Dimitra Maoutsa

Interested in dopaminergic learning, interaction of appetitive and aversive learning systems, & history-dependent modulation of learning? Come by my #cosyne2026 poster Thursday [1-096]: Reinforcement learning with distributed representations of prediction error and value.
#compneurosky #neuroskyence

Very happy to share our review on Reinforcement Learning vs Statistical Learning, with @ambrafer.bsky.social and @predictivebrain.bsky.social:

www.sciencedirect.com/science/arti...

A nice summary:
www.sainsburywellcome.org/blog/two-eng...

Is spatial navigation innate 🧠? Using #NeuroPixels we show that the #torus 🍩 underlying the #GridCell map exists already on day 10 in rats — before pups open eyes and ears and before they start upright walking. 🧵1:4
👇
www.biorxiv.org/content/10.6...

2/7 Using large-scale #Neuropixels recordings in rat pups (P8-P19), we recorded up to ~1000 simultaneous MEC-PaS units. We found toroidal manifolds in the medial entorhinal cortex (#MEC) as early as postnatal day 10 (P10), preceding eye/ear opening and active exploration🍩

1/7 🧠 My journey into development begins with this work and question: how does the brain's spatial navigation system develop? We found that the neural networks for spatial navigation (tori and rings) are preconfigured and only later anchor gradually to the world with experience! 🧵

Come check out our poster at Cosyne 2026, on Thursday! Plasticity vs dynamics, RNN with online learning rule, inference based on structure and many other ideas!

BioRiv paper:
www.biorxiv.org/content/10.6...

Hippocampus a ‘general-purpose statistical learning machine’ New cross-species findings may help settle a long-standing debate about whether the hippocampus is required for passively learning information.

Whether the hippocampus is involved in unrewarded learning has been a controversial question. A new preprint finds that it may be critical for passively learning information.

By @natmesanash.bsky.social

#neuroskyence

www.thetransmitter.org/memory/hippo...

Feedback control of random networks as a model of flexible motor cortical dynamics across tasks Kalidindi and Crevecoeur develop a computational framework linking feedback-controlled networks to limb dynamics. They demonstrate that optimal control of fixed network reproduces key motor cortical d...

Nice work, congratulations! In a recent model we found that similar neural dynamics may be due to similar task structure independent of network connectivity (supp. Figure). Could a simpler explanation be that all animals experienced essentially the same task structure?
www.cell.com/cell-reports...

To assess conserved neural computations, we tested the similarity of neural dynamics with Dynamical Similarity Analysis, an awesome technique for comparing the “rules” of two dynamical systems (arxiv.org/abs/2306.10168). Low dynamical distance, here, implies similar computations. 6/18

Interested in cell type diversity, the cortical operating regime, and how recurrent connections shape the integration of feedforward and feedback inputs during context-dependent processing? Come check out my poster [1-038] at #Cosyne2026.

Link: doi.org/10.64898/2026.02.06.704473

1-031, Poster session 1 (Thu, Mar. 12, 20:30): @maxschwabe.bsky.social (a Cosyne presenter awardee 🎉, a MASTER student) will present how decomposing neural dynamics to intrinsic and input-driven modes can tell us how naturalistic decision computations are realized in the RNNs.

Check out our latest research drop! We show BLA dopamine signaling encodes the emotional weight of sensory transitions, but not the associative strength or value of stimuli. These signals dynamically rescale when the learning context changes: "this matters most!" www.biorxiv.org/content/10.1...

InputDSA: Demixing then comparing recurrent and externally driven dynamics in complex systems - Kempner Institute We explored how to measure the similarity between two complex systems when they are driven by external inputs, like biological neural circuits or reinforcement learning agents. Our novel method, calle...

NEW from the #KempnerInstitute: InputDSA, a tool to separate intrinsic dynamics from input-driven effects—enabling accurate, efficient comparisons of complex systems with external inputs.

Read the #DeeperLearning blog post by @annhuang42.bsky.social & @kanakarajanphd.bsky.social: bit.ly/4bkrvy9

Cerebellar climbing fibers impact experience-dependent plasticity in the mouse primary somatosensory cortex Optogenetic climbing fiber activation regulates experience-dependent plasticity in the primary somatosensory cortex of mice, suggesting a role of the olivo-cerebellum in instructive signaling across b...

Quite impressed with the results reported here, a cerebellar learning signal affects neocortex plasticity. In the context of credit assignment, this suggest a cross-system coordination of plasticity: elifesciences.org/articles/109...

Conflicting adaptations in an inhibitory feedback circuit Abstract figure legend We studied activity-dependent adaptation in the fruit fly Drosophila’s memory centre, the mushroom body. Here, excitatory Kenyon cells (KCs) receive feedback inhibition from th...

Check out our latest paper - In neural networks with inhibitory feedback, local homeostatic adaptation can conflict with adaptation at the network level doi.org/10.1113/JP29...

Nepotism has made Iran weak.

by Jared Kushner and RFK Jr.

Science thrives when diverse voices are heard.
This #InternationalWomensDay, we celebrate women everywhere - including women #neuroscientists who mentor, inspire & push the boundaries of discovery 🌟

Happy International Women’s Day from IBRO!

I’ll be presenting my work at #COSYNE2026. Stop by our poster to come learn about how the geometry of neural population activity shapes communication between brain areas during learned behavior 🐦‍⬛🧠🎶

Excited to give a talk at #Cosyne2026 about my PhD work!

We show that RNNs trained on visual search converge on brain-like solutions, producing primate-like behavior and neural representations. Happy to chat if you're at Cosyne!

📅 March 15, 2026
📍 Lisbon, Portugal
www.biorxiv.org/content/10.1...

Publisher demands $500 from impersonated author to retract paper Last year, we wrote about a Walsh Medical Media journal that refused to withdraw an author’s paper unless he paid a fee — even though he didn’t write or submit the article. For one reader, some details of that story were familiar. Laertis Ikonomou, an associate professor at the University of Buffalo in New York, … Continue reading Publisher demands $500 from impersonated author to retract paper

Lol. This is academic publishing taken to its logical end.

https://retractionwatch.com/2026/03/05/publisher-demands-500-from-impersonated-author-to-retract-paper/

Task learning increases information redundancy of neural responses in macaque visual cortex How does the brain optimize sensory information for decision-making in new tasks? One hypothesis suggests that learning reduces redundancy in neural representations to improve efficiency, whereas anot...

RIP redundancy reduction?

Beautiful work by Liu & colleagues showing that neural redundancy increases with learning, as predicted by a Bayesian model:
www.science.org/doi/10.1126/...

The most sensitive inputs to cutaneous representing regions of primary somatosensory cortex do not change with behavioral training - PubMed Learning a sensory detection task leads to an increased primary sensory cortex response to the detected stimulus, while learning a sensory discrimination task additionally leads to a decreased sensory cortex response to the distractor stimulus. Neural responses are scaled up, and down, in strength, …

Some people have written about how these two ideas may not be mutually exclusive.

pubmed.ncbi.nlm.nih.gov/26634900/

As a result, we suspect the same neurons can exhibit different levels of stability to different stimuli based on network connectivity (as opposed to stimulus complexity/dimensionality). Just a hunch at this point, but seems plausible enough. More in this paper: www.nature.com/articles/s41...

How are neural manifolds and single-neuron response properties related to circuit structure?

How degenerate are these relationships?

Theory and a plethora of examples can be found in the following paper, out today in Neuron 🌟

It was a privilege to co-supervise first author @lpezon.bsky.social!

3. We find that the circuit structure
– can impose symmetries on the network's low-dim. dynamics
– constrains the topology of the set of all single-neuron responses.
From the second point, we pinpoint topological features of neural activity relevant for comparing it with models.

Linking neural manifolds to circuit structure in recurrent networks Dimensionality reduction methods are widely used in neuroscience to investigate two complementary aspects of neural activity: the distribution of sing…

Excited to share our new paper to be published in Neuron!

With Valentin Schmutz @bio-emergent.bsky.social and Wulfram Gerstner @gerstnerlab.bsky.social, we explore how circuit structure in RNNs shapes network computation and single-neuron responses.
www.sciencedirect.com/science/arti...

Orbitofrontal circuits for context-gated reward predictions https://www.biorxiv.org/content/10.64898/2026.03.05.709962v1

Functional reorganization of motor cortex connectivity during learning https://www.biorxiv.org/content/10.64898/2026.03.03.709199v1

it's out!

@hazimi.bsky.social and i explore how higher order representations of *one's own first-order representational uncertainty* -- not representations OF noisiness in the world -- can be studied, including how they are constructed in the first place.

philosophymindscience.org/index.php/ph...