transforms. Later in time (after 100 ms), neurons in V1 are also sensitive to the more global organisation of the scene (Lamme & Roelfsema, 2000). These response properties probably stem from recurrent feedback processing (the influence of higher-tier cortical areas on lower-tier cortical areas) and lateral connections from pyramidal neurons (Hupe et al. 1998). While feedforward connections are mainly driving, feedback connections are mostly modulatory in their effects (Angelucci et al., 2003; Hupe et al., 2001). Evidence shows that feedback originating in higher-level areas such as V4, IT, or MT, with bigger and more complex receptive fields, can modify and shape V1 responses, accounting for contextual or extra-classical receptive field effects (Guo et al., 2007; Huang et al., 2007; Sillito et al., 2006). The visual information relayed to V1 is not coded in terms of spatial (or optical) imagery but rather are better described as edge detection. As an example, for an image comprising half side black and half side white, the dividing line between black and white has strongest local contrast (that is, edge detection) and is encoded, while few neurons code the brightness information (black or white per se). As information is further relayed to subsequent visual areas, it is coded as increasingly non-local frequency/phase signals. Note that, at these early stages of cortical visual processing, spatial location of visual information is well preserved amid the local contrast encoding (edge detection). A theoretical explanation of the computational function of the simple cells in the primary visual cortex has been presented in. It is described how receptive field shapes similar to those found by the biological receptive field measurements performed by DeAngelis et al. can be derived as a consequence of structural properties of the environment in combination with internal consistency requirements to guarantee consistent image representations over multiple spatial and temporal scales. It is also described how the characteristic receptive field shapes, tuned to different scales, orientations and directions in image space, allow the visual system to compute invariant responses under natural image transformations at higher levels in the visual hierarchy. In primates, one role of V1 might be to create a saliency map (highlights what is important) from visual inputs to guide the shifts of attention known as gaze shifts. According to the V1 Saliency Hypothesis, V1 does this by transforming visual inputs to neural firing rates from millions of neurons, such that the visual location signaled