• Corpus ID: 9177366

Running head : DIVISIVE NORMALIZATION AND FACIAL ATTRACTIVENESS 1 Facial attractiveness choices predicted by divisive normalization

@inproceedings{Furl2016RunningH,
  title={Running head : DIVISIVE NORMALIZATION AND FACIAL ATTRACTIVENESS 1 Facial attractiveness choices predicted by divisive normalization},
  author={Nicholas Furl},
  year={2016}
}
Do people appear more or less attractive depending on the company they keep? I employed normalization models to predict context dependence of facial attractiveness preferences. Divisive normalization – where representation of stimulus intensity is normalized (divided) by concurrent stimulus intensities – predicts that choice preferences between options increase with the range of option values. I manipulated attractiveness range trial-by-trial by varying the attractiveness of undesirable… 

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