Associated with the above issue, I had a situation on a trek, carrying a heavy backpack, when a stone slipped from under my foot and I fell. The active models were not able to anticipate this possibility. In this case, the capacity to build a new model suitable to the external reality is reduced. As we know, PSM is activated instead. However, I am still amazed that I was not hurt during that fall (it was practically a controlled fall, but outside my consciousness). Usually, PSM tries to save what can be still saved, and it is even possible, that it will accept sacrificing an arm, to save what is more important.
Connected with this specific problem, there is also another variant that a parallel model to the main model of walking was created. This parallel model predicted that the stone will slip and built a saving model outside the line of the PSM. However the theory predicts only two lines: one of the PSM and one of the ZAM which controls the global activity. Possibly, the ZM could let the main ZAM act, and build in parallel other ZAMs models for new situations, which would be activated in special cases. This type of behaviour is not specifically excluded by the theory, but in reality it is not met sufficiently clearly, so that it can be sustained. Building a parallel model is an easy operation, but the question is, how does the main ZM know what other ZAM to activate, when the active ZAM does not correspond anymore. The implementation of this facility could be done if there were a 'pipeline' built by the main ZM, so that a specific order of activation of parallel ZAMs existed in special cases. But this would imply the existence of a new hardware. As I already said, the existence of this facility (pipeline of ZAMs) cannot be sustained yet, due to insufficient data, but could be a line of further hardware development of the brain.
The issue of walking, jumping and running is inimaginably complicated and I do not believe that in predictible future, robots will come close to the performance of a chicken a few days old, running on a difficult terrain.
Climbing trees is an even more complicated activity, than walking and jumping. The basic information is related to the lack of precise information about the resistance of the branches. The models are able to make an evaluation of the resistance of each branch, but the model will have enough simulations in which the branch will break. ZM will need to take this into account, based on various local models, in order to build a good strategy (the best ZAM reactualised very often). In this case, the stability in the tree will be given by the capacity of building alternative models, which could be activated, if a branch broke. The brain effort needed to ensure the stability of the person in a tree is huge. Not all brains have this capacity. Moreover the ZM should also build a 'saving' model, in which there should be at least three points of support at any moment, in the ideea that if at least two will behave as in the simulation, the system will have an acceptable level of stability.
Walking on a difficult terrain, jumping and the stability in tree climbing are tests, which can show global performance of humans in the domain of image models. In animals these functions can be even more efficient.
ETA 26: The brain evolves under our eyes.
Generally all ETAs refer to the behaviour and evolution of the brain of a normal average human.
In 1900 Quantum Mechanics appeared. It marks the highest level attained up to now, in the brain evolution. However, people, who reached this extreme advance of knowledge, are ordinary people in everyday life. Independent of the level in the professional field, in everyday life, the brain continues to act to a large extends based on image models.
I have an example, in which one can see clearly, and above any doubt, the evolution of the brain towards more and more advanced symbolic models, at the level of the common person, in an issue always associated with image models: nutrition.
In all times, people have eaten based on analysis on image models. Associated terms to nutrition are taste, smell, colour, aspect etc. The decision to eat or not a certain food, is based on image models. It can be said that the whole being, with its whole structure, participates at solving the nutrition problem.