Abstract
Correlations of genetic variation in DNA with functional brain activity have already provided a starting point for delving into human cognitive mechanisms. However, these analyses do not provide the specific genes driving the associations, which are complicated by intergenic localization as well as tissue-specific epigenetics and expression. The use of brain-derived expression datasets could build upon the foundation of these initial genetic insights and yield genes and molecular pathways for testing new hypotheses regarding the molecular bases of human brain development, cognition, and disease. Thus, coupling these human brain gene expression data with measurements of brain activity may provide genes with critical roles in brain function. However, these brain gene expression datasets have their own set of caveats, most notably a reliance on postmortem tissue. In this perspective, I summarize and examine the progress that has been made in this realm to date, and discuss the various frontiers remaining, such as the inclusion of cell-type-specific information, additional physiological measurements, and genomic data from patient cohorts.
Subject
Applied Mathematics,Artificial Intelligence,Computer Science Applications,General Neuroscience
Cited by
10 articles.
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