Aitor Morales-Gregorio

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Aitor Morales-Gregorio

Aitor Morales-Gregorio

@AitorMoraGre

Computational Neuroscientist @CharlesUniPRG; previously @fz_juelich; Catching up on graphic design; Electrical engineer vibes ⚡; he/him 🏳️‍🌈

Aquisgrán, Alemania Katılım Eylül 2019
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Aitor Morales-Gregorio
Aitor Morales-Gregorio@AitorMoraGre·
I need to share this cute animation I made to showcase neurons might sometimes work together to encode/represent information in a higher dimensional state-space :) @matplotlib #DataViz #SciArt
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Aleksandr Kovalev
Aleksandr Kovalev@koval_alvi·
I'm at AAAI-26 in Singapore! If you're around - let's meet up! On January 27th, I'll be presenting a poster at the NeuroAI Workshop: "Masked Autoencoders Learn Perception-Relevant Representations from Resting State Neural Data"
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Biomedical Neuroengineering
Biomedical Neuroengineering@NeuroEngin_UMH·
Excited to share that our research has been covered by @elpais_espana A study led by Eduardo Fernández (@IB_UMH) demonstrates that direct stimulation of the visual cortex can enable visual perception in a patient blind due to optic nerve injury. 📰elpais.com/ciencia/2026-0…
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Crémieux
Crémieux@cremieuxrecueil·
Apparently some researchers thought it was significant that early high performance and later high performance were negatively correlated They didn't realize they were conditioning on a collider Nor did the editors at Science, who published their claims anyway Just incredible
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H.SHIMAZAKI
H.SHIMAZAKI@h_shimazaki·
🚀 論文発表です：Nature Communications に掲載 Explosive neural networks via higher-order interactions in curved statistical manifolds Aguilera, Morales, Rosas, Shimazaki 🔗 nature.com/articles/s4146… この研究では「曲がった空間上のニューラルネットワーク」 を提案しています： • 自己調節アニーリングにより記憶想起を爆発的加速 • 多安定性を伴う爆発的な相転移を実現 • 曲率制御により記憶容量やロバスト性を向上 🧠 統計多様体の変形に基づくこのモデルは，高次相互作用を自然に実装し，記憶ダイナミクスの新たな理論を提示します． 🔎 内容を簡単に把握したい方は： NotebookLMによる音声解説 ➡️ [日本語] notebooklm.google.com/notebook/a1e3b… 日本語プレスリリース ➡️ hokudai.ac.jp/news/pdf/25072…
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PRX Life
PRX Life@PRX_Life·
Scientists developed a measure that captures and compares the 2D structure of real, arbitrary matrices, demonstrating how it can robustly assess similarities and differences in synthetic network connectivity data and experimental data of brain activity. go.aps.org/42HyMF2
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PRX Life
PRX Life@PRX_Life·
Singular angle similarity measures the similarity of real, arbitrary matrices accounting for their 2D structure, outperforming standard methods in analyzing synthetic networks and neural activity patterns. Read the paper: go.aps.org/42HyMF2
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Javier Blas
Javier Blas@JavierBlas·
Before the outage hit, Spain was running its grid with very little dispatchable spinning generation, and therefore no much inertia. Solar PV/thermal + wind: ~78% Nuclear: 11.5% Co-generation: 5% Gas-fired: ~3% (less than 1GW) Snapshot at 12.30pm local time (outage was 12.35pm)
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Aitor Morales-Gregorio
Aitor Morales-Gregorio@AitorMoraGre·
I got inspired by this and managed to reproduce the art style with my own EEG signals 😄🧠⚡️
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Brad Caldwell@Caldwbr

Still amazed at how qualitatively different the response to music is at O2 (visual cortex) vs Fz (upper central prefrontal), here left vs right, listening to same song. We're talking time-frequency plot (SAM spectral amplitude modulation). Top is current moment, left is 3 Hz, right is 40 Hz, depth/upperRight is amplitude. Most time-frequency plus use color intensity for amplitude which makes it hard to see variations. My idea of using the third dimension to plot amplitude is revealing amazing details and correlations with music/speech.

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Brad Caldwell
Brad Caldwell@Caldwbr·
Still amazed at how qualitatively different the response to music is at O2 (visual cortex) vs Fz (upper central prefrontal), here left vs right, listening to same song. We're talking time-frequency plot (SAM spectral amplitude modulation). Top is current moment, left is 3 Hz, right is 40 Hz, depth/upperRight is amplitude. Most time-frequency plus use color intensity for amplitude which makes it hard to see variations. My idea of using the third dimension to plot amplitude is revealing amazing details and correlations with music/speech.
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Mo Bashiri
Mo Bashiri@neuralbash·
🧠 Meet LAMINR: Where neurons meet their match—finding common patterns that keep them excited 🔥💘 LAMINR learns & aligns invariance manifolds of sensory neurons to reveal shared properties. 🌟 #ICLR2025 Oral 📝 Paper: shorturl.at/08968 💻 Code: github.com/sinzlab/laminr
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Luca Baroni
Luca Baroni@LuchinoBaroni·
So excited to share our work got an oral at ICLR! Huge thanks to @neuralbash—your vision and drive made this possible; collaborating with you as co-first authors has been truly amazing. Also deeply grateful to @AntolikLab & @sinzlab for their invaluable support and guidance!🚀
Mo Bashiri@neuralbash

🧠 Meet LAMINR: Where neurons meet their match—finding common patterns that keep them excited 🔥💘 LAMINR learns & aligns invariance manifolds of sensory neurons to reveal shared properties. 🌟 #ICLR2025 Oral 📝 Paper: shorturl.at/08968 💻 Code: github.com/sinzlab/laminr

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