How many bits of information can different synaptic learning rules store about spike trains? In new work I attempt to calculate this analytically and propose a potential first-principles account of BTSP: journals.aps.org/pre/abstract...

SFI is hiring a postdoctoral fellow to work with SFI Professor David Wolpert on the thermodynamic cost of distributed computation, from digital circuits to human brains. We are seeking a scholar with expertise in physics, computer science, or a related field. santafe.edu/about/jobs/p...

My department, Neurobiology and Biophysics at the University of Washington (nbio.uw.edu), is hiring a new tenure-track Assistant Professor, application deadline 09/30/26. It's a broad search — molecular to organismal, all of neuroscience/physiology/biophysics welcome. apply.interfolio.com/187735

Here you go arxiv.org/abs/1909.02603

Additive function approximation in the brain

Many biological learning systems such as the mushroom body, hippocampus, and cerebellum are built from sparsely connected networks of neurons. For a new understanding of such networks, we study the fu...

arxiv.org

Difficult decisions take time, but can we keep all accumulated evidence in mind long enough to make better choices? We find that working-memory limitations constrain decision-making, and these effects are modulated by dopamine. biorxiv.org/content/10.6... bioRxiv out with Cina Aghamohammadi et al.

Working memory limitations and dopamine modulation in probabilistic reasoning

Difficult decisions require gathering evidence over extended periods, placing demands on working memory. Yet, how working memory limitations affect decision-making remains largely unknown. We trained ...

biorxiv.org

Yale Neuroscience is hiring another computational neuroscience position this year! Please share with anyone who might be interested, and feel free to reach out if you have any questions about the position, or growing neuro-AI community at Yale/WTI!

Yale Neuroscience@yaleneuro.bsky.social · 2mo ago

The Department of Neuroscience at Yale is hiring faculty members. We have 2 searches: one general (deadline Oct 15), one focused on computational neuroscience (deadline Nov 30). Apply! apply.interfolio.com/190736 & apply.interfolio.com/190740

I am proud of this paper. Since it came out in 2022 it has received 0 citations (yes that's a zero). But multiple young scientists have found it useful! (from other labs, so they were not coerced...). Perhaps you will find it useful too? SOME TIPS FOR WRITING SCIENCE doi.org/10.1523/ENEU...

Some Tips for Writing Science

When preparing a scientific paper, we typically write with coauthors who have different backgrounds and styles, and we target readers who have little time and patience. To help both readers and writer...

doi.org

Are cells themselves a kind of thermodynamic computer? “To my physicist’s way of thinking, it would be fair to say that nature uses Langevin computers programmed by evolution,” said Stephen Whitelam, a statistical physicist.

Thermodynamic Computers Go With the (Energy) Flow | Quanta Magazine

Today’s computers need safeguards against random energy fluctuations. Thermodynamic computers would put those fluctuations to use.

quantamagazine.org

New preprint (well, very updated). 🤖🧠🧪 We find that an abstract model of neuromodulation lets spiking neural networks perform much better, particularly in challenging noisy environments, using less energy. Relevant to #neuroscience and #neuromorphic computing. 🧵👇 www.biorxiv.org/content/10.1...

Neuromodulation enhances the capability and efficiency of spiking neural networks

Spiking neurons underlie the brain’s extreme energy efficiency, and therefore have great potential in neuromorphic computing, although realising this efficiency in practice has proven challenging. We ...

biorxiv.org

Out today! Our (w/ @annaschapiro.bsky.social) review of the alignment between the C-HORSE model and the hippocampal structure learning literature. We find strong congruence with the model's key principles and propose several avenues for future investigation!

Evidence for complementary learning systems within the hippocampus

Abstract. Decades of research have established the hippocampus as central to episodic memory, but growing evidence suggests that it also contributes to str

royalsocietypublishing.org

📢 TA Applications Open 🇿🇦🧠 Are you an advanced PhD or post-doc in computational neuroscience? Apply to be a Teaching Assistant (TA) for the 10th #Imbizo in Noordhoek, Cape Town! ⏳ Applications close: 1 Sep 2026 (20:00 UTC) 🔗 Apply: imbizo.africa/ta-applicati...

Neural activity in mouse cortex forms rotating spiral waves. The architecture of individual axons matches the wave geometry, centered on somatosensory cortex. Beautiful new pape from our colleagues in the @steinmetzneuro.bsky.social lab. www.science.org/doi/10.1126/...

🚨🧠 Our paper is out! We introduce a simple computational model that generates macroscopic, long-timescale dynamics as seen in large-scale neural recordings. #neuroscience #dynamics @marius10p.bsky.social @zhong-lin.bsky.social @hhmijanelia.bsky.social Link: go.nature.com/4tRNjIu

Nature@nature.com · 5mo ago

Nature research paper: A critical initialization for biological neural networks go.nature.com/4tRNjIu

New preprint: "Linear equivalence of nonlinear recurrent neural networks." For large nonlinear (potentially chaotic) RNNs with random connectivity, the full N×N covariance matrix takes the same form as that of a ~linear~ network with the same couplings, driven by independent noise.

Linear equivalence of nonlinear recurrent neural networks

Large nonlinear recurrent neural networks with random couplings generate high-dimensional, potentially chaotic activity whose structure is of interest in neuroscience, machine learning, ecology, and o...

arxiv.org

Our latest publication grapples with how the brain could implement gradient descent by sending learning targets top-down, gating plasticity with dendritic inhibition, and updating synaptic weights with biologically observed learning rules like BTSP. www.cell.com/cell-reports...

Cellular and subcellular specialization enables biology-constrained deep learning

Galloni et al. introduce “dendritic target propagation”: a Dale’s law-compliant learning algorithm for cortical microcircuits with soma- and dendrite-targeting inhibition and realistic connectivity co...

cell.com

Aaron Milstein@neurosutras.bsky.social · last yr.

New #NeuroAI #compneurosky preprint! To better understand how target-directed learning works in the brain, we sought to engineer an artificial neural network capable of solving complex image classification tasks that comprises only experimentally-supported biological building blocks. (1/15)

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

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...

arxiv.org

Are you at #cosyne2026 and looking for a postdoc position? CATNIP = Neural Dynamics Lab is hiring! catniplab.github.io/postdoc-hiri...

The cortex generates invariant dynamic primitives; the cerebellum reconfigures them to drive distinct policies. Huge congrats to first author Martha Garcia-Garcia for leading this tour de force, and @somnirons.bsky.social & Michal Wojcik for a great collaboration! www.biorxiv.org/content/10.6...

At the Bernstein Conference 2024, Jeremie Lefebvre and I organized a workshop on the computational consequences of neural heterogeneity. Now, slightly more than a year later, we funneled the emerging discussions into a perspective piece: www.cell.com/neuron/fullt...

How heterogeneity shapes dynamics and computation in the brain

No two neurons are the same, yet models often treat neural populations as pools of identical and interchangeable elements. Here, Dahmen et al. highlight recent theoretical advances that reveal the imp...

cell.com

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

Building compositional tasks with shared neural subspaces

Nature - The brain can flexibly perform multiple tasks by compositionally combining task-relevant neural representations.

rdcu.be

New paper out at PNAS: www.pnas.org/doi/10.1073/... Revisiting the high-dimensional geometry of population responses in the visual cortex with @jpillowtime.bsky.social. The review took forever because a reviewer was doubtful our new estimator can infer eigenvalues beyond the rank of the data! (1/6)

We are very excited to announce that our new preprint with Saleh Esteki, @stefanofusi.bsky.social, and @roozbehkiani.bsky.social is now available on biorxiv! www.biorxiv.org/content/10.6.... We investigated how reward context is learned, represented, and updated to bias decisions. Thread 🧵👇! 1/13

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

New preprint from the lab! 🚀 We find that hippocampal OLM interneurons provide a circuit-level inhibitory feedback signal that dynamically controls when and where behavioral timescale synaptic plasticity can occur. Feedback welcome!

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · 10mo ago

Dendrite-targeting OLM interneurons regulate the formation of learning-related CA1 place cell representations https://www.biorxiv.org/content/10.64898/2025.12.21.695825v1

Rapid neocortical network modifications via dendritic plateau potential induced plasticity https://www.biorxiv.org/content/10.1101/2025.11.19.689338v1

Now in PRX: Theory linking connectivity structure to collective activity in nonlinear RNNs! For neuro fans: conn. structure can be invisible in single neurons but shape pop. activity For low-rank RNN fans: a theory of rank=O(N) For physics fans: fluctuations around DMFT saddle⇒dimension of activity

Connectivity Structure and Dynamics of Nonlinear Recurrent Neural Networks

The structure of brain connectivity predicts collective neural activity, with a small number of connectivity features determining activity dimensionality, linking circuit architecture to network-level...

journals.aps.org

Our latest project find shared representations while controlling for confounds is out www.biorxiv.org/content/10.1... Check @s-michelmann.bsky.social 's thread for the executive summary. Code in python and matlab: github.com/s-michelmann... — Now is play time 👨‍💻

🧠 Paper out! We investigated how hippocampal and cortical ripples support memory during movie watching. We found that: 🎬 Hippocampal ripples mark event boundaries 🧩 Cortical ripples predict later recall Ripples may help transform real-life experiences into lasting memories! rdcu.be/eui9l

Movie-watching evokes ripple-like activity within events and at event boundaries

Nature Communications - The neural processes involved in memory formation for realistic experiences remain poorly understood. Here, the authors found that ripple-like activity in the human...

rdcu.be

Excited to share this project specifying a research direction I think will be particularly fruitful for theory-driven cognitive science that aims to explain natural behavior! We're calling this direction "Naturalistic Computational Cognitive Science"