Bidirectional Mapping

This step employs dual regression to enable quantitative comparison cross species, using the latent embedding defined previously.

• Dual regression is a method used to project group-level patterns (e.g., networks derived from Independent Component Analysis) onto individual subject data. Previous work have also employed this method to translate brain phenotypes across species using gene expression data.

• In our pipeline, first, the value of imaging phenotype in mouse brain of ROIs was first regressed by the mouse graph embedding to calculate a β matrix.

• Then, we used the β matrix dot the graph embedding matrix of human, which will output an estimate vector consistent with the ROIs number of the human brain.

• To maintain stability, this process was repeated 500 times to generate the final average vector. The same procedure was applied in reverse for human-to-mouse mapping.

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🔔 This process has been embedded into the transbrain.trans.SpeciesTrans() class. You can directly refer to the source code in Mapping Functions page and go to Tutorials to learn the usage.