The perception of a familiar face is no more than the sum of its parts.

Why do faces become easier to recognize with repeated exposure? Previous research has suggested that familiarity may induce a qualitative shift in visual processing from an independent analysis of individual facial features to analysis that includes information about the relationships among features (Farah, Wilson, Drain, & Tanaka Psychological Review, 105, 482-498, 1998; Maurer, Grand, & Mondloch Trends in Cognitive Science, 6, 255-260, 2002). We tested this idea by using a "summation-at-threshold" technique (Gold, Mundy, & Tjan Psychological Science, 23, 427-434, 2012; Nandy & Tjan Journal of Vision, 8, 3.1-20, 2008), in which an observer's ability to recognize each individual facial feature shown independently is used to predict their ability to recognize all of the features shown in combination.

The efficiency of dynamic and static facial expression recognition.

Unlike frozen snapshots of facial expressions that we often see in photographs, natural facial expressions are dynamic events that unfold in a particular fashion over time. But how important are the temporal properties of expressions for our ability to reliably extract information about a person's emotional state? We addressed this question experimentally by gauging human performance in recognizing facial expressions with varying temporal properties relative to that of a statistically optimal ("ideal") observer. We found that people recognized emotions just as efficiently when viewing them as naturally evolving dynamic events, temporally reversed events, temporally randomized events, or single images frozen in time.