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Cebra

research-assistant

About

Learnable latent embeddings for joint behavioral and neural analysis

Website Rank
 
5.26M
Category Rank
(Science_and_Edu…)
4.2K
Country Rank
(US)
2.36M
Website Traffic
 
11.6K
Monthly Visits Trend
Top Traffic Countries
Top Traffic Sources
Recent Reviews
 
10
Company Size
 
-
Employees On Linkedin
 
-
Twitter Followers
 
1.4K
Twitter Likes
 
111
Twitter Posts
 
55
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Facebook Likes
 
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Summary

CEBRA is a novel encoding method that jointly uses behavioural and neural data to produce consistent and high-performance latent spaces.

Features

  • Consistent and high-performance latent spaces
  • Can be used for hypothesis testing or label-free analysis
  • Mapping of space and uncovering complex kinematic features
  • Rapid and high-accuracy decoding of natural movies from visual cortex

Use Cases

  • Neural dynamics modeling during adaptive behaviors
  • Probing neural representations
  • Investigating sensory and motor tasks
  • Analyzing calcium and electrophysiology datasets
  • Decoding video frames using embeddings
Recent Reviews (10)
TrackingActions
2023-10-17

RT by @tak_yamm: Yes, you can use it in this manner. @cebraAI has a DeepLabCut loading function already, see docs! https://cebra.ai/docs/usage.html - We demo this use in Ye et al 2023a: https://arxiv.org/abs/2203.07436 - And in Ye et al 2023b AmadeusGPT: https://arxiv.org/abs/2307.04858

dr_alexharris
2023-10-17

R to @TrackingActions: So exciting! Thank you!

cebraAI
2023-10-16

RT by @rgonzalezlaiz: πŸŽ‰πŸ”₯ CEBRA has hit 10K downloads in < 6 months, and we have a new pypi release 0.3.0 to celebrate! πŸŽ‰ Full notes: https://github.com/AdaptiveMotorControlLab/CEBRA/releases thanks to @stes_io @NasFilippova @rgonzalezlaiz @celia_bqt @TrackingActions & the new external contributors too πŸ™πŸΌπŸ”₯πŸ¦“

_Silver_Black_
2023-10-13

R to @TrackingActions: Also in Switzerland! πŸ˜†

AheadOfTheNerve
2023-10-13

R to @TrackingActions: πŸ€”πŸ€”

TrackingActions
2023-10-11

R to @sofroniewn: I’m just not a fan of autoencoders when contrastive learning does a better job at finding true latents; reconstructing complex inputs is still hard. So, in short yes, we start by using identifiable models with @cebraAI and we will have more work up soon on explainability πŸ˜ƒ

TrackingActions
2023-10-07

R to @TrackingActions: Link!! https://www.linkedin.com/posts/mackenziemathis_the-mathis-lab-of-adaptive-motor-control-activity-7115645199027957760-j8Ej?utm_source=share&utm_medium=member_ios

ChuckleScience
2023-10-04

R to @ChuckleScience: Students learnt to use open source tools like @Prusa3D, @arduino, @bonsai_rx, @ThePSF, @DeepLabCut, #keypointMoSeq, @cebraAI, and important concepts to use these in the study of animal behavior.

cebraAI
2023-10-03

πŸ‘€ we have a new pypi release coming out in the next days!! Stay tuned for some nice updates! πŸ¦“πŸŽ‰

AIBleak
2023-10-02

Hello @cebraAI, you have been featured on our portal @AIBleak https://aibleak.com/product/cebra Share with your friends and get reviews to get into the top list.

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