Framewise co-activity patterns of functional MRI data may reflect the transient synchronization and coordination across brain regions. High-intensity frames of resting state fMRI have revealed granulated co-activation patterns that resembled the resting state brain networks. However, whether the low-intensity frames carry such information remains unclear. The present study trained variational autoencoder models with both positive values and negative values of normalized fMRI time series respectively and evaluated the two models on a separate dataset. We found the two models were very similar, suggesting that the negative-value frames can reflect transient brain co-activity patterns as the positive ones do.
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