I've been researching the process of performing a spatial correlation between gene expression in the brain and particular imaging phenotypes such as structural white matter connectivity. My research thus far has been on functional imaging phenotypes rather than structural, but when reading G.Z Wang et al. 2016, which performs a correlation between gene expression and rs-fMRI in the default-mode network I noticed that the authors specifically note their choice to use resting-state data was because "it might be difficult to meaningfully relate brain gene expression to brain activity measured during specific task-based paradigms" due to the postmortem nature of transcriptome data collection. This seems to effectively discount most functional imaging phenotypes as viable for correlation with gene expression such as MEG response latency—either they have to be static or display static trends over a period of time. Is this generally true as far as linking transcriptomics withe neuroimaging, or is this specific to the author's method of analysis?



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