Computational Elements

The rate of change of the chemicals building the brain, which cause the generation, and transmission, of the electrical signals within the organ, guides the flow of the signals, and forms the structure of the neural networks that are responsible for the computational power of the brain.

The computations result in one absolute conclusion, and many relative ones. The absolute conclusion is the more, or most, global conclusion(s) computed, after the process of the data, on each group level.

Groups: Different sets of (received or stored) information, and the respective networks responsible for processing them.

Stronger conclusions are made on more global scales. The different groups of data, the different networks which process them, and the relationships among the networks, determine the nature of these more global conclusions.

Hypothesis

There maybe a 1000 reasons why people believe in anything they believe in, or have believed in throughtout the history. The distinctiveness of the reasons does not have relevance to the fact that they are causes which map future effects, and outcomes, based on real-time past and present data.

The beliefs give birth to actions, decisions, and new beliefs. The results are stored in the live matter inside the brain in forms of groups of networks which together help compute and process the data it stores and receives on a continuous basis. The networks are governed by electro-chemical reactions, therefore, the level of the chemicals constructing these reactions, their rate of change, becomes of significant computational value. The reactions are enforced and executed on molecular, and even atomic levels. The true nature of the rules of these levels is not of importance to the study of human life and behavior.

Neural Processes:

If the focus of the process is to achieve a certain state, to cycle around a certain point of importance, choosing weights which would result in values close to the target value would be desirable in designing the process algorithm.
Could the effect of these assigned weights be considered "neutral" in the sense that their values do not end up causing too much fluctuations to the either end of the spectrum in the final results?

They are still actively engaged factors even if they are essentially neutral.

A: In the practical continuous analysis of such a system, that definition of neutral essentially depends on the assumed range of the weights. The ranges which cause drastic changes in the behaviour of the system can never be considered "neutral" unless, of course, neutral is defined completely different in another language.

The last sentence remains valid.

Employing neutral decision-making processes will result in better target achievements in most cases if one considers their true origins in cellular structure and behaviour, bio-chemical interactions and the available networks, and how they connect to each other.

... The way the brain can dynamically, but not efficiently at all, grow and change through simple repeating algorithms, to fulfill certain purposes, and to communicate with the outside world.