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- Kirkby, Lowry A.; Luongo, Francisco J.; Lee, Morgan B.; Nahum, Mor; Van Vleet, Thomas M.; Rao, Vikram R.; Dawes, Heather E.; Chang, Edward F.; Sohal, Vikaas S.
- Cell 2018 v.175 no.6 pp. 1688-1700.e14
- amygdala; anxiety; artificial intelligence; data collection; electroencephalography; hippocampus; humans
- ... Human brain networks that encode variation in mood on naturalistic timescales remain largely unexplored. Here we combine multi-site, semi-chronic, intracranial electroencephalography recordings from the human limbic system with machine learning methods to discover a brain subnetwork that correlates with variation in individual subjects’ self-reported mood over days. First we defined the subnetwork ...
- Schmiedel, Benjamin J.; Singh, Divya; Madrigal, Ariel; Valdovino-Gonzalez, Alan G.; White, Brandie M.; Zapardiel-Gonzalo, Jose; Ha, Brendan; Altay, Gokmen; Greenbaum, Jason A.; McVicker, Graham; Seumois, Grégory; Rao, Anjana; Kronenberg, Mitchell; Peters, Bjoern; Vijayanand, Pandurangan
- Cell 2018 v.175 no.6 pp. 1701-1715.e16
- data collection; databases; epigenetics; gene expression; genes; genetic polymorphism; genetic variation; genotype; human diseases; humans; pathogenesis; quantitative trait loci; risk
- ... While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (database of immune cell expression, expression quantitative trait loci [eQTLs], and epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified c ...