Natural variability is essential to learning new faces

ABSTRACT

We learn new faces throughout life, for example in everyday settings like watching TV. Recent research has shown that image variability is key to this ability: if we learn a new face over highly variable images, we are better able to recognize that person in novel pictures. Here we asked people to watch TV shows they had not seen before, and then tested their ability to recognize the actors. Some participants watched TV shows in the conventional manner, whereas others watched them upside down or contrast-reversed. Image variability is equivalent across these conditions, and yet we observed that viewers were unable to learn the faces upside down or contrast-reversed—even when tested in the same format as learning. We conclude that variability is a necessary, but not sufficient, condition for face learning. Instead, mechanisms underlying this process are tuned to extract useful information from variability falling within a critical range that corresponds to natural, everyday variation.

KEYWORDS:

• Face recognition
• face learning

Acknowledgements

We would like to thank Renée Lefebvre for taking part in the initial piloting of the video procedure.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007–2013) / ERC Grant Agreement n.323262 to AMB, and from the Economic and Social Research Council, UK [ES/J022950/1] to AMB.