Fig. 3. Using cortical functional network information to discriminate between mouse models of autism and wild-type mice (IMAGE)
Caption
A, The support vector machine learns cortical functional network information before and after the onset of behavior, and discriminates between autism model mice and wild-type mice based on test data. B, Discrimination accuracy of machine learning when using data from each 1-second time window at the locomotion start point (green: results when trained with all functional bonds, blue: results when trained with only the top 1% functional bonds in the importance index, gray: results when trained with random data). C, Importance index of functional domains. The higher the value, the more important it is for discriminating between autism model mice and wild-type mice. The figure on the right is a visualization of the most important index connections.
Credit
Nakai, N., Sato, M., Yamashita, O. et al. Virtual reality-based real-time imaging reveals abnormal cortical dynamics during behavioral transitions in a mouse model of autism. Cell Reports (2023). DOI：10.1016/j.celrep.2023.112258
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