🦓CEBRA @cebraAI
🦓 Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables | pip install cebra cebra.ai Dev by @mwmathislab Joined September 2021-
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Quite thrilled that our (@stes_io & I) US patent on #cebra for use to generate time-series embeddings was granted! patents.google.com/patent/US12499…
🦓 Self-supervised multimodal ML is promising the next AI breakthrough - in our new work published in @Nature, we debut @cebraAI: for self-supervised hypothesis- and discovery-driven science. 📝 doi.org/10.1038/s41586… 💻github.com/AdaptiveMotorC… 🦓 cebra.ai 🧵⬇️
Ready to start with #CEBRA for your behavioral clustering, neural data, or joint-modeling? Check out our new demo notebook to help you learn the best practices and how to develop models! cebra.ai/docs/demo_note… 🌈🦓 #ML4Science
We have a new release up! Check out 0.5.0rc1!! 🔥 Important maintenance updates to keep up with dependencies, some nee features, and preparing for much more coming in the next weeks 👀… github.com/AdaptiveMotorC… #cebra @mwmathislab
Exciting! There is a new demo notebook for how to use #CEBRA on @AllenInstitute OpenScope project data! 🎉 contributed by @LecoqJerome, now live at cebra.ai/docs/demos.html #opensourcedata 🦓🫶 #machinelearning4neuro
In fact, this is what this very cool preprint does, cross subject decoding using CEBRA! Mind blowing decoding across even held out cohorts of patients 🤯
First, we developed and prospectively validated plug & play movement #decoders combining #connectomics with contrastive learning in @cebraAI for #ECoG signals. The video shows decoding in a prospective validation of a model that has never seen #braindata from the patient before.
Population dynamics and deep-learning analyses (@cebraAI @TrackingActions) of anterior insula single-unit recordings uncover distinct coding patterns of anxiety-provoking and safe environments, as well as tastants of positive and negative valence.
🥳 check out the #DeepLabCut + #CEBRA work for behavioral analysis from @shaokaiyeah et al @NatureComms nature.com/articles/s4146… ⬇️
#SfN24 update: sadly, we are not there in person, but we love to see a lot of #DeepLabCut powered science is 🥳 and we are happy to retweet it! 💕 (tag us!) 👀 But, here is what we would present 🥰🔥 DeepLabCut 3.0 release candidate is up!🔥 pip install deeplabcut==3.0.0rc5
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I have been reviewing the CEBRA paper in depth. What really strikes me is the multi-sessions/animal embedding. I feel like this paper is only scratching the surface of what could be done there. For starter, we could embed across species or even between models and experiments.
@saleh1414911 @NatureComms People can/do: science.org/content/articl…
🚨Excitingly, this new paper in @NatureComms shows #CEBRA for behavioral analysis! Using SuperAnimal model for pose, we use 🦓 to do behavioral analysis — check us out if you are considering animal behavioral clustering 🚀🐭 (we are not only for neural data! 🥳)
🔥 SuperAnimal: Foundation pose models for animals, trained on over 80K images, our model(s) can be used in the lab or the wild 🐭🐆🐄 💜models are available within @DeepLabCut & @huggingface w/extensive model/datacards 📰actu.epfl.ch/news/unifying-… 📄nature.com/articles/s4146…
1/2 Happy to present our new findings this Thurs 16:20 at the Mathematics of Neuroscience & AI conv. neuromonster.org. We use @TrackingActions’ lab @cebraAI to probe stimulus-induced cortical embeddings by layer, cell type, in a biophysical model of cortical microcircuit.
Delighted to play a small part in this tour de force from @Simon_CEChang et al ! Beautiful merger of many behavioral tasks, neural recordings, @cebraAI, opto & scRNA-seq across tasks to find flexibility (and some neg. valence stability) of neural ensembles in the amygdala 💪🔥
Check out my latest preprint with @FermaniFederica and @caina89: “Molecular and neural mechanisms of behavioural integration in the extended-amygdala”, now on biorxiv! biorxiv.org/content/10.110… 1/n
Mackenzie Mathis @TrackingActions @EPFL_en started #Cajal2024 with an intro to the study of movement. After, she presented the challenges and accomplishments of pose estimation and the latest developments of @DeepLabCut and @cebraAI. @Cajal_Training @bdxneuroschool 15/20
@AheadOfTheNerve @WeissShahaf Then I think it’s fair 😊 - MWM
@AheadOfTheNerve @WeissShahaf I wouldn’t recommend different iterations and temperatures if you want to head-to-head compare model infoNCE loss values; consistency would be okay though, as if you want to be sure they are each trained to be across-run consistent, then fine across animals/models
🦓 Self-supervised multimodal ML is promising the next AI breakthrough - in our new work published in @Nature, we debut @cebraAI: for self-supervised hypothesis- and discovery-driven science. 📝 doi.org/10.1038/s41586… 💻github.com/AdaptiveMotorC… 🦓 cebra.ai 🧵⬇️
#CEBRA🦓can be used to build a unified neural encoding model using data from many animals, and that can then be deployed on new animals for BMI-style decoding 🦾
🔥what was super exciting is the pre-trained encoder can be used to rapidly adapt to a new dataset, which doesn’t have the same # of neurons, etc, and by rapid, in this case less than 1 sec of new data! (And this is with a super simple MLP NN and kNN decoder!)
Did you know you can use #CEBRA for adapting to new animals, or decode across animals?! ⬇️
Alright, after a bit of a break, I want to highlight more features of CEBRA! (1) you can use it across subjects, combing spikes & calcium data to build a consistent space that can be used for cross-subject decoding! 🔥
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