possess complex visual representations in VVC that align with DNNs.

High-dimensional structure underlying individual differences in naturalistic visual experience Han and Bonner reveal that individual visual experience arises from high-dimensional neural geometry distributed across multiple representational scales. By characterizing the full dimensional spectru...

Human visual cortex representations may be much higher-dimensional than earlier work suggested, but are these higher dimensions of cortical activity actually relevant to behavior? Our new paper tackles this by studying how different people experience the same movies. 🧵 www.cell.com/current-biol...

I’m excited to share our preprint ‘Phase similarity between similar objects indicates representational merging across retrieval training but not sleep.’ We use EEG to compare representational changes to memories across retrieval-mediated and sleep-based consolidation www.biorxiv.org/content/10.6...

How are memories consolidated during sleep?
Excited to share another preprint: hippocampal SWRs route memory content to the cortex via interregional co-reactivation of concept cells, optimized by slow-oscillation–spindle coupling. With the great @tschreiner.bsky.social @humansingleneuron.bsky.social

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.

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

Inference over hidden contexts shapes the geometry of conceptual knowledge for flexible behaviour Flexible decision-making in uncertain environments requires inferring the relevant context and focusing on behaviourally relevant information. We tested the hypothesis that the brain supports this pro...

We don’t learn the world as it is. We rapidly infer what matters, with belief and attention reciprocally shaping each other as neural geometry adapts.

Thanks to @stephanie-theves.bsky.social, @mikael-johansson.bsky.social, Peter Gärdenfors, @doellerlab.bsky.social.

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

Critically, inference stretches neural distances along relevant dimensions and compresses irrelevant ones right before a decision, predicts faster RTs, and this re-shaping precedes feedback-related frontal theta tracking model-derived PE.

The brain’s representational space flexes with inferred complexity.

Neural effective dimensionality scales up in 2D vs 1D, and is higher on correct vs incorrect trials. In 2D, the two attended features show up as near-orthogonal axes in a shared planar manifold plane.
6/8

Eyes tell the same story
Gaze selectively shifts toward task-relevant features, irrelevant features drop out. Gaze entropy decreases as beliefs stabilise, and negative prediction errors from the HSI model trigger broader sampling (exploration), while positive PEs tighten focus (exploitation).
5/8

A Hidden State Inference (HSI) model best explained choices and inferred contexts, beating Q-learning variants (standard, forgetting, counterfactual).

HSI captures something structurally different from incremental RL.
4/8

Participants adapted fast: first trial after a switch was at chance level, then rapid recovery. RTs drop and accuracy rises within context blocks - they used the structure to take decisions.
3/8

Serial reversal learning task with same cars, same feature space (3 dimensions), but the rule silently flips. Different dimensions matter in different trials. Sometimes one dim matters, sometimes two dims. You only find out via feedback, meaning participants had to infer the latent state.
2/8

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

Having worked at the Max Planck Institute for Human Development in Berlin, it is hard not to find this advice laughable coming from a group that seems to foster anything but open culture and flat hierarchies.

Simulated Complex Cells Contribute to Object Recognition Through Representational Untangling Abstract. The visual system performs a remarkable feat: it takes complex retinal activation patterns and decodes them for object recognition. This operation, termed “representational untangling,” orga...

Brains are designed for dimensionality reduction.
Simulated Complex Cells Contribute to Object Recognition Through Representational Untangling
doi.org/10.1162/NECO...
#neuroscience

🚨 🆕 Preprint 🚨

How does the brain represent natural images?

Using MEG + multivariate analysis, we disentangle contributions of retinotopy, spatial frequency, shape, and texture

Together, our results reveal how visual features jointly and dynamically support human object recognition.

link 👇

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

As always, interesting stuff by @sandervanbree.bsky.social

I'm happy to share my debut as first-author with the recent publication of our article in #JNeurosci:

www.jneurosci.org/content/earl...

Big thanks again to @tschreiner.bsky.social and the whole team who made this possible! 🧠🌬️

Investigating individual-specific topographic organization has traditionally been a resource-intensive and time-consuming process. But what if we could map visual cortex organization in thousands of brains? Here we offer the community with a toolbox that can do just that! tinyurl.com/deepretinotopy

New Correspondence with @davidpoeppel.bsky.social in Nat Rev Neurosci. www.nature.com/articles/s41...

Here, we critique a recent paper by Rosas et al. We argue that "Bottom-up" and "Top-down" neuroscience have various meanings in the literature.

PDF: rdcu.be/eSKYI

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...

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

Cognitive Maps in the Prefrontal Cortex The prefrontal cortex (PFC) is critical for our ability to rapidly and flexibly adapt our behavior in new environments based on our previous experience. Despite its importance, the neural substrates a...

1/ Excited to share that our symposium review covering cognitive mapping in the PFC just came out in the Journal of Neuroscience: www.jneurosci.org/content/45/4...

We went back to the drawing board to think about what information is available to the visual system upon which it could build scene representations.

The outcome: a self-supervised training objective based on active vision that beats the SOTA on NSD representational alignment. 👇

How prediction error drives memory updating: role of locus coeruleus–hippocampal interactions The brain constantly generates predictions based on one’s knowledge of the world, as captured in memory. When these predictions are in error, our know…

How prediction error drives memory updating: role of locus coeruleus–hippocampal interactions

Looks interesting, from Groves et al

#neuroskyence #psychscisky #cognition

Disrupted Sleep: Mechanisms Linking Sleep Deprivation, Neurovascular Dysfunction, and Metabolic Pathways at Leeds Beckett University on FindAPhD.com PhD Project - Disrupted Sleep: Mechanisms Linking Sleep Deprivation, Neurovascular Dysfunction, and Metabolic Pathways at Leeds Beckett University, listed on FindAPhD.com

Please repost! Fully funded four-year PhD studentship opportunity on sleep deprivation and neurovascular dysfunction on the BBSRC Yorkshire Bioscience Doctoral Training Partnership, including annual stipend, research costs and home tuition fees tinyurl.com/ms7v2pcx