Sharing a new bite-sized paper:
Predictive coding network == cellular sheaf
We put linear predictive coding networks into the language of sheaf theory, and use cohomology/Hodge decompositions to understand when recurrent PCNs actually learn.
In some sense, the ubiquity of the Einstein summation convention in mathematics is a testament to the fact that vast swathes of differential and algebraic geometry, functional analysis, analysis of PDEs, etc. can be usefully reformulated in terms of zillions of dot products.
The unbearable slowness of being: Humans still clock in at just 10 bits/s. Even after peer review :) Share link for Neuron: https://t.co/P4vZlpwZWG, ArXiv: https://t.co/HdzKqnnI3d
I'm excited to share our #NeurIPS2024 paper, "Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems" 🧠✨ We introduce the gpSLDS, a new model for interpretable analysis of latent neural dynamics! 🧵 1/10
I'm excited to share our #NeurIPS2024 paper with
@jsoldadomagrane@SmithLabNeuro@YuLikeNeuro!
We develop a new brain stimulation framework (MiSO) to drive neural population activity toward specified states.
Paper: https://t.co/1VHPSHDu8d
Poster Session 4 East, Dec 12 16:30
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1/10 Very excited to announce that my thesis project is now a preprint! We present the first detailed study of mental imagery in human ventral temporal cortex, bringing together the interests of @doristsao and @UeliRutishauser. https://t.co/LBukzKqMOA
How much info in population activity on latents? I'm presenting at @eusipco2024
Jeon, H., & Park, I. M. Quantifying Signal-to-Noise Ratio in Neural Latent Trajectories via Fisher Information. European Signal Processing Conference https://t.co/gvaFJt5z2g
#compneuro#tweeprint
New preprint post! We show that motor commands in the superior colliculus shift the internal representation of heading during REM sleep despite the immobility of sleeping mice. Thus, the brain simulates actions and their consequences during REM sleep.🧵1/7
https://t.co/KS6GX8smYx
🚨 New paper alert!
Have you ever suspected that spikes, Dale's law, and E/I balance might be more than just biological constraints, but rather fundamental to how brains compute? Check out my latest work with Christian Machens @Neuro_CF: https://t.co/5lZ8TlDmIE
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I'd like suggestions on the best "pure theory" paper you've read. Clearest explained, best written, etc, one caveat is there can be NO data. Just theory