Visualizations can be made to reflect high-dimensional data by letting values control visual attributes such as size, color, shape, rotation, and text labels.
Spontaneously emerging cortical representations of visual attributes.
Kenet, T. et al. Spontaneously emerging cortical representations of visual attributes.
Attractive visual attributes were found in species that are ecologically close, leading to an 'aesthetic bottleneck'.
Kenet, T., Bibitchkov, D., Tsodyks, M., Grinvald, A. & Arieli, A. Spontaneously emerging cortical representations of visual attributes.
Eight landscape photographs were evaluated for 11 visual attributes by 98 respondents.
These re-creations are typically evaluated and compared using those same visual attributes.
Jacques Bertin's six retinal properties describe the different visual attributes one can use to differentiate between data-driven shapes.
Kenet T, Bibitchkov D, Tsodyks M, Grinvald A, Arieli A. Spontaneously emerging cortical representations of visual attributes.
However, the present results demonstrate that these visual attributes are not necessarily needed in order to achieve high-level decoding accuracy.
Generally, the visual attributes that make species - or other objects - attractive are relatively similar: bright colours or the presence of contrasting patterns19.
