Linking central gene expression patterns and mental states using transcriptomics and large-scale meta-analysis of fMRI data: A tutorial and example using the oxytocin signaling pathway


The measurement of gene expression levels in the human brain can help accelerate our understanding of complex mental states and psychiatric illnesses. Mental states are typically associated with whole-brain networks, however, gene expression levels from post-mortem brain samples have traditionally been measured in a limited number of brain regions due to resource limitations. The recent availability of whole-brain gene expression data from the Allen Human Brain Atlas (AHBA) provides the opportunity to generate gene expression patterns for over 20,000 genes. By linking these expression patterns with brain activity patterns that are associated with specific mental states, researchers can better understand which genes may support given mental states, via forward inference. Conversely, reverse inference can also be used to determine which mental state activation patterns are most strongly associated with a given gene expression map. This chapter provides a step-by-step guide on how to use the AHBA in conjunction with the NeuroSynth fMRI meta-analysis tool to identify the mental state correlates of specific gene expression patterns, using genes from oxytocin signaling pathway as an example. We also demonstrate how to perform an out-of-sample validation and assess the specificity of results for genes of interest.

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