1/13 New paper with @wimdeneys.bsky.social accepted at @cognitionjournal.bsky.social 🥳 Is creativity intuitive? 👩🎨 A 🧵👇
Hugo Ninou
@hugoninou.bsky.social
I am a PhD student working at the intersection of neuroscience and machine learning. My work focuses on learning dynamics in biologically plausible neural networks. #NeuroAI
1/10 🚨 New preprint: Using Large Language Models to Estimate Belief Strength in Reasoning 🚨 When asked: "There are 995 politicians and 5 nurses. Person 'L' is kind. Is Person 'L' more likely to be a politician or a nurse?", most people will answer "nurse", neglecting the base-rate info. A 🧵👇
Excited to present my latest work, “Curl Descent: Non-Gradient Learning Dynamics with Sign-Diverse Plasticity,” this Friday at 11:00 AM at NeurIPS 2025! Come by spotlight poster #3014 🎉 I’d love to discuss it with you: neurips.cc/virtual/2025...
NeurIPS Poster Curl Descent : Non-Gradient Learning Dynamics with Sign-Diverse PlasticityNeurIPS 2025
neurips.cc
1/6 New preprint 🚀 How does the cortex learn to represent things and how they move without reconstructing sensory stimuli? We developed a circuit-centric recurrent predictive learning (RPL) model based on JEPAs. 🔗 doi.org/10.1101/2025... Led by @atenagm.bsky.social @mshalvagal.bsky.social
🚨New spotlight paper at Neurips 2025🚨 We show that in sign-diverse networks, inherent non-gradient “curl” terms arise, and can, depending on network architecture, destabilize gradient-descent solutions or paradoxically accelerate learning beyond pure gradient flow. 🧵⬇️ www.arxiv.org/abs/2510.02765
Curl Descent: Non-Gradient Learning Dynamics with Sign-Diverse Plasticity
Gradient-based algorithms are a cornerstone of artificial neural network training, yet it remains unclear whether biological neural networks use similar gradient-based strategies during learning. Expe...
arxiv.org
Big week for astrocyte research: 3 new Science papers link astrocytes to behavior. We're excited to add to the momentum with our new PNAS paper: a theory, grounded in biology, proposing astrocytes as key players in memory storage and recall. w/ JJ Slotine and @krotov.bsky.social (1/6)
1/6 Why does the brain maintain such precise excitatory-inhibitory balance? Our new preprint explores a provocative idea: Small, targeted deviations from this balance may serve a purpose: to encode local error signals for learning. www.biorxiv.org/content/10.1... led by @jrbch.bsky.social
(1/6) Excited to share a new preprint from our lab! Can large, deep nonlinear neural networks trained with indirect, low-dimensional error signals compete with full-fledged backpropagation? Tl;dr: Yes! arxiv.org/abs/2502.20580.
Training Large Neural Networks With Low-Dimensional Error Feedback
Training deep neural networks typically relies on backpropagating high dimensional error signals a computationally intensive process with little evidence supporting its implementation in the brain. Ho...
arxiv.org
🚨 Paper Alert! 🚨 1/n Thrilled to share our latest research, now published in Nature Communications! 🎉 This study dives deep into how the cerebellum shapes cortical preparatory activity during motor adaptation. www.nature.com/articles/s41... #neuroskyence #motorcontrol #cerebellum #motoradaptation
Cerebellar output shapes cortical preparatory activity during motor adaptation - Nature Communications
Functional role of the cerebellum in motor adaptation is not fully understood. The authors show that cerebellar signals act as low-dimensional feedback which constrains the structure of the preparator...
nature.com
Created a starter pack of neuroscience in/from Paris. Let me know if you want to be added (the 'from' can include those not in Paris anymore) or just tap in if you want to know what we're talking about! Regardless, please re-tweet! go.bsky.app/3Zs9w5w
For the Blueskyers interested in #NeuroAI 🧠🤖, I created a starter pack! Please comment on this if you are not on the list and working in this field 🙂 go.bsky.app/CscFTAr