Let's consider that an M-model transmits no information (e.g. our eyes are closed). A local-ZM takes the information from that M-model. Because the M- model transmits no information, the ZM must receive no information. What is really received is called NULL-model. For a normal brain, in the above condition, the local-ZM must receive a completely dark surface. What is really received is an indication about the overall status of the brain. For instance, in the above conditions, we can receive a dark surface with some randomly moving points. That is, the local-ZM detects a bright point in a place, but at the second scan the point is not there anymore. This means that there is a noise, but no important hardware problems. A stable image is generated by a hardware problem of M or ZM models. Application: In the first seconds after wake up, with closed eyes, look towards a moderately bright surface. Usually, one should perceive a dark surface full of grey points moving randomly. After a few seconds, the surface becomes a uniform dark-grey one. This is a typical situation for a brain in a normal status. It is also possible, in the first moments, to see big bright points or shapes, moving randomly. They evolve to dark and small grey points, and then to a uniform grey surface. In such a situation, the brain is not in a good shape (maybe the person did not sleep enough...) Anyways, if the final status of the NULL model is a uniform grey surface, the brain is OK. This case has been illustrated for the eyes, but NULL models exist for all senses. ETA 6: Time Excepting when specified otherwise, the subject is the same for human and animal beings. Based on MDT, time is not a parameter for the functions of the brain. This is a basic deficiency. But there is a problem: as the brain predicts on and on the evolution of the external reality, how often is this activity done? Of course, this problem is associated to the technological implementation of every type of brain, so it is outside the field covered by MDT. Even so, based on MDT, we can make some assumptions. Because the brain is an optimized device as to its energy consumption, we assume that the predictions about the evolution of the external reality are done at a speed which depends on the changing speed of the external reality. That is, the brain time flows with variable speed. This is also our feeling based on our own experience. For instance, when we are involved in a complex activity, time seems to flow too fast and when we have nothing to do, time seems to flow very slowly. This is a big design drawback. Without time, the long-range models could be inefficient or unusable. So, the brain is forced to compensate, somehow, this drawback.