CEBRA is a powerful machine learning tool that enables scientists to unlock the mysteries of behavior and neural activity. It uses advanced non-linear techniques to generate consistent and high-performance latent spaces from joint behavioural and neural data recorded simultaneously. This allows researchers to map behavioural actions to neural activity, enabling them to gain a better understanding of neural dynamics during adaptive behaviours and uncover underlying correlations of behaviour. CEBRA’s neural latent embeddings can be used for both hypothesis testing and discovery-driven analysis. It is incredibly versatile, with users able to customize parameters and settings to fit their research needs. It is also user-friendly, with an intuitive interface and streamlined workflows that make it simple to use. With CEBRA, scientists have the power to generate data-driven insights and uncover the hidden mechanisms of behaviour.
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