EPFL researchers have managed to decode a mouse’s brain signals to predict what it sees using a new algorithm for building artificial neural network models designed to capture brain dynamics. This machine learning algorithm is called CEBRA and it can decode what a mouse sees while it watches a movie as well as reconstruct the positions of rats as they freely run around a room.
As the first mouse watched the movie, researchers used electric probes and optical probes to record brain activity. This data was then used to train CEBRA and when applied to the captured brain signals of another mouse watching the movie clip for the first time, the machine learning algorithm was able to identify specific frames it was seeing.
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CEBRA excels compared to other algorithms at reconstructing synthetic data, which is critical to compare algorithms. Its strengths also lie in its ability to combine data across modalities, such as movie features and brain data, and it helps limit nuances, such as changes to the data that depend on how they were collected,” said Steffen Schneider, the co-first author of the paper.