<Tr> <Td> Hypercomplex </Td> <Td> orientation, motion, direction, length </Td> <Td> Brodmann areas 18 and 19 </Td> </Tr> <P> In extrastriate visual areas, cells can have very large receptive fields requiring very complex images to excite the cell . For example, in the inferotemporal cortex, receptive fields cross the midline of visual space and require images such as radial gratings or hands . It is also believed that in the fusiform face area, images of faces excite the cortex more than other images . This property was one of the earliest major results obtained through fMRI (Kanwisher, McDermott and Chun, 1997); the finding was confirmed later at the neuronal level (Tsao, Freiwald, Tootell and Livingstone, 2006). In a similar vein, people have looked for other category - specific areas and found evidence for regions representing views of places (parahippocampal place area) and the body (Extrastriate body area). However, more recent research has suggested that the fusiform face area is specialised not just for faces, but also for any discrete, within - category discrimination . </P> <P> Idealized models of visual receptive fields similar to those found in the retina, lateral geniculate nucleus (LGN) and the primary visual cortex of higher mammals can be derived in an axiomatic way from structural requirements on the first stages of visual processing that reflect symmetry properties of the surrounding world . Specifically, functional models for linear receptive fields can be derived in a principled manner to constitute a combination of Gaussian derivatives over the spatial domain and either non-causal Gaussian derivatives or truly time - causal temporal scale - space kernels over the temporal domain . Such receptive fields can be shown to enable computation of invariant visual representations under natural image transformations . By these results, the different shapes of receptive field profiles found in biological vision, which are tuned to different sizes and orientations in the image domain as well as to different image velocities in space - time, can be seen as well adapted to structure of the physical world and be explained from the requirement that the visual system should be invariant to the natural types of image transformations that occur in its environment . </P> <P> A computational theory for auditory receptive fields can be expressed in a structurally similar way, permitting the derivation of auditory receptive fields in two stages: </P>

Where are the receptive fields for vision located
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