Although many studies have used brain measurements of hetero- and homosexual individuals to discern potential characteristics, it has been difficult to draw valid and robust conclusions due to the small sample sizes of most studies and the variability of experimental designs. Newer resting-state functional connectivity (RSFC) fMRI methods are easier and cheaper to conduct, have a much better signal-to-noise ratio, and allow for a substantially larger suitable population of participants.
Using this RSFC methodology, a recent study investigated whether sexual orientation can be reliably predicted, based solely on a brief five-minute brain scan, using machine learning programming and predictive pattern classification.
This study demonstrated for the first time that a simple five-minute resting-state scan of the human brain can, with high [83%] accuracy, successfully predict sexual orientation in healthy participants. Sexual orientation is a highly complex human trait. While the differences in brain measurements between homo- and heterosexual participants allowed for a relatively accurate prediction of sexual orientation, the results of this study do not address the question of what caused these differences, such as the effects of nature or nurture.
