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Surround modulation in visual motion areas was studied with the static MAE and fMRI. Stimuli were composed of a luminance defined central motion area, with a surround that could be static during adaptation or moving. Static surround attributes (MAE Experiments 1-3) could involve colour and could change between adaptation and test. Changing surround attributes from luminance to colour or vice versa between adaptation and test reduced the MAE. Colour changes between adaptation and test caused a greater MAE reduction than luminance contrast changes. In fMRI Experiments 4-6, surround modulation was tested through BOLD activity evoked within ROIs. These were defined as motion selective areas of cortex that had some retinotopic organisation and corresponded topographically to the foveally located central part of the stimulus. Voxels directly activated by the surround were excluded from the ROIs. Width and velocity of rings defining the centre-surround stimuli either controlled for the cortical magnification factor (M-scaled) or did not.

In this thesis I begin by extending previous psychophysical research on the effects of visual motion on spatial localisation. In particular, I measured the perceived spatial shift of briefly presented static objects adjacent to a moving stimulus. It was found that the timing of the presentation of static objects with respect to nearby motion was crucial. I also found a decrease of this motion induced spatial displacement with the increasing distance of static objects from motion, suggesting a local effect of motion. The induced perceptual shift could also be reduced by introducing transient stimuli (flickering dots) in the background of the display. The next stage was to construct a computational model to provide a mechanism that could facilitate such shifts in position. To motivate our combined model of motion computation and spatial representation we considered what functions could be attributed to V1 cells on the basis of their contrast sensitivity functions. I found that functions based on sums of differential of Gaussian operators could provide good fits to previously found V1 data. The properties of V1 cells as derivatives of Gaussian kernel filters on an image were used to build a spatial representation, where position is represented in the weighting of these filter outputs, rather than in a one-to-one isomorphic representation of the scene. This image representation can also be used along with temporal derivatives to calculate motion using the Multi-Channel Gradient Model scheme (Johnston et al, 1992). 1 demonstrate how this framework can incorporate motion signals to produce "in place" shifts of visual location. Finally a combined model of motion and spatial location is outlined and evaluated in relation to the psychophysical data.

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A preliminary study by Freeman et al (1996b) has suggested that when complex patterns of motion elicit impressions of 2-dimensionality, odd-item-out detection improves given targets can be differentiated on the basis of surface properties. Their results can be accounted for, it if is supposed that observers are permitted efficient access to 3-D surface descriptions but access to 2-D motion descriptions is restricted. To test the hypothesis, a standard search technique was employed, in which targets could be discussed on the basis of slant sign. In one experiment, slant impressions were induced through the summing of deformation and translation components. In a second theory were induced through the summing of shear and translation components. Neither showed any evidence of efficient access. A third experiment explored the possibility that access to these representations may have been hindered by a lack of grouping between the stimuli. Attempts to improve grouping failed to produce convincing evidence in support of life. An alternative explanation is that complex patterns of motion are simply not processed simultaneously. Psychophysical and physiological studies have, however, suggested that multiple mechanisms selective for complex motion do exist. Using a subthreshold summation technique I found evidence supporting the notion that complex motions are processed in parallel. Furthermore, in a spatial summation experiment, coherence thresholds were measured for displays containing different numbers of complex motion patches. Consistent with the idea that complex motion processing proceeds in parallel, increases in the number of motion patches were seen to decrease thresholds, both for expansion and rotation. Moreover, the rates of decrease were higher than those typically expected from probability summation, thus implying mechanisms are available, which can pool signals from spatially distinct complex motion flows.