In agreement with neurophysiological studies showing sensitivity of IT neurons to stimulus position (DiCarlo & Maunsell,
2003; Op De Beeck & Vogels,
2000), human imaging studies have found that areas in human ventral visual cortex are topographically organized (Arcaro, McMains, Singer, & Kastner,
2009; Brewer, Liu, Wade, & Wandell,
2005; Sayres & Grill-Spector,
2008) and that the position of an object can be decoded using multivoxel pattern analyses in higher areas such as LO (Carlson et al.,
2011; Cichy et al.,
2011; Sayres & Grill-Spector,
2008; Schwarzlose et al.,
2008). Similarly, MEG studies using source localization have shown that varying the position of a stimulus evokes distinct patterns of activity in ventral temporal cortex (Liu & Ioannides,
2006,
2010). Solidifying position coding in ventral temporal cortex introduces an important constraint on models of object recognition, as these models need to account for the sensitivity of IT neurons to retinal location. One possibility is that position invariance can be addressed at the population level by integrating responses across individual neurons (DiCarlo & Cox,
2007; for a critique of this account, see Robbe & Op de Beeck,
2009). This account has received empirical support from both neurophysiological and imaging studies showing that linear classifiers can read out category and identity information from areas in the ventral temporal pathways across changes in position and size (Carlson et al.,
2011; Cichy et al.,
2011; Hung et al.,
2005; MacEvoy & Epstein,
2007; Sayres & Grill-Spector,
2008; Schwarzlose et al.,
2008; Williams et al.,
2008).