A sequence of mechanisms in the visual system transforms retinal images into codes for increasingly complex form representations (Cadieu et al.,
2007; Felleman & Van Essen,
1991; Hubel & Wiesel,
1968; Lennie,
1998). The mechanisms are often comprised of populations of neurons individually sensitive to a narrow range of a particular stimulus dimension but collectively sensitive to the whole range of that dimension (Clifford,
2014; Clifford et al.,
2007; Kohn,
2007; Storrs & Arnold,
2012). Neurons of the primary visual cortex (V1) are locally selective for orientation and spatial-frequency (Blakemore & Campbell,
1969; De Valois, Yund, & Hepler,
1982; Hubel & Wiesel,
1968) and in V2 they can, in addition, analyze angles and curves (Hegde,
2000; Ito & Komatsu,
2004). These properties could be considered one-dimensional as they concern the properties of a line. In V4, populations of neurons selective for the relative positions of such properties present on a boundary are used in the analysis of the complex two-dimensional shape of objects (Badcock, Almeida, & Dickinson,
2013; Bell, Dickinson, & Badcock,
2008; Bowden, Dickinson, Fox, & Badcock,
2015; Dickinson, Bell, & Badcock,
2013; Dickinson, Cribb, Riddell, & Badcock,
2015; El-Shamayleh & Pasupathy,
2016; Pasupathy & Connor,
1999,
2001,
2002), while a response to perceived size (Mikellidou et al.,
2016) and shape (Ellison & Cowey,
2009; Silson et al.,
2013) have been reported in LO1 and LO2, respectively. Although analyses of the boundaries of objects are frequently of critical importance to their identification it is often a contrast in visual properties between the interior of the boundary of the object and its background that defines the position of the boundary (Tan, Dickinson, & Badcock,
2013). Aggregation of the responses of V1 neurons with consistent or smoothly varying orientation, spatial frequency, color, or disparity can, therefore, allow perceptual segmentation of the visual field.