Neural control refers to the manipulation of inputs to particular structures of the nervous system to cause desirable output behavior. There are two kinds of neural control mechanisms, namely, closed loop and open loop. As an example of the former, the hypothalamus receives sensory information from the body to control its temperature. If the environmental temperature rises, then the hypothalamus makes the skin sweat to cool the body. This temperature control is called closed loop, because after the output behavior is modified, new sensory data are taken to see whether the output behavior should be increased or reduced. Hence, closed-loop neural control depends on feedback information about the effects of output behavior. In contrast, the nervous system can sometimes perform open-loop control. This form of control does not rely on feedback to correct erroneous outputs, and thus, the nervous system must rely on knowledge of system behavior to compute its output. Therefore, open-loop neural control requires accurate models of the system. Although such control can be less precise, it has the advantage of speed, because it does not require feedback for computations. One example of open-loop neural control occurs in the first 100 ms of the eye trying to do smooth pursuit of a target in the visual field. This period of pursuit is open loop, because no visual feedback is available because of the delays in the visual system. Thereafter, visual feedback (and other sources of information) is available to close the loop, which improves performance.