The Biological Basis of IOPT Measurement

By: Gary J. Salton, Ph.D.
Chief: Research & Development
Professional Communications, Inc.


INTRODUCTION

An organization is an entity—a thing. It is built of people assembled for a common purpose. That “thing” can be measured with varying degrees of accuracy. More precision means deeper analysis and greater accuracy.

“I Opt” technology is unique. It can access to the highest level of measurement—a ratio scale. It can do this because of the time and attention that was devoted to figuring out how to access the brain’s guidance system directly without the need for using psychology as a go between. A simple ruler can be used as a touch stone to explain how “I Opt” measurement system was developed and is applied.

Graphic 1

                                      THE BASIC CONCEPT

 CREATING A ZERO

The beginning of the ruler is the zero point of the scale. Without a zero point you cannot use division and multiplication. For example, no tool can tell that a person is 30% introvert. This is because the scale (Myers Briggs Foundation, 2019) has neither a zero base nor equal increment scaling.

“I Opt” technology is unique. It has both a zero point and equal interval scales. It can use entire range of math tools including division. It can do this because has developed methods of directly accessing the information processing capacities of the human brain. Graphic 2 is a visual representation of the model.

Graphic 2

BASIC INFORMATION PROCESSING MODEL

The simplest argument for a zero point is that a “no information” condition is possible. For example, in deep sleep. No information input means that there nothing to process. The model literally disappears as a part of the brain function. The absence of the thing being measured is the definition of a zero condition.

Nomological Net is a tool for establishing content validity—one of the eight validity dimensions. It traced each of the 96 “I Opt” statements back to the basic model. A total of 87.5% of the survey responses could be directly tied to the model. The 12.5% balance was tied back to the model by explicit inference (Soltysik, 2000, p.19). This result evidences the direct relation of “I Opt” to information processing.

The input and output parts of the model are the measurement points. Input is measured using “method.” This is the form that the input takes. It is a continuum. It ranges from “unpatterned” on one end to “structured” at the other. While the two variables exist on the same dimensional plane they are not opposites. Rather they are alternatives. For example, food input might be arrayed on a calorie scale ranging from eggs (~75 calories) on one end to hotdogs (~150 calories) on the other. They share a caloric content while being alternative foods.

The “I Opt” method unpatterned and structured alternatives are mutually exclusive. The use of one excludes the other. For example, behavior can strictly follow some predefined format. With no unpatterned element the “unpatterned” variable is zero. Similarly behavior can be completely random in manner and the “structured” end would be zero.

The concept of mode governs the output and is a continuum that ranges from action on one end to thought on the other. The variables are alternatives but here the use of one does not preclude the other. But the zero value base of output is not lost. The fact that action and thought can exist together does not mean that they have to. It is possible engage thought to the exclusion of action—a zero action condition. Similarly, action can be so all consuming that it precludes thought—a zero thought condition.

“I Opt” technology clearly has a zero level both in total and on its input and output components. The ruler has a zero level beginning. This gives it access to all of math including division. The next step is to establish that the ruler has an end point.

FINDING THE END OF THE RULER

Ratio measurement has no theoretical limit. However, human information processing does have limits imposed by society and ultimately by biology. Those limits can be seen through the lens of the “I Opt” variables.

Method governs the input side of the model with unpatterned selection at one end and structured at the other. The limit of input is that without a guiding structure attention can shift minute to minute. Carried to the extreme the frantic behavior mandates residence in a mental ward. This condition actually has a psychological designation—“attentional distraction.”

Similarly, the maximum degree of structured input causes behavior becomes robotic. Psychology’s obsessive-compulsive disorder might be an example of the character of this condition. Input is restricted to predefined items. At extreme levels, the societal response is the same as for input—the mental ward residence. Thus both ends of method input ruler has an endpoint—withdrawal from the organizational matrix.

The output side is governed by “I Opt’s” mode concept—a continuum with thought on one end and action on the other. Carried to the extreme the thought option evolves into a catatonic state. When this occurs the mental ward again beckons. Similarly an unending stream of action not guided by thought creates a chaotic condition again signaling confinement to a mental ward. Extreme levels of input and output share a common end—withdrawal from society. If society did not act, biology would. If left unattended all of the conditions described would ultimately be fatal. One way or another, the human information processing ruler has an end.

FINDING THE INCREMENTS

The beginning and end of the “I Opt” ruler has been set. The remaining task is to define the steps for getting from one end to the other.

Graphic 3

SAMPLE “I OPT” SURVEY SELECTION

Graphic 3 shows the basic approach used. Individuals are quizzed as to their information processing preference in terms of the measurement variables. Not all of the survey statements are as simple and obvious as this illustration. But all ultimately map back to input and output and that in turn maps back to the basic model.

The statements are effectively “mapping” brain circuits. Those circuits are created by use. The more a particular neuron is engaged, the stronger becomes its connection to other particular neurons. The chain of these neural connections form into circuits—a predetermined path through a neural network. Those circuits are what determine behavior. “I Opt” technology counts the number of times a respondent chooses to use a particular circuit.

Method and mode categories are exhaustive. Anything that engages the model must register on the “I Opt” scales. Thus the 24 “I Opt” statement responses converted to percent will sum to 100%. Dividing the count of the 24 statements into 100% yields an increment of 4.17% (100% ÷ 24). That is the increment by which degrees of the “I Opt” variables can be measured. They are all equal increments because they are based on the same simple count.

A survey with more statements would allow for finer measurement. However, completing the survey is not without cost. Too long of a survey would result in people losing interest. This can lead to answering capriciously or even refusing to participate. In school room situations this may not be an issue. In field settings when the survey is being applied to fully mature individuals—some at a high organizational level—it is an issue. The 24 statement set was found to offer the best resolution (4.2%) on which to make reliable organizational development judgements without alienating the respondents. Thus 4.17% became the ruler’s equal interval increment.

“I OPT” BIOLOGICAL FOUNDATIONS

“I Opt” uses the model shown in Graphic 2. That model only works because it is a reflection of what is happening in the human brain. Input and output reflect the activity of neurons. The brain has over 100 billion cells. But the “I Opt” does not have to engage a particular neuron or group of neurons to work. This is due to the brain’s organization.

It has been known since 1983 (Fodor. 1983) that the brain is modularly organized. These modules consist “of a relatively large set of anatomically distributed regions” that are “anatomically separate” and that each plays “a unique role in cognitive control, including its implementation, maintenance, and updating” (Marek & Dosenbach, 2018). A recent issue of Scientific American cited seven identifiable brain modules base on MRI studies (Bertolero and Bassett, 2019). There are probably more awaiting discovery.

One characteristic of all of these modules is that they tend to interact with other brain circuits in a limited number of ways. It is only at certain points that input is accepted and their output is picked up by other circuits. This suggests that “I Opt” statements do not have engage a specific neuron or set of neurons to register a particular outcome. They merely have to engage the same module.

The foregoing is not proof. However, the direction of neuroscience research increasingly reinforces the “I Opt’s” tie back to the human mind. It is possible with today’s fMRI technology to actually image the “I Opt” statements as they are being processed. These images could confirm “I Opt’s” modular access contention. Unfortunately, the cost of that kind of study would be prohibitive. But just the ability to consider that kind of definitive work sets “I Opt” apart from all other assessments. It is theoretically possible to create and make sense of a visual picture of a mental function actually working on an “I Opt” variable. Who else could say that? Fortunately the strength of the validity study measures makes imaging a “nice to have” but not a necessity.

CONCLUSION

This brief summary is not a full explanation of how and why “I Opt” works. It does, however, illustrate the thought and effort that has gone into making sure its measures are accurate. That effort puts “I Opt” judgements and recommendations on a rock solid foundation. That solid foundation means that “I Opt” technology can be trusted to deliver accurate assessments and predictions today, tomorrow and 100 years from now.

BIBILIOGRAPHY

Bertolero, Max and Bassett, Danielle, How Matter Becomes Mind, Scientific American, July, 2019, pp. 26-33.

Fodor, Jerry A. (1983). Modularity of Mind: An Essay on Faculty Psychology. Cambridge, Massachusetts: MIT Press.  ISBN 0-262-56025-9

Marek, S., & Dosenbach, N. (2018). The frontoparietal network: function, electrophysiology, and importance of individual precision mapping. Dialogues in clinical neuroscience, 20(2), 133–140.

Myers Briggs Foundation, Extraversion or Introversion, Accessed December,2019: https://www.myersbriggs.org/my-mbti-personality-type/mbti-basics/extraversion-or-introversion.htm?bhcp=1

Soltysik, Robert (2000), Validation of Organizational Engineering: Instrumentation and Methodology, Amherst: HRD Press.