The cells in the MST area have much larger receptive fields than the MT cells. This means that the MST cells can see even larger motion patterns composed of many local motions detected by the MT cells. Such a global motion pattern may reflect the global optic flow of the scene and can be represented by an array of arrows each representing the velocity, both direction and speed, of a local motion.
Optic flow plays an important role in the perception of 3D motion. When there exists a relative motion between an observer and the surrounding world, either some objects moving relative to the static observer, or, in the case of ego-motion, the observer moving in a stationary world, information about this overall motion can be extracted from the optic flow by the brain allowing for proper reaction. For example, when the eye is looking at the heading direction of an ego-motion, the optic flow forms an expansion pattern. When the motion is backward, a contraction pattern is formed instead. When the observer undergoes different 3D motions, various different optic flow pattern will be formed. It is the job of the visual system, artificial or biological, to compute the 2D optic flow and use it to estimate the 3D motion.
In computer vision, optic flow computation has been an active research subject and various algorithms have been developed to extract optic flow information from a sequence of images. (See, for example, [18] for detailed discussion on optic flow computation.) However, how optic flow patterns are computed and recognized in a biological visual system may be quite different.