Micah G. Allen societaslinguistica.eu
Computational neuroscience posts on BlueSky! Add #compneuro, #compneurosky, 🧠🤖, or 🧠💻 to your post for it to appear in this feed. Don't be an jerk. Posts must be about comp. neuroscience. Run by @mgallen.bsky.social
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This is a great thread, and I think it hits on one of the biggest challenges in neuroscience that I hope NeuroAI can impact.
Until we can rigorously define what computations are occurring in the brain, we can't make any real progress in our functional understanding. We need constraints. 🧠🤖🧪
Sam Gershman@gershbrain.bsky.social
I once saw a (very interesting) talk about sleep in which the speaker started by saying that we don't really know how to define sleep, and then proceeded to operationalize sleep in flies as basically periods when they are still for a long time. This got me thinking...
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🚨 #SLE2026 Workshop alert! 🚨
How do Large Language Models reshape linguistics? 🧠🤖
Join the debate about LLMs' impact on linguistic theory, methods and human language! Osnabrück 26-29 August 2026.
#LLM #linguistics
Full text of our workshop proposal:
societaslinguistica.eu/sl….
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Scientists at @ucsc have built an automated platform to grow and monitor brain organoids (brain tissue in a dish) 24/7 🧠🤖. It captures neural activity missed by manual methods—boosting reproducibility & paving the way for breakthroughs in brain research.
www.sciencedirect.com/sci….
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Thrilled to see this work accepted at NeurIPS!
Kudos to @hafezghm.bsky.social for the heroic effort in demonstrating the efficacy of seq-JEPA in representation learning from multiple angles.
#MLSky 🧠🤖
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🧠🤖Affective states as clinical signals: AI models for decision-making and symptoms
This month’s Editor’s Pick examines the role of affective states in computational psychiatry—a field that uses mathematical and AI-based models to link behavior, brain function, and mental health.
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Do you trust AI? Researchers used #fNIRS to measure trust directly from brain activity 🧠🤖.
In 18 participants, prefrontal responses predicted trust in an AI teammate.
ML models achieved F1 = 0.77 / AUC = 0.81, outperforming behavioral measures.
📖 doi.org/10.63562/257...
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Equation: GenAI×RobotVision → fewer misses; QC↑ 🧠🤖
Few-shot inspection; normalize views; explain flags; verify drift - GLCND.IO
Explore → glcnd.io/abb-and-landinga…
#Robotics #ComputerVision
glcnd.io
ABB and LandingAI Empower Robotic Vision with Generative AI - GLCND.IO
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