It is a principal open question whether noninvasive imaging methods in humans candecode information encoded at a spatial scale as fine as the basic functional unit of cortex: cortical columns. We addressed this question in five magnetoencephalography

Humans recognize faces and objects with high speed and accuracy regardless of their orientation. Recent studies have proposed that orientation invariance in face recognition involves an intermediate representation where neural responses are similar for mirrorsymmetric views. Here, we used fMRI, multivariate pattern analysis, and computational modeling to investigate the neural encoding of faces and vehicles at different rotational angles. Corroborating previous studies, we demonstrate a representation of face orientation in the fusiform face-selective area (FFA). We go beyond these studies by showing that this representation is category-selective and tolerant to retinal translation. Critically, by controlling for low-level confounds, we found the representation of orientation in FFA to be compatible with a linear angle code. Aspects of mirror-symmetric coding cannot be ruled out when FFA mean activity levels are considered as a dimension of coding. Finally, we used a parametric family of computational models, involving a biased sampling of view-tuned neuronal clusters, to compare different face angle encoding models. The best fitting model exhibited a predominance of neuronal clusters tuned to frontal views of faces. In sum, our findings suggest a category-selective and monotonic code of face orientation in the human FFA, in line with primate electrophysiology studies that observed mirror-symmetric tuning of neural responses at higher stages of the visual system, beyond the putative homolog of human FFA.

Knowledge about the principles that govern large-scale neural representations of objects is central to a systematic understanding of object recognition. We used functional magnetic resonance imaging (fMRI) and multivariate pattern classification to investigate two such candidate principles: category preference and location encoding. The former designates the preferential activation of distinct cortical regions by a specific category of objects. The latter refers to information about where in the visual field a particular object is located. Participants viewed exemplars of three object categories (faces, bodies, and scenes) that were presented left or right of fixation. The analysis of fMRI activation patterns revealed the following. Category-selective regions retained their preference to the same categories in a manner tolerant to changes in object location. However, category preference was not absolute: category-selective regions also contained location-tolerant information about nonpreferred categories. Furthermore, location information was present throughout high-level ventral visual cortex and was distributed systematically across the cortical surface. We found more location information in lateral-occipital cortex than in ventral-temporal cortex. Our results provide a systematic account of the extent to which the principles of category preference and location encoding determine the representation of objects in the high-level ventral visual cortex.