How do we recognize a face? To date, most research has answered “holistically”: We look at all the features—eyes, nose, mouth—simultaneously and, perceiving the relationships among them, gain an advantage over taking in each feature individually. Now a new study overturns this theory. The researchers—Jason M. Gold and Patrick J. Mundy of the Indiana University and Bosco S. Tjan of the University of California Los Angeles—found that people’s performance in recognizing a whole face is no better than their performance with each individual feature shown alone. “Surprisingly, the whole was not greater than the sum of its parts,” says Gold. The findings appear in the journal Psychological Science, which is published by the Association for Psychological Science.
To predict each participant’s best possible performance in putting together the individual features, the investigators used a theoretical model called an “optimal Bayesian integrator” (OBI). The OBI measures someone’s success in perceiving a series of sources of information—in this case, facial features—and combines them as if they were using the sources together just as they would when perceiving them one by one. Their score recognizing the combination of features (the whole face) should equal the sum of the individual-feature scores. If the whole-face performance exceeds this sum, it implies that the relationships among the features enhanced the information processing—that is, “holistic” facial recognition exists.