CEBRA

About CEBRA

CEBRA is a powerful machine-learning platform designed to analyze joint behavioral and neural data. Targeting neuroscientists, it provides innovative latent embedding techniques that reveal correlations between behavior and neural activity. Users benefit from high-performance models capable of decoding complex brain functions and enhancing research outcomes.

CEBRA offers free access to its innovative machine-learning tools, with plans for premium features in development. Users can access both basic and advanced functionalities for analyzing neural data, maximizing their research capabilities. Upgrading unlocks exclusive tools, enhancing data analysis and modeling experience significantly.

CEBRA features a user-friendly interface that simplifies the process of analyzing complex datasets. Its intuitive design ensures seamless navigation through various functionalities, allowing researchers to focus on their data rather than the tools. With innovative visuals and layouts, browsing becomes an engaging and efficient experience.

How CEBRA works

Users begin by onboarding with CEBRA, where they can upload behavioral and neural data sets. The platform facilitates a straightforward process to select models and parameters for analysis. Once configured, users navigate the intuitive dashboard to interpret embeddings, decode behaviors, and visualize results seamlessly. CEBRA optimizes these key interactions for maximum efficiency in neuroscience research.

Key Features for CEBRA

High-Performance Latent Spaces

CEBRA offers high-performance latent spaces that reveal complex neural dynamics and behavioral correlations. This unique capability allows researchers to uncover meaningful structures in large datasets, streamline data analysis, and enhance the understanding of neural behavior relationships, making it a vital tool in neuroscience studies.

Decoding Brain Activity

With CEBRA, users can decode brain activity from neural data, translating complex signals into understandable behavioral metrics. This feature enhances traditional research methods, providing a robust approach to analyze and predict outcomes based on neural activity, ultimately advancing neuroscience research methodologies.

Flexible Dataset Integration

CEBRA supports single and multi-session datasets, allowing users to conduct rigorous hypothesis testing without needing extensive label data. This flexibility facilitates diverse research applications, enabling users to examine complex behaviors across various species in a streamlined and efficient manner.