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Open access visualization of Heatmap, LDA Classifier, Multiunit Activity, Confusion Matrices, Decoding Accuracy
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Pairwise identity decoding results. At each 0.5 s time bin, an LDA classifier was trained to distinguish between each pair of modalities based on the top 40 principal components of multiunit activity. The 70 trials per modality were randomly divided in half to generate train and test data 1,000 times, and the accuracies of the resulting decoders were averaged together to yield the values in the confusion matrices. Asterisks represent significantly different accuracies relative to a null distribution, which was generated by training the same decoder on data with shuffled labels 1,000 times.*Significantly different 95% confidence intervals (CIs);**97.5% CIs;***99% CIs.

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