Cebra
RecommendedLearnable latent embeddings for joint behavioral and neural analysis
June 23rd, 2026
About Cebra
Cebra is an advanced machine learning solution that employs non-linear methods to generate reliable and efficient latent spaces from concurrent recordings of neural and behavioral data.
Key Features
- Neural Latent Embeddings tool for hypothesis testing and discovery-driven analysis
- Validated accuracy proven on various datasets and tasks across species
- Can be used with single or multi-session datasets and without labels
- Provides high-accuracy decoding of natural movies from visual cortex
- Code available on GitHub and pre-print available on arxiv.org
Use Cases
- Analyze and decode behavioural and neural data to uncover neural representations
- Map and reveal complex kinematic features in neuroscience research
- Produce consistent latent spaces across different data types and experiments
- Helps neuroscientists better understand underlying neural representations involved in adaptive behaviours
Other Features
- Open Source
- No Signup Required
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