On The Origin Of Experience: The Shaping Of Sense And The Complex World

Filling the theoretical gap

A gap exists in the theoretical explanation of contemporary biophysics. No account is provided for sensory experience and the role that it may play in the formation and operation of biophysical structure. It is my purpose here to fill this gap.

This book presents a scientific explanation of “experience” in nature. It explains how sensing biophysical structures, like you and Ioriginate to become a part of the rich and complex evolving world.

“Experience” is that which is most familiar. It is common to all of our senses. Because it is so present, immediate, and constant we have developed a variety of ways of speaking about it. We often refer to our immediate experience as “consciousness” or “the mind.” Perhaps its basis is what people refer to when they speak of “the spirit” or “the soul.” Some suggest that it is distinct from the body, even that it may leave the body and survive death.

Most of us will at least consider that our experience defines who we are: it is our existence, our “self.”

Yet we all recognize that the form of our experience changes as our body changes, and we are reminded of this in sickness, trauma, and intoxication. But how are we to explain this relationship between our body and our experience, between our body and "our mind?" Does experience play a role in the determination of our physical behavior or is it merely along for the ride?

Long standing questions

Surprisingly perhaps, for a work of science, we will suggest answers to these and other long standing questions. The more popular of these include: What does it mean to be alive?  What happens to our experience when we die? How did all life begin?  

Some less popular questions, but more useful perhaps, are: What is "thinking?" What role does experience have in the formation and operation of the body? How is a particular sense constructed and how does recognition combine these particulars to lead to directed behavior?

A role for experience

I will present the view that whatever the basis of experience is it necessarily plays a role in the world. It does play a role in the determination of our physical structure and its behavior. Indeed, the basis of experience plays a fundamental role in the formation and action of the complex "living" world

The character of sense

Our senses each possess a unique “character,” a differentiation of experience. Our sense of smell, of touch, our visual sense, and so on, each have a form that distinguishes them. That form exists in the dynamic structure of our body. The body literally shapes how we feel.

Individuals

Each of us, as a structure in the world replicated by the power of genetics, is the product of this same mechanism in the large. We are an individuation against this basis, formed by these same mechanisms and evolved toward an ever richer characterization of sense.

This shaping of sense and the variety of behaviors associated with it are the subject of our book: How sense first comes to be in the world. The role that it plays in the formation and operation of individuals. The mechanisms that characterize our experience. And how this mechanics operates in order to turn this “shaping” into what we refer to as “thinking.” 

Machines that experience

I explore how we may use this new understanding to inform our models of computation and to create a new type of machine, machines that can solve problems that we could not solve before, machines that experience

 

"On The Origin Of Experience: The Shaping Of Sense And The Complex World" is a single volume written for a general audience, authored by Steven Ericsson-Zenith and published by IASE. Scheduled for release April 2012.

EXPLAINING EXPERIENCE IN NATURE: THE FOUNDATIONS OF LOGIC AND APPREHENSION

Three theories

This work is concerned with the development and operation of sentient biophysical structure. The vehicle of our inquiry is an investigation into the foundations of logic and apprehension with respect to the mathematical characterization of such structure, its behavior, and its computable reproduction.

Three related theories are presented: The first of these provides an explanation of how sentient individuals come to be in the world. The second describes how these individuals operate. And the third proposes a method for reasoning about the behavior of individuals in groups. By extension our inquiry brings together the traditional concerns of cosmology, computation, and epistemology.

Underlying this investigation is the broad range of contemporary biophysical observation and experimentation. Much of this observation and experimentation was impossible before the current era. The results are voluminous and often narrowly specialized. Theorists have, as yet, had little time to consider the broader implications.

These theories are based upon a new explanation of experience in nature, the construction of senses, and the operation of spontaneous biophysical behavior. This new approach is developed from first principles to enable a rigorous and systematic explanation of the variety of associated behaviors. 

The nature of our inquiry

Alongside this development is a further inquiry that focuses upon the nature of our work. It discusses the existential aspects of scientific inquiry, its epistemology and logic. It seeks to clarify the nature of the mathematical characterization and computation of natural behaviors, dealing with questions in the foundations of logic. It explores methodological issues related to reduction and the refinement of ideas from intuition to formal logical structure.

This second inquiry is the necessary complement to the first because it is an explanation that deals with its own foundation.

A calculus for biophysics

In support of this broad inquiry we work toward the development of a calculus for biophysical construction and its dynamics. The focus of this calculus is the structural dynamics for the range of single cells, multicellular architectures, and membranes. In our model it is the shape of these biophysical elements that characterize sense and modify action potentials producing motility, if successful this mechanics mathematically characterizes sensory and motile behavior.

Upon this foundation we propose a model of apprehension and explore how its products are processed by the organism. Finally, we propose  a probabilistic theory that enables us to reason about inaccessible factors in group behavior.

Three mathematical approaches

We follow three mathematical directions in anticipation that they inform each other. The first of these is the simple assertion that the basis of sense and spontaneous biophysical action is universally present and by this simple presence structure assembles against it. This approach can only serve us if the mechanism characterizes a structural dynamic that is a consequence of this presence. The second direction is more conventional and follows a similar line of reasoning to the first except that it suggests the mechanism is the result of a covariant field effect upon the geometry of closed structures.

The third approach is radical and a purely mathematical exploration. It argues that the effects we seek to characterized have a natural mathematical basis and that if we eliminate naive assumptions concerning apprehension from a logical geometry then a characterization of the effect will suggest itself.

Rejection of emergence theory

You will note immediately that our approach is differential upon closed smooth manifolds and not founded upon a discrete particle theory. This is due to a recognition that neither construction from atoms nor the magic of emergence are viable existential explanations of our continuous and unfied experience, of sense.

A new computational mechanics

The mechanics we propose suggests the design and physical realization of a new model of computation; one in which structure and the concurrency of action are a first-order consideration. Symbolic processing in the biophysical system is storage free and the capacity of symbol representation is combinatorial across dynamic sensory manifolds, suggesting general engineering principles that offer significantly more symbolic processing capability in biophysical architectures than previously considered.

Proof in practice

We identify opportunities for experimental verification of the theory and we suggest a proof of our results in practice by the identification of this mechanism, allowing the construction of machines that experience.

 

Explaining Experience In Nature: The Foundations Of Logic And Apprehension is a series of technical volumes authored by Steven Ericsson-Zenith and published by IASE. Available by subscription.

Computing With Structure

Two opposing views concerning the nature of Logic will concern us.

The first, represented in the variety of models of computation considered by Alan Turing[1][2], is the view that Logic is the integration of symbolic elements, where each element is an independent discrete value and the logical mechanism is one of conditional integration of these values in specialized, configurable, or unorganized machines, the state of which may be discretely stored and reloaded.

The second is the view, suggested by Rudolf Carnap[3], that computable Logic is "differentiation from the entirety of sense," in which symbolic elements are continuously bound by the originating whole, they are products of this differentiation.

A concise and general way to state this distinction is that the Turing view of the nature of computable logic is the integration of the parts and Carnap's view is the differentiation of the whole.

Our goal here will be to show that these two views, and the realizable mechanisms that they represent, are distinct and that their operation produces different results. In particular, the Turing models represent a metaphysical view that has no capacity for the "basic relation" of Carnap, the "recollection of similarity" (recognition), and results in prohibitive storage and value distribution requirements.

We will propose realizable mechanisms based upon the second of these models for the reproduction of this mathematical character that closely bind the state of logical expressions and response potentials.

We suggest that these mechanisms are observable in nature and that current "connectionist" interpretations of this behavior are false. For this reason so-called Neural Networks, the "unorganised machines" proposed by Alan Turing, necessarily fail.

Considering contemporary computing machinery, parallel computation as we understand it today is decomposable, a second order consideration of the Turing model. Parallelism can be semantically removed from computer programs with no discernible effect upon the results. Therefore it contributes nothing algorithmically, providing only performance semantics.

Putting aside for a moment the challenges of the recognition problems, well-known data storage and distribution issues limit the engineering of efficient large scale algorithms on parallel machines. Without transparent data movement expressing these algorithms for execution upon these machines may be intractable at the scales we now consider.

Yet after two decades of detailed investigation with new technologies the evidence shows there is no storage architecture independent of symbolic processing in biophysical systems. Biophysical behavior is broadly cooperative and concurrent. But there is no load/store architecture and recognition operations are low cost. Overall energy requirements are, in effect, independent of processing utilization.

Contrary to the view of earlier paradigms, the electrical behavior seen in neurons is best considered for its non-isolated participation in the dynamics of neurological and broader cell structure. These structural dynamics are closely bound to response potentials in complex electrochemical behavior. We present examples.

In biophysics then it is structure and the concurrency of action that are first-order considerations. It is the shape of single cells and multicellular membranes ("closed manifolds" in mathematical terms) that characterize sense and modify response potentials that produce behavior.

A generalization of the existing evidence suggests that symbols form directly upon the surface of these manifolds in cell and membrane architectures, the processing of which constrains biophysical action potentials1 associated with the structure. This close binding of symbol processing and response potential is naturally formed by the evolutionary process.

Symbolic processing in the biophysical system is profoundly efficient. Storage is free and the capacity for symbol representation is combinatorial across dynamic sensory manifolds. This simple efficiency suggests general engineering principles that offer significantly greater symbolic processing capability in biophysical architectures than previously considered.

In biophysical systems structural parallelism is not decomposable without impact upon the results. It plays a role algorithmically, providing the mechanisms of recognition and memory in the surface conformations of the processing architecture. Large scale differentiation appears in the dynamics of these closed manifolds and result in measurable characteristic behavior suggesting new architectures for identification and prediction

It should be clear that these claims concerning parallel and symbolic processing in biophysical architectures, independent of a complete theory including sense, have merit and are readily verified. As presented, no new physics is required to accept the biophysical evidence. However, as we discover the details of this mechanism a broader physical theory may be required.

Experimental verification will suggest manufacturing techniques promising technologies that can leverage advances in biotechnology and provide fundamental advantages over current large scale computing architectures.

A research and development effort of modest size is required to verify these claims and to validate the investment required to advance the technology. If the model holds, genuinely new devices implementing these "symbolic processing surfaces" could be available within 10 years.

To effectively construct such machines we require the development of a new computational logic, one that deals with structural conformation and related action potentials. We will outline our first steps toward such a logic. This approach suggests a new pragmaticist foundation for logic (and potentially a new mathematics to be built upon it) since it eliminates the integration of traditional truth values in favor of symbolic differentiation upon closed manifolds and the transformation of the associated structure.

 

The above is the conference abstract for "Computing With Structure," an academic paper authored by Steven Ericsson-Zenith and due to be presented at the Isaac Newton Institute's "Incomputable," England, June 2012.
http://www.mathcomp.leeds.ac.uk/turing2012/inc/

 

Notes

1 : ... action potentials ...

"Action potential" here is not to be interpreted as the electrical potential of "connectionism". The action potential we refer to is mechanical and responsible for the motile action of biophysical structure.

References

[1] Turing, Alan. On Computable Numbers, With An Application To The Entscheidungsproblem. (1936).

[2] Turing, Alan. Intelligent Machinery, A Heretical Theory. (1951).

[3] Carnap, Rudolf. The Logical Structure Of The World. Open Court (1928). ISBN:0812695232.