Figure 1: Precision in context representations.

Four different possibilities for precision. Top left: high-resolution and high-dimensional representations, as shown both by the high-resolution image (matrix) representing the spatial environment and the principal components breakdown (inset), which indicates relatively high dimensionality (several components explaining significant variance). In contrast, as shown on the top right, the matrix is the same size (resolution) but is blurred and thus of lower dimensionality. On the bottom left, the same image but in black and white is of lower resolution but comparable dimensionality to the original image. Finally, a low-resolution, low dimension image involves a blurred version of the black and white image.