Protocol for extracting and evaluating activity distributions in rat electrocorticograms with principal component analysis and k-nearest neighbor

Le résumé fourni par la source

Principal component analysis (PCA) and k-nearest neighbor (kNN) can be applied to extract and compare activity distributions from electrocorticogram (ECoG) signals across recorded neural activity. Here, we present a protocol for recording ECoG activity from the neocortex of rats and applying PCA and kNN on the recorded data. This protocol allows for comparison between different types of cortical activity in a multidimensional space. For complete details on the use and execution of this protocol, please refer to Mellbin et al. 1

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