Computational neuroscientist.
Maybe at @[email protected]
Also @memming.bsky.social
Group leader @Neuro_CF
(formerly Associate professor @SBUNeurobiology)
A new preprint that revives the theory of continous attractors that may be surprising to you! Despite their mathematical fragility, we show that they are functionally *robust*. No wonder we see approximate continuous attractors in neuroscience often. https://t.co/H37rUSpUoE
🧠🗣️ Ever stumbled over your words, realizing only after speaking them outloud? Your brain might not have followed the plan. New preprint on the neural ensemble organization of speech motor plans and what it means for speech BCIs https://t.co/f7zpqNDKSc 1/10
I've been a happy customer of @TheBrainTech product since 2015 or before, using the free tier which had basic cloud sync function. I finally upgraded to the PRO version and paid $200+ and I can no longer use the basic sync function... am I doing something wrong?
If you are at #cosyne2026 come see poster [2-152] Dynamical archetype analysis: Autonomous computation. Ábel Ságodi is presenting how you can compare dynamical systems at behaviorally relevant timescale while keeping the interpretability!
Happy to share that our new paper is out in Nature Communications with Zoe Ashwood, @IntlBrainLab, and @jpillowtime!
We study how animals switch between internal decision-making states in non-stationary environments using a GLM-HMM framework.
https://t.co/gZoqFwgcZx
Joint junior faculty position in Computational Neuroscience, split between Ctr for Computational Neuroscience at @FlatironInst and the CUNY Graduate Center @GC_CUNY. Application deadline: 16 Jan 2026!
https://t.co/TdmduNJ7uG
How can I accelerate breakdown of caffeine in my body? I will need to increase CYP1A2 (P450) activity (without smoking). Vigorous exercise over 30 days was shown to increase it up to 70%? https://t.co/cbAvrcMwMw
Gonçalo M. Tavares's poetry book, "Mr. Swedenborg and the Geometrical Investigations" is *not* available on https://t.co/avBjIAbcll... ISBN: 9896419981
https://t.co/8IrTLO8RJI
The research labs you can join through INDP range from systems neuroscience, computational neuroscience and clinical neuroscience, to neocybernetics, neuroethology, and natural intelligence.
To learn more about the culture and value, check out: https://t.co/DRgY0duCjz
Applications are now open for the International Neuroscience Doctoral Programme (INDP) at Champalimaud Foundation, Lisbon, Portugal.
Deadline for application: Jan 31, 2026
https://t.co/OBheiSE8zH
The programme includes an initial year of classes + three lab rotations.
We seek motivated applicants from all areas of neuroscience, as well as physics, math, computer science, electrical/biomedical engineering, and related quantitative backgrounds. English is the working language. It's an American-style graduate program in Europe.
One advantage of monosemantic, sharply-tuned, grandmother-cell, axis-aligned, neuron-centric representation as opposed to polysemantic, mixed-selective, oblique population code is that it can benefit from evolution. Genes are good at operating at the cell level. #neuroscience
Theoretical Insights on Training Instability in Deep Learning TUTORIAL
https://t.co/HbvPvVWuIt
gradient flow-like regime is slow and can overfit while large (but not too large) step size can trasiently go far, converge faster, and find better solutions #optimization#NeurIPS2025
Some of my favorites from #NeurIPS2025
more neg max Lyapunov exp => faster parallelized RNN convergence
Gonzalez, X., Kozachkov, L., Zoltowski, D. M., Clarkson, K. L., & Linderman, S. Predictability Enables Parallelization of Nonlinear State Space Models. https://t.co/T5rUSHTr7s
score/flow matching diffusion models only starts memorizing when trained for long enough
Bonnaire, T., Urfin, R., Biroli, G., & Mezard, M. (2025). Why Diffusion Models Don’t Memorize: The Role of Implicit Dynamical Regularization in Training. https://t.co/CXmR8LyEKD