NEODES implement the equivalent of 'preload' and 'slack' in simple spring-load systems

NEODES are model neurons which store mutable state data in two cybernetically compatible ways. These two methods are analogous to 'preload' and 'slack' in simple spring-load systems.

In the first case depicted in the figure below, the spring is already exerting a 'default' force (called the 'pre-load') before any displacement occurs. In the second case, a certain default amount of displacement must occur (called the 'slack') before the load-bearing element (modelled by a simple spring) is able to react to the applied load. 

The reader is asked to imagine building a structure out of a collection of building blocks, where some blocks are longer than they are supposed to be, while others are shorter than the design specifies. The longer blocks must be forced into their place, incurring a certain preload force (assuming they 'give' a little), while the shorter blocks slide in easily, and rattle about with room ('slack') to spare.

Aside: It should come as no real surprise to us that the organisational paradigms underpinning neural circuitry are so simple and practical, they have obviously evolved from load (strain, actually) redistribution in composite solids and trusses.

This generalised model became important in the management of complex projects, by replacing the length parameter by the time needed to complete each sub-task. The method became known as the critical path method (CPM). It is not the intention of this document to describe the history of CPM [1]. Rather, the reader is encouraged to explore the similarities between the roles of the brain and a project engineer, who is contracted to produce a given result within a limited time [2]. 

Consider a standard integrate-and-fire neuron. Lets call these elements 'simple linear neurons', or SLN's. If the sum of all excitatory and inhibitory inputs to the SLN fails to reach the cell membrane potential, then the situation is analogous to the spring with slack. Further input displacement is needed before output occurs. If the sum of all excitatory and inhibitory inputs to the SLN exceeds the cell membrane potential, then the situation is analogous to the spring with preload. The neuron is producing a default output without any additional external inputs. 

Note that the slope, or gradient, of the input-output function remains the same in each case. Any network of such SLN's (which form the basis of NEODES) will behave like a hydraulic system, or an interconnected array of electrical current sources and sinks. Any NEODE which is currently idle cannot maintain neocybernetic equilibrium, due to the presence of slack. Only NEODEs which are preloaded are able to 'fire', and therefore play an active part in the maintainance of neocybernetic equilibrium.

At a lower, simpler level, a network of NEODES could balance dynamically encountered forces, just like the hydraulic actuators of an aircraft. At a higher, more complex level, a network of NEODES could compute process critical times, via the computation of the critical path, just like the operating system of a real-time computer. Both scenarios must have exerted a fair degree of evolutionary pressure on the design of animal nervous systems.

1. In 1956 James E. Kelley Jr. (of Remington Rand) and Morgan R. Walker (of DuPont) began developing algorithms for project scheduling at DuPont, building on work that had been done at the company during the Manhattan Project.

2. Karol Adamiecki (1866-1933) developed a methodology for "work harmonization" that was based on graphical analysis. The graphical charts used in this method have become known as "Harmonograms", and pre-date the similar chart work of the better-known Henry Gantt by more than ten years, and aspects of the Critical Path Method by 60 years. Activities and their durations were represented by the position and length of paper strips. In the header of the strips the name and list of preceding activities were given. see www.historicprojects.com