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with mimicry, as in the first example, is that the original association between (A) yellow and black insects and (B) dangerous is that nondangerous insects resembling the dangerous ones will also be avoided by predators and thus are more likely to survive and pass on the genes for coloration that more closely match the dangerous species. The second example illustrates the same principle of mimicry and exploitation of an A-B association in which evolution favored those nonpoisonous snakes that resembled the poisonous ones. “Indeed, an evolutionary lag following a changed environment provides another route to superstitious behaviours,” Foster and Kokko explained, “whereby an organism associates two events that once were, but are no longer causally related, e.g. a predator goes extinct but the prey still hides at night.”

The third example of the E. coli swimming toward the taste of a substance chemically similar to aspartate because of its original preference for the real thing has obvious parallels with the human enjoyment of artificial sweeteners as well as with our modern problem of obesity. In the natural environment, (A) sweet and rich foods are strongly associated with (B) nutritious and rare. Therefore, we gravitate to any and all foods that are sweet and rich, and because they were once rare we have no satiation network in the brain that tells us to shut off the hunger mechanism, so we eat as much as we can of them. On the other end of the taste spectrum, there is the well-known taste aversion effect—one-trial learning—where the pairing of a food or drink with severe nausea and vomiting often results in a long-term aversion for that food or drink. In my case it was a graduate school pairing of (A) too much cheap red wine with (B) a night of vomiting that made it difficult for me for decades to enjoy red wines, even expensive labels. The evolutionary significance is clear: foods that can kill you (but don’t) should never be tried a second time, so one-trial learning evolved as an important adaptation.

Supernormal Patternicities

Supernormal stimuli combine the principles of mimicry and the SS-IRM-FAP system and are another example of an innate form of patternicity. Niko Tinbergen, for example, discovered that gull chicks peck even more fervently at a fake bill that is longer and narrower than the real beak of their mother. He also studied a species of bird that normally nests upon small pale blue eggs with gray specks on them and found that he could get them to prefer sitting on giant bright blue eggs speckled with black polka dots. It’s a form of tricking a brain preprogrammed by evolution to expect certain patterns by exposing it to exaggerated forms of the same.18

Harvard University evolutionary psychologist Deirdre Barrett, in her 2010 book Supernormal Stimuli, documented numerous instances of ancient innate human patternicities hijacked by the modern world.19 In addition to the pattern of sweet and rich foods leading to obesity mentioned above, Barrett outlined how modernity has commandeered our ancient propensities for patterns of sexual preferences, leading to expectations of women’s faces and figures to match the supernormal stimuli seen in perfect (and perfectly modified) supermodels with long legs, hourglass figures, 0.7 waist-to-hip ratios, enlarged breasts, perfectly symmetrical faces with blemish-free complexions, full lips, large alluring eyes with dilated pupils, and full, thick heads of hair. In the environment of our Paleolithic ancestors, the “normal” dimensions of these physical characteristics were proxies for genetic health, and thus there was a natural selection for emotional preference for women who approximated such physicality. Like food that is nutritionally rich and environmentally rare, such physical characteristics are both strongly desired and without satiation, so our brains can be tricked into feeling that more is better.

Today, of course, no one walks into a nightclub with calipers to measure waist-to-hip ratios or facial symmetries. Evolution has done the measuring for us, leaving