FieteGroup
142 posts
@FieteGroup
Fiete group @MIT, theoretical and computational neuroscience. Run by the group. Follows and retweets are not an endorsement.
🚨New Preprint! Wondered how grid cells form multiple discrete modules? Interested in continuous attractors and modularity? With @FieteGroup, we discover + generalize a physical mechanism for forming modules from smoothly varying parameters in a dynamical system!👇(1/15)
How does one brain circuit encode memories of both places and events? 🧠 The answer is out in Nature today! (proud to have lead this work as a Co-First author @FieteGroup ) 🔗 nature.com/articles/s4158… Talk: youtube.com/watch?v=P4kHqk… This work extends MESH: proceedings.mlr.press/v162/sharma22b
Finally a tweeprint on our recent preprint presenting Vector-HaSH ! Vector-HaSH extends MESH to unify two important and seemingly independent roles of hippocampus: Spatial Mapping and Episodic Memory ! Brief talk: youtube.com/watch?v=P4kHqk… Preprint: biorxiv.org/content/10.110… 1/n
@doristsao @FieteGroup +1 to an amazing conceptual breakthrough in theoretical neuroscience that I think did not depend on big data or fancy technologies. What we can say is that BRAIN technologies will make the theory testable in a much more conclusive way than was ever possible.
Btw, I don't know if @FieteGroup is funded by BRAIN, but their recent work understanding grid cell-place cell dynamics as a general mechanism for episodic memory that factorizes problem of building attractors from problem of assigning content to them, is such a beautiful and creative synthesis of a large amount of observational data leading to an entirely new conceptual insight. The experimental work underpinning it goes back to John O' Keefe 1976.
This work from @FieteGroup looks pretty cool: biorxiv.org/content/10.110… Showing how structure in the sensory cortex (hierarchy, topography, etc.) can emerge from self-organizing dynamics and spontaneous activity on a cortical sheet. Looking forward to reading this one.
Mechanistic interpretability is not only for ML or LLM, but is even more promising for Science! A few months ago, we proposed a brain-inspired method (BIMT) for NN interpretability; Now we're happy to see that it can give something back to neuroscience - Growing brains in RNNs!
I am excited to announce Associative Memory & Hopfield Networks Workshop @NeurIPSConf 2023! We have a stellar lineup of invited speakers. The call for contributed papers is now open. See you in New Orleans! Website: amhn.vizhub.ai Submission: openreview.net/group?id=NeurI…
