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When Collaboration Beats Ability: Mixed-Ability Teams Can Outperform High-Ability Teams Under Coordination Demands osf.io/preprints/ps...

doi.org/10.64898/202...

Dorsoventral hippocampus neural assemblies reactivate during sleep following an aversive experience - Nature Neuroscience Synchronization of sharp-wave ripples across the dorsoventral hippocampus during sleep supports coordinated reactivation that represents negative experiences more faithfully than positive ones.

doi.org/10.1038/s415...

Functional Ca2+-permeable AMPA receptors in hippocampal astrocytes mediate calcium signaling in vitro - Scientific Reports Glutamate is the main excitatory neurotransmitter in the brain, acting through ionotropic receptors such as AMPA receptors (AMPARs). While their neuronal role is well established, AMPAR function in astrocytes remains poorly understood, especially in the hippocampus. In this study, we investigated the expression and functional properties of astrocytic AMPARs, focusing on their capacity to mediate calcium signaling and inter-cellular communication. Using astrocyte primary cultures, we confirmed the expression of GluA1 and GluA2 subunits, along with detectable levels of GluA4. Calcium imaging revealed that pharmacological AMPAR stimulation elicited intracellular Ca²⁺ signals in a subset of astrocytes which were markedly potentiated when desensitization was impaired. Notably, some of these responses persisted without extracellular Na⁺, compatible with the presence of functional calcium-permeable AMPARs (CP-AMPARs) in hippocampal astrocytes. However, sodium was required for full amplification of the Ca²⁺ signals, suggesting a synergistic role of Na⁺ and Ca²⁺ influx. Pharmacological inhibition of GluA2-lacking AMPARs reduced the responses, supporting the coexistence of GluA2-lacking and GluA2-containing subtypes. Sniffer-calcium assays suggested that strong AMPAR stimulation can engage ATP-dependent signaling, facilitating calcium wave propagation. Altogether, our results reveal functional and heterogeneous AMPAR populations in hippocampal astrocytes. Further investigations will elucidate their physiological roles, localization, and contribution to neuroglial interactions under physiological and pathological conditions.

doi.org/10.1038/s415...

Entorhinal cortex represents task-relevant remote locations independently of CA1 - Nature Neuroscience Neurons in medial entorhinal cortex collectively represent discrete nonlocal positions during immobility. During this nonlocal coding, CA1 is uncoupled from entorhinal cortex. These representations ar...

doi.org/10.1038/s415...

Shor's algorithm is possible with as few as 10,000 reconfigurable atomic qubits Quantum computers have the potential to perform computational tasks beyond the reach of classical machines. A prominent example is Shor's algorithm for integer factorization and discrete logarithms, w...

arxiv.org/abs/2603.286...

Neuropeptide Y co-opts neuronal ensembles for memory lability and stability - Nature Neuroscience This study from Wei-Guang Li, Tian-Le Xu and colleagues shows that neuropeptide Y released by specific hippocampal inhibitory neurons can switch fear memories into extinction memories by acting on two...

doi.org/10.1038/s415...

doi.org/10.64898/202...

doi.org/10.1101/2023...

Resting on Their Laureates? Research Productivity Among Winners of the Nobel Prize in Physiology or Medicine Founded in 1920, the NBER is a private, non-profit, non-partisan organization dedicated to conducting economic research and to disseminating research findings among academics, public policy makers, an...

Research Productivity Among Winners of the Nobel Prize in Physiology or Medicine www.nber.org/papers/w31352

Scientific Publishing: Rethinking how research is reviewed and published Taking a radical new approach to the publication process resulted in eLife losing its impact factor, but authors, reviewers, editors and funders support the journal and its efforts to reform scientifi...

Scientific Publishing: Rethinking how research is reviewed and published doi.org/10.7554/eLif...

Inhibitory normalization of error signals improves learning in neural circuits Normalization is a critical operation in neural circuits. In the brain, there is evidence that normalization is implemented via inhibitory interneurons and allows neural populations to adjust to chang...

How do neural circuits in the brain implement normalization? 🧠

In our new paper, we show that just normalizing sensory input isn't enough. Crucially, we must also normalize the error signals! 🧵👇

Paper: arxiv.org/abs/2603.17676

Really stoked to see this project in (pre)print. On how to implement normalization-via-inhibition in ANNs, and what it might mean for inhibition in the brain. ⚖️

Great job @royeyono.bsky.social and the team 👏👏👏

Unsupervised pretraining in biological neural networks - Nature During visual learning, neural plasticity is driven by unsupervised learning in mice.

It’s amazing in a few ways!
doi.org/10.1038/s415...

Linking neural manifolds to circuit structure in recurrent networks Neural population activity can be described either by low-dimensional dynamics on neural manifolds or by single-neuron selectivities. Using a theoretical approach, Pezon et al. relate these two statis...

Linking neural manifolds to circuit structure in recurrent networks www.cell.com/neuron/fullt...

Cooperative thalamocortical circuit mechanism for sensory prediction errors - Nature Experiments in mice show that a cortico-thalamic circuit generates prediction-error signals in primary visual cortex that amplify visual input that deviates from animals’ expectations.

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

Are the place-cell representations of environments Euclidean even? I am not sure.

doi.org/10.64898/202...

doi.org/10.64898/202...

𝗗𝘆𝗻𝗮𝗺𝗶𝗰𝗮𝗹 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗮𝗻𝗱 𝗰𝗼𝗺𝗽𝘂𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆
Another mega paper that deserves close attention.
Lots of implications, including emergence and evolution
iopscience.iop.org/article/10.1...
#complexity

A neural network model of hippocampal contributions to category learning A neural network model of the hippocampus exhibits a division of labor across its two main pathways during category learning, with one pathway specializing in extracting systematic category information and another in encoding arbitrary details.

A neural network model of hippocampal contributions to category learning doi.org/10.7554/eLif...

Predictive sequence learning in the hippocampal formation Chen et al. simulated hippocampal circuits that learned to predict sequences of sensory inputs and validated the model with analysis of neural recordings. CA1 neurons in the model compute prediction e...

Predictive sequence learning in the hippocampal formation www.cell.com/neuron/fullt...

Insightful angle for mechanistic interpretability!
doi.org/10.48550/arX...

Check out our new work on motor learning across multiple brain regions!

Dopamine encodes deep network teaching signals for individual learning trajectories Longitudinal tracking of long-term learning behavior and striatal dopamine reveals that dopamine teaching signals shape individually diverse yet systematic learning trajectories, captured mathematical...

Dopamine encodes deep network teaching signals for individual learning trajectories www.cell.com/cell/fulltex...

On the first principles of gradient-based inference
doi.org/10.48550/arX...

What does it mean for a system to compute? What does it mean for a system to compute?, Wolpert, David H, Korbel, Jan

What does it mean for a system to compute?
doi.org/10.1088/2632...

Vectorized instructive signals in cortical dendrites - Nature Mice learning a neurofeedback brain–computer interface task show neuron-specific teaching signals in cortical dendrites, consistent with a vectorized solution for credit assignment in the brain.

Here we are. That is foundational paving ways for the future of the gradient descent rules in the brain! Huge Congrats Mark!
Amazing. doi.org/10.1038/s415...

I’m not entirely sure what’s in this, but it appears to make sense
doi.org/10.48550/arX...

Reasoning Models Don't Always Say What They Think Chain-of-thought (CoT) offers a potential boon for AI safety as it allows monitoring a model's CoT to try to understand its intentions and reasoning processes. However, the effectiveness of such monit...

Same topic, a little bit early reference, and from the Anthropic team.
arxiv.org/abs/2505.05410

Are Your Reasoning Models Reasoning or Guessing? A Mechanistic Analysis of Hierarchical Reasoning Models Hierarchical reasoning model (HRM) achieves extraordinary performance on various reasoning tasks, significantly outperforming large language model-based reasoners. To understand the strengths and pote...

While I’d rather take Dario Amodei’s warning as an attention-worthy message, hierarchical reasoning doesn’t seem to reason. The future might be more of a turmoil than a single-lane apocalypse

arxiv.org/abs/2601.10679