Machine Learning PhD Student @GeorgiaTech Systems Neural Engineering Lab (PI: @chethan) (https://xitter.cf/t.co/2sZ2U6m60O)
Atlanta, GA
Joined August 2023
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Modern neuroscientists routinely record the complex, goal-oriented, and time-varying activity of thousands of neurons. Can we find representations of neural activity that 1) are human-interpretable and 2) enable the generation of neural activity for unrecorded behavioral conditions? We present our recent work on Generating Neural Observations Conditioned on Codes with High Information (GNOCCHI) 🥔🍝 !!
By leveraging unsupervised, information-based diffusion models, GNOCCHI can discover interpretable latent spaces from neural data and generate high-quality neural activity for specific conditions outside of the set of available neural recordings!
Jonathan McCart retweeted
Excited to announce the 2nd Foundation Models for the Brain and Body Workshop at #NeurIPS2026 in Sydney, Australia! 🧠🤖
We invite short papers & demos on AI for neural, physiological, or behavioral data.
📅 Papers: Sep 4
💡 Demos: Sep 19
Learn more 👉 brainbodyfm-workshop.github.…
On biological neural data, GNOCCHI-inferred codes can predict target position for held-out trials better than LFADS, suggesting that the representations learned by GNOCCHI can generalize to unseen conditions better than previous models!
For more information, including additional comparisons to LFADS, check out the pre-print at the link below! Major thanks to all the co-authors who helped make this happen! @arsedle, @chris_versteeg, @DomenickMifsud, Mattia Rigotti-Thompson and @chethan !
arxiv.org/abs/2407.21195
Jonathan McCart retweeted
Cosyne Workshop Alert! On Tuesday March 5th, @chethan and I are proud to bring you:
Understanding Neural Computation using Task-trained and Data-trained Networks.
youtu.be/bJ0stLORdgQ
Jonathan McCart retweeted
Are you a postbac interested in neural engineering / BCIs? 🧠🤖🗣️
Come join our team!! Work directly with our amazing BCI participants.
Great exposure for prospective grad/med school applicants! snel.ai/positions
Jonathan McCart retweeted
Stop by NeurReps 2023 tomorrow morning to hear about how ODIN can help you accurately infer neural latent dynamics from neural recordings! Hint: combine low-dimensional dynamical models with injective, nonlinear readouts!
If you are interested in estimating neural dynamics from population recordings, come to our poster Tuesday afternoon to hear more about how injectivity can improve the interpretability of your models! #SfN23
PSTR445.20 / XX40
Jonathan McCart retweeted
Ever wondered whether the dynamics learned by LFADS-like models could help us understand neural computation? @chethan,@arsedle, @JonathanDMcCart, and I developed ODIN to robustly recover latent dynamical features through the power of injectivity! 📜 1/ arxiv.org/abs/2309.064021/
