The Brain, A Decoded Enigma

by Dorin Teodor Moisa

A basic functional facility of the brain is that any model can develop any of its elements as a model. Once a model activates an element, that element is able to develop itself as a model, by direct interaction with the external reality and with any other model of the brain.

Another functional facility is described here. We see that a model can activate any of its elements to develop itself as a model. But, even if an element is already developed as a model, the main model continues to treat it as an element. This important feature will be developed below.

So, a main model has an element. This element has some properties. To integrate that element, the main model uses these properties. Now, the problems could be like: "why that element has such properties?" or "how such properties can be changed?" To answer such questions, the main model has to develop the element as a model. Once an element is developed as a model, its properties appear to be truths generated by the model. So, depending of the point of view, referring to the same entity, we discuss about an element with some properties, or about a model with some associated truths.

Once an element is developed as a model, the model can be changed. A changed model will have other associated truths, so that, when treated as an element of the main model, it has another set of properties. Thus the properties cannot be changed in a direct way, but through the changes in the model. In any case, a main model can operate only with elements, regardless of the fact that the element is or not already developed as a model.

We already use terms as "long range models" or "short range models". Let's define them.

A long-range model has already been defined as a model with its own elements developed as models. But here we will prefer another alternative definition. A long-range model is a model which reaches its aims by activation and deactivation of some of its elements. Such elements are already developed as models.

A short-range model reaches its aims by direct activation.

Example: to switch on the light in a room, a ZM model will make a ZAM. That ZAM will simulate the action. Based on this simulation it will activate an AZM which, in turn, will switch on the light. The ZM-model will confirm the success of the activity of the short-range ZAM model.

Example: To travel from a place to another, a ZM will make a ZAM. The ZAM will make some ZAMs. These ZAMs will make some others ZAMs. For any specific activity there will be a ZAM. Once a ZAM has reached its aim, it will be deactivated by the ZAM-model which activated it, and a new ZAM is activated. The general control belongs to the main-ZAM. The main-ZAM can be modified by the main ZM. Long-range models do such activity.

Example: we enter a room and switch on the light. The light really switches on. A local-ZM gets this information based on IR. But, a long-range ZM, which contains the local-ZM as an element, understands that the light had been broken, and now it is on. The local-ZM acts here as a shorter-range model. It does not understand the general environment. The main-ZM (which contains the local-ZM as element) is a long-range model.