Visual features contribute differently to preferences for different item categories

Low-level visual features have been known to play a role in value-based decision-making. However, thus far, mainly single features were tested on one type of item using one method of measurement. Here, we test the contribution of low-level visual features on three items types: fractal-art images, faces, and snack food items. We test the role of visual features on preferences using both subjective ratings and choices. We show that low-level visual features contribute to value-based decision-making even after controlling for higher level configural features of faces like eye-distance and market features of snacks like calories. Importantly, we show that while low-level visual features consistently contribute to value-based decision-making, different features contribute to different types of items when using different measurement methods. Our study highlights the necessity of using multiple item types and multiple measurement methods to construct a unifying framework regarding the contribution of low-level features to value-based decision-making.