CEBRA

About CEBRA

CEBRA is a powerful platform designed to analyze behavioral and neural data jointly, aiming to uncover hidden dynamics in neuroscience research. Its core innovative feature is non-linear latent embedding, which provides consistent representations of complex behaviors, enhancing researchers' understanding of neural activity during adaptive behaviors.

CEBRA offers a free access tier for users to explore its capabilities. For enhanced features, researchers can upgrade to premium plans providing advanced analysis tools and support. Investing in higher tiers grants access to comprehensive insights, thus driving more effective utilization of behavioral and neural data.

CEBRA features an intuitive user interface that streamlines the data analysis process for researchers. With clear navigation and user-friendly design elements, it allows seamless integration and exploration of datasets. The platform’s layout enhances user experience, making it easy to retrieve insights from complex behavioral-neural interactions.

How CEBRA works

Users interact with CEBRA by uploading their behavioral and neural datasets through a simple onboarding process. Once uploaded, they can utilize the platform's advanced machine learning features to create latent embeddings, allowing them to visualize and analyze the correlations between behavioral actions and neural activity effectively. With options for hypothesis testing and label-free analysis, CEBRA ensures a smooth navigation experience, enhancing research accuracy and productivity.

Key Features for CEBRA

Joint Behavioral and Neural Data Analysis

CEBRA's joint behavioral and neural data analysis feature stands out by efficiently integrating large datasets to produce consistent latent spaces. It benefits researchers by revealing intricate relationships between neural dynamics and behaviors, enhancing their ability to draw meaningful conclusions in neuroscience studies.

High-Performance Latent Space Creation

CEBRA excels in high-performance latent space creation, allowing users to visualize complex datasets effectively. This unique feature aids researchers in uncovering hidden patterns in behavioral and neural data, enhancing their ability to analyze and interpret results accurately, thus improving their research endeavors.

Hypothesis-Driven and Discovery-Driven Analysis

CEBRA offers both hypothesis-driven and self-supervised discovery-driven analysis capabilities. This flexibility not only accommodates various research needs but also empowers users to explore and validate their findings in innovative ways, making CEBRA a valuable asset for neuroscience researchers seeking comprehensive insights.