Shypd.aiThe largest open index of AI toolsCebra is a machine-learning method that compresses time series data to reveal hidden structures, excelling with behavioral and neural data. It can decode neural activity to reconstruct videos and trajectories.
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Cebra is a machine-learning method designed to compress time series data, uncovering otherwise hidden structures within the variability of the data. It is particularly effective when applied to simultaneously recorded behavioral and neural data. The tool allows for the decoding of activity from the visual cortex of the mouse brain to reconstruct viewed videos, and can decode trajectories from the sensorimotor cortex of primates. Cebra supports both calcium and electrophysiology datasets across various sensory and motor tasks, and can be used for simple or complex behaviors across species. It offers flexibility for single and multi-session datasets, enabling hypothesis testing or label-free analysis. The method produces consistent, high-performance latent spaces, which can be used for mapping space, uncovering complex kinematic features, and rapid, high-accuracy decoding.
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