A Simple Scan Can Tell How Fat You'll Get and How Much Sex You'll HaveS

The world is full of delicious food and beautiful people, and sometimes it's hard to turn down their respective charms. But now a team of researchers has used data from fMRI scans to successfully predict weight gain and sexual activity—and can tell if you're likely to fall foul of temptation well in advance.

Using functional MRI scans, a team of scientists from Dartmouth has been studying a region of the brain known as the nucleus accumbens—part that people often refer to as the "reward center". In fact, the researchers rounded up a group of first year university students and then scanned their brains while showing them neutral images—such as environmental scenes—or something rather more enticing: pictures of appetizing food of erotic photographs.

After processing the data from the scans, the researchers waited six months before asking each participant to fill in a questionnaire. They found that those people whose reward centers responded most strongly to pictures of food had gained significantly more weight than the others. Likewise, those whose brains had responded most strongly to erotic images had gone on to be more sexually active. The research appears in tomorrow's issue of The Journal of Neuroscience.

With temptation all around us, it can sometimes be difficult to avoid giving in. Sadly, even though the researchers can now predict your weight gain or sexual needs, it's still up to you to control your urges. William Kelley, one of the researchers, agrees:

"We seek to understand situations in which people face temptations and try to not act on them... You need to actively be thinking about the behavior you want to control in order to regulate it. Self-regulation requires a lot of conscious effort."

The researchers suggest that learning what the trigger for your cravings is—from the arrival of a dessert cart to something a little more, umm, physical—is a good first step in keeping your urges at bay. Or, well, you could just give in. [The Journal of Neuroscience via EurekAlert]

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