FIRST PRINCIPLES OF PHYSIO
INFORMATIC SYSTEMS
The conceptual, theoretical
and experimental basis for a general systems reference architecture for
Physio-informatic systems
Physio-informatics
is a new
systems model for linking human physiologic systems to information systems
in the most general way. This general systems model has been derived through an
ever evolving series of experiments and explorations.
The
conceptual, theoretical and analytical basis for establishing a general systems
based reference architecture for
Physio-informatic systems necessarily crosses many disciplines. It must be
emphasized from the onset that the
following discussion of the derivation and
development of a general model (aka.. reference architecture ) for
describing “meaningful” information
flow between humans and informatic systems is a broad topic area which covers
many scientific disciplines, engineering techniques and a continually expanding
array of technologies. Including but not limited to Physiology, Physics,
Mathematics, Philosophy, General Systems, Bio-Cybernetics Systems, Cognitive
Neuroscience, Perceptual Psycho-Physics, Perceptual State Space Modulation,
Bio-Sensors, Quantitative Human Performance, Expressional Interface Systems,
Physio-Informatics, Intelligent Interface-Metrics, User Tracking Interface
Systems, Distributed Tele-Robotic Controllers and Intermental Networking.
A
general perspective of this effort is that it is an attempt at integrating these
areas of human scientific endeavor (as mentioned above) in a manner which will
not require that future researchers in Physio-Informatics master all of them before they can
contribute meaningfully to the process of optimizing the coupling between humans
and informatic systems in an interactive interface system. Thus the intent of
this effort is to establish a general conceptual framework (a reference
architecture) which can be used as a guiding heuristic tool when
confronted with the challenge of designing and developing interactive
interface systems for human computer interaction. Specifically one which extends
perceptual dimensionality and facilitates enhanced expressivity.
Physioinformatics
A systems based, physiologically robust, reference architecture for designing and refining interactive human-computer interface systems in ways which increase operational throughput of information.
The
term“ physio-informatics” will be used in this dissertation to denote
informatic systems which are either biologically/physiologically based
(primarily neurologic i.e. neuro informatic) information systems and/or
informatic systems which are designed to support interaction (dynamic exchange
of information) with such systems
The
intent of this work is to develop a systems based, physiologically robust,
reference architecture for designing and refining interactive human-computer
interface systems in ways which increase operational throughput of information.
Extending the perceptual dimensionality of information presented to the human
and enhancing the expressional capacity of the human to convey intent to the
informatic system achieve this increased throughput.
Interactive
Human-Computer Interface Systems
In
the various traditional models of human computer it is customary to think in
terms of inputs and outputs. Input from the computer to the human and out from
the human to the computer or input from the human to the computer and output of
the computer to the human. The purpose of this dissertation is to develop a
systems model for interactive human-computer interface systems which is thought
to be more representative of reality than traditional models in that it is
consistent with the phenomenological aspects. That is the development of a
physiologic based reference architecture for designing and developing
interactive human computer interface systems to match the human nervous
system's ability to transduce, transmit, and render to consciousness the
necessary information to interact intelligently with information.
"The
physiologic basis of a reference architecture for designing interactive
human-computer interface systems"
Context And
Initial Motivation
The
capacity of computers to receive, process, and transmit massive amounts of
information is continually increasing. Current attempts to develop new
human-computer interface technologies have given us devices such as gloves,
motion trackers,3-D sound and graphics. Such devices greatly enhance our
ability to interact with this increasing flow of information. Interactive
interface technologies emerging from the next paradigm of human-computer
interaction are directly sensing bio-electric signals (from eye, muscle and
brain activity) as inputs and rendering information in ways that take advantage
of psycho-physiologic signal processing of the human nervous system (perceptual
psychophysics). The next paradigm of human-computer interface will optimize the
technology to the physiology -- a biologically responsive interactive
interface.
INTERACTIVE INFORMATION TECHNOLOGY
Interactive
information technology is any technology which augments our ability to create /
express / retrieve / analyze / process / communicate / experience information
in an interactive mode. Biocybernetics optimizes the interactive interface,
promising a technology that can profoundly improve the quality of life of real
people today. The next paradigm of interface technology is based on new
theories of human-computer interaction, which are physiologically and cognitively
oriented. This emerging paradigm of human computer interaction incorporates
multi-sense rendering technologies, giving sustained perceptual effects, and
natural user interface devices which measure multiple physiological parameters
simultaneously and use them as inputs. Biologically optimized interactive
information technology has the potential to facilitate effective communication.
This increase in effectiveness will impact both human-computer and human-human
communication, "enhanced expressivity".
"BIOCYBERNETIC CONTROLLER"
Interactive
interface technology renders content specific information onto multiple human
sensory systems giving a sustained perceptual effect, while monitoring human
response, in the form of physiometric gestures, speech, eye movements and
various other inputs. Such quantitative
measurement of activity during purposeful tasks allows us to quantitatively
characterize individual cognitive styles. This capability promises to be a
powerful tool for characterizing the complex nature of normal and impaired
human performance. The systems of the future will monitor a user's actions,
learn from them, and adapt by varying aspects of the system's configuration to
optimize performance. By immersion of external senses and iterative interaction
with biosignal triggered events complex tasks are more readily achieved. This
paradigm shift of mass communication and information technologies is providing
an exciting opportunity to facilitate the rapid exchange of relevant
information thereby increasing the individual productivity of persons involved
in the information industry. Areas such as computer-supported cooperative work,
knowledge engineering, expert systems, interactive attentional training, and
adaptive task analysis will be changed fundamentally by this increase in
informatic ability. The psycho-social implications of this technologically
mediated human-computer and human-human communication are quite profound. Providing the knowledge and technology required
to empower people to make a positive difference with information technology
could foster the development an attitude of social responsibility towards the
usage of this technology and may be a profound step forward in modern social
development. Applications which are intended to improve quality of life, such
as, applications in medicine; education, recreation and communication must
become a social priority.
An overview of the
field of interactive human-computer interface systems
In
the time between those early days and the late 70’s the ability for the
computer to respond to a task given it by a human was, for the most part,
limited by computation power. From the early days of computer programming where
each logical connection was “hard wired” by an army of technicians to the time
of punch cards, the concept of interaction with a computer had a very limited
and specific interpretation. A great advance was made when the computer had a
“typewriter” like mechanism which allowed computers to be programmed through
“terminals”. As the speed of the computer increased along with its capacity to
respond to the human, it began to become apparent that the humans ability to
convey intent to the computer and the computers capacity to display results of
its calculations to the human would become a limiting factor in the
“interaction” between humans and computers.
Innovators at Xerox PARC, MIT, NASA, DARPA and other computer research
facilities began to rethink the concept of how humans and computers would be
able to communicate more effectively. (in this context the term “communicate”
is used to mean the ability to intentionally exchange meaningful
information).The first significant breakthrough to make it out of the lab was
the “WIMP” interface (Windows, Icons, Mouse, Pointer) graphical user interface,
referred to in the nerd zone as the GUI (pronounced gooey). In the late 70’s
with the commercial release of Apple’s“ personal” computer, with it’s GUI, to
the general public …….blah..blah
In
the mid 80’s computer systems used by industry were becoming fast enough, and
display technology and was becoming sophisticated enough to be able to “render”
graphic images for engineers in computer aided drafting and design jobs to be
able to begin to manipulate these rendered images with ever increasing speed
and resolution. At the same time new techniques were being developed by
scientists to enable them to “visualize” a graphic image that was the result of
a very complex set calculations. These new areas of CAD/CAM and scientific
visualization continued to evolve with faster and faster computation and ever
increasing quality of graphic images.
In
the late 80’s it was recognized that the compute power and graphic display
techniques
While
it is true that there was much work was done in the human factors of “Man-Machine”
interfaces throughout the late 70’s and the 80’s, this work dealt with the
physicality of the environment and information displays, and much of that work
was done in the context of very specialized tasks. Tasks for specifics kinds of
work such as piloting fighter airplanes or space craft, controlling complex
industrial processes such as nuclear power plants, or complex chemical
processing plants were well studied and refined. However these task differ from
interactive human computer systems in that the humans are controlling some
machine or physical system and were not primarily interacting with information
as represented by computer systems. (one exception to this would be the
interaction with a computer simulation of a complex physical system). The primary
efforts for researching and refining these systems were in the field of
ergonomics, dealing with the energetics of the human interacting with their
environment, and cognitive science, the mental computation required to perform
effectively in the environment.
Also
in the late 80’s a new concept began to take hold in the field of human
computer interaction, the concept of “immerse systems” where the computer
systems began to encompass the humans senses and track the movements and
position of the human in an effort to develop a synthetic environment with in
which the human could interact in a more natural way. These virtual reality
systems sparked a brief but important revolution in the thinking and gadgetry
of human computer interaction. From an evolutionary neuro-information
processing perspective this technology creates a new potentiality for response
to perceptual awareness: it canalizes not a single response to a single
stimulus, but rather multiple responses to multiple stimuli born of a single though
multi-dimensional sensorial perceptual state. the combination of these
different rendering modalities with somatotopic placement, in order to achieve
and demonstrate spatial coding of the rendered information. Optimizing the
human computer interface will rely on the knowledge base of physiology and
neuroscience, that is, the more we know about the way we acquire information
physiologically the more we know the optimum way for a human to interact with
intelligent information systems. The next paradigm will see the
"THINNING" of the human-computer interface to a biological sheer as
the interface will map very close to the human body.
PHYSIOLOGICALLY ORIENTED INTERFACE DESIGN
Knowledge
of sensory physiology and perceptual psychophysics is being used to optimize
our future interactions with the computer. By increasing the number and
variation of simultaneous sensory inputs, we can make the body an integral part
of the information system, "a sensorial combinetric integrator". We
can then identify the optimal perceptual state space parameters in which
information can best be rendered. That is what types of information are best
rendered to each specific sense modality, "a sense specific optimization
of rendered information. Research in human sensory physiology, specifically
sensory transduction mechanisms, shows us that there are designs in our nervous
systems optimized for feature extraction of spatially rendered data, temporally
rendered data, and textures. Models of information processing based on the capacity
of these neurophysiological structures to process information will help our
efforts to enhance perception of complex relationships by integrating visual,
binaural, and tactile modalities. Then by using the natural bioelectric energy
as a signal source for input; electroencephalography, electroocculography, and
electromyography (brain, eye and muscle) we can generate highly interactive
systems in which these biological signals initiate specific events. Such a
real-time analysis enables multi-modal feedback and closed-loop interactions.
The
following discussion is concerned with developing a “reference architecture” (a
formalized conceptual framework for thinking) for designing physiologically
robust interactive human computer interface systems. The purpose of the
reference architecture will be to provide insight into the various components
of the system in the context of how they might affect the flow of information
as information is passed through them The primary focus will be to consider the
flow of information between the human and the computer in a sustained,
iterative, experiential interaction In the context of this dissertation it will
be assumed that the intent of developing this reference architecture is to map
the information flow during/caused by the intentional /volitional interaction
with information between a conscious human and a computer system An exchange of
information between the an experienced perceptual state and an external
physical state is mediated by a biologic / physiologic information transporter
system This system is multi modal – multi scale – concurrent hetero-purpose
poly-dyno- morphic simul-tasking
For
this discussion we will assume that interface systems which support Human
computer interaction can be modeled as a system where information flows between
various components of the system in a specific manner
Theoretical position –
Information can be mapped and represented as a specific state space parameter set.
Universe of
discourse “Mind happens at an anthroscopic scale.”
The
phenomena of interest, (perception and expression), occurs at the anthroscopic
scale.
The
anthroscopic scale, the natural scale of perceptibility and expressivity of an
individual human, is “From meters to millimeters, from decades to
deci-seconds.”
Assumptions
Time
is perceived as a unidirectional vector.
The
nervous system is the primary information infrastructure for humans.
The
nervous system supports the transduction transmission representation and
response to information in the environment.
Basic
principles.
Human
perception and expression is mediated, for the most part, by the nervous
system.
Hypothesis
An
understanding of the human neuro physiology allows for exploitation of
predictable adaptive capabilities. The assertion is that the information flow
between external sources and direct experience is
biased/restrained/constrained/limited/enhanced/facilitated in understandable
and predictable ways by the physiological mechanisms of human information
processing.
Physio
info metrics
--- the quantitative measure of the information carrying capacity of a
physiologic system.
Physiologically
mediated information is exchanged between external environment and experiential
awareness. The fundamental nature of the nervous system (neuro info matrix)
determines its operational capacity. Both the physicality and the physiology
contribute to the set of bio-physical restraints. The physicality of the
nervous system constrains the perception of space, time, mass and energy.
Physiology of the human nervous system restrains perception by computational
limits of the system. The complexity, functionality and capacity of the
intra-activity of the nervous system sustains perception. ERGO - The form and
function of the nervous system influence various parameters of perception and
expression. That is to say that nervous system is the biologic structure that
is considered most likely to be responsible for mediating information flow
within the human body
The
Basic ideas leading to the primary foundations for this thinking can be seen as
coming from the following areas
Operational Philosophy
-Action
directed goals in the pursuit of new knowledge - which start with logical
analysis of observed phenomena and
proceed to the point of discerning an operational utility of continuing the
pursuit in the current mode of analysis or changing modes to seek a more
fruitful mode of investigating the phenomena. (Oppenhiemer)
In
other words it is a philosophy of scientific investigation which constantly
seeks to validate the current mode of analysis for a given set of observed
phenomena so as to maintain constant progress in the discovery process of new
knowledge.
General Systems Theory
General
systems theory is a useful framework for developing complex models for
investigating complex systems, like those of Physio-Informatics, is in as far
as it has certain concepts of systems models and principles such as
hierarchical order, progressive differentiation and feedback that can be defined and characterized and elaborated
on with set and graph theory which state explicitly conditions for membership
and orders of relationship.
The
“open systems” approach to a general systems theory by von Bertalanffy in the late 1930’s was instigated by a
perceived need to break out of the “closed systems” model which implicitly
separates the system from its environment, as it would lead to incorrect
conclusions. His concept was that biological systems necessarily must be
considered as being open systems where both information and energy is in
continuous flow between the system and the environment. His initial formulation
of a general system was an attempt to derive principles which were valid for
open systems.
A
system can be defined as an object consisting of a set of complex objects or relationships, each of which are in
some way associated with other objects with in the system in a way that some
quantities (parameters) with in those objects are associated with quantities
(parameters) of other objects within the same system.
(
von Bertalanffy)
Information
The
base elements with which information is constructed is “difference”. A difference can be interpreted as either an
ontological fact or as an abstract matter.
Information can be defined as a difference which makes a
difference. (Bateson 1970) Or a difference with a non zero significance
(Warner)
The
relevant aspects of Information Theory concerning the transmission effects
on information across physical
structures, are considered to be important in physio-informatic systems, but
are tempered by the fact that biological systems do not adhere to the neg-entropy formulation of Shannon
Cybernetics
Also
of significant importance is theory of Cybernetics, the theoretical model of
feedback governed systems whose present state influences in some way the
probabilities of any future state occurring in the system. It is interesting to
note that the operators which are invoked on the system are a result of past or
currents states. This is important to establish that there is a relationship
between operators and states beyond the “transformational function” of
operators on states.
Definitions
A
state of any system is defined by the set values which describe the condition
of the system in any given point in time (the value of all the state vectors).
A system will have a state space which represents/contains all possible states
of that system.
State Space, States and Operators
For
those systems whose quantities are in continuous flux a special kind of set
called a “State Space” can be constructed which has as its elements (set
members) an n-tuple of values which are the values of the quantities at a given
instant. At any given instant the system is said to have a “state” which is
determined by the values of each of the “parameters” at that instant. (Ashby,
Zadeh)
For a given system whose States are not static (in time) within a given state-space it can be asserted that a transformational function has been performed on the system which determines the “next” state the system will be in. Such a transformational function is called an operator. Thus it is correct to say that an operator acts on an initial state parameter value and produces a new state parameter value.
In
an open system is can be asserted that the “evolution of the states in time”
i.e. the “state space trajectory” can be considered to be influenced by both
the current state of the system (internal factors) and the processes of the
environment (external factors) which are acting on the system.
States Operators and Information State-Spaces
A strange but useful mathematical modeling system for elaborating this has been established. A state space of a physio-informatic system can be described as a set of information-based states which behave in a particular manner.
The initial assumption is that all the information that is perceived about the external environment is filtered-mediated-biased by the nervous system. This is known as the “Neuro Cosmological Principle” of epistemology, which has an “Anthro-scopic scale” and an “Anthro-centric perspective”.
Expression Space - is a universe of discourse within which the physical and mental realms are complimentary subspaces.
The following discussion is
concerned with the development and elaboration of
The notation system for
mapping the flow of information in any physio-informatic system
The formal term for this is
“Expression Space Notational System”
“NEUROCOSMOLOGY”
A notational system which enhances the ability to see
differences
ANY information which can be
expressed is a member of Expression space.
Neuro-cosmology is a
notational system which has as its prime focus the flux and flow of information between a perceiving human being an
the environment. As such Neuro-cosmology has :
-A
superior descriptive process
-A
powerful system of methods and models
-A
superior conceptual frame work within
which to map info flux
-Derivational
pathways from first principles to operational systems
-Intrinsic heuristics
Assertion
The
nervous systems capacity to transduce, transmit, characterize, experience and
respond to information of environmental conditions limits the know-ability of
the environment. The anthroscopic neurophysiologic info matrix
supports/provides the basic infrastructure for the continuous
intentional/willful interaction with the environment. Biologically mediated
information exchange couples perception to the environment. The physio info
metrics of the neural info matrix determines the through flux. The exchange of
that information can be abstracted. The flow of information can be
parameterized by temporal, spatial, ergo-dyno-morphic flux. Any state of
information is characterized by a specific state-space parameter set.
Theoretical
construct
A
descriptive mathematical model that can map the transformation of information
as it is exchanged between various components of the interactive human-computer
interface system is presented below. This model which most generalizes the
phenomenological aspects has a notational system which exploits
interdisciplinary interaction and a languaging system which can classify
emerging observations.
.
Neurocosmology-
Anthroscopic epistemology is biased by Neural systems
A notational system has been derived which
represents the flow of information between the environment and the neurally
mediated experience of consciousness. This formal descriptive notational system
will enable the creation of“ most probable maps” of information flow between
humans and their environment.
|
A set can be defined
--Expression space is characterizable
Definition ANY expressible
information is in Expression space
|
|
An expression of any
experiencable information is a member of E-space ANY state of information which is experienced
and expressed |
|
The minimum element of
resolution is a the existence/experience of a difference
To have a non zero
information content a noticeable difference with non zero significance needs
to occur |
|
The minimum element of
information is a significant difference
IT is a difference between
ANY 1 and ANY other IT is the information
trajectory which relates ANY state of
information IT is an expression space
state path |
It
should be noted that the following formalisms will be loosely followed.
Set theory – where membership to a given set is
determined by some formal means
Graph
theory – where the position and relationships are determined by intrinsic
values
Given
the dynamic nature of physio-informatic
systems
A
more general system of States and Operators will be pervasive.
In
the course of systematic reflection upon those fundamental essences which
appear to be ontologically distinct primary percepts, one may construct a sound
and verifiable epistemology with a triad of categorical types. That is, if one
is to separate the "WORLD" as perceived into categories which are
characterized
phenomenologically rather than by the material constituents
with which it is constructed, one finds that there are three principle realms
which may act in concert and in various combinations to account for the whole
of perceptible "reality". These three categories are Experiential,
Biophysical and the Physical, more commonly known as MIND, LIFE and MATTER.
Consider
a complex system that has as its primary components 3 fundamentally distinct
sets of parameter values. Or three “state spaces” a state space is a set whose
members are defined by an n-tuple of values which correspond to the parameter
values of One set is a set of parameter values of a computational system.
Another set is a set of directly measurable parameter values of a physiologic system.
The third set is a set of parameter values which are directly experienced by a
conscious human. Each set is distinguishable from the other in that the
computational system and the physiological system are physically separable and
the physiological and perceptual state space are phenomenological. It is
acknowledged that the basis of perceptual experience is most probably supported
by a specific set of physiologically distinct systems. It is beyond the scope
of this dissertation (and frankly unnecessary) to develop a robust
explanation/model for the specifically/physically distinguishable aspects of
conscious experience (the mind) and assumed neural matrix (the body) that is
thought to at least co-occur with those conscious experiences. Suffice it to say
that a user in the context of an experiential interaction with information does
not routinely confuse the two.
|
Expression-space
|
|
Mind subspace
C-term [] C-term is the
mind-space operator. C-term is the
operation which changes one mind-state to another. There is an implication of conscious attention in a C-term
operation. When one instance of
couscous perception intentionally and willfully affects the generation of a
specific type of mind-state then this is considered a C-term operation |
|
Biological subspace
B-term [] B-term is the generic bio-subspace operator. B-term changes information states which
are directly linked to the biological
/ physiologic information processing functions. Any process which is achieved by a living
organism is a B-term type function. |
|
Space-time
Z-term [] Z term is a
generic space-time operator. This is
a function which accounts for all the physical (non-biological) changes in
information states in the physical subspace.
Z-term functions are those which the physicists and other physical
scientists study. They are things
like electricity, magnetism, gravity, thermal dynamics, etc. In general, anything with just physical
properties is a Z-term function. |
This
is the subspace of E-space which contains all the information states directly
perceived by the mind.
Now with these terms in mind (pardon the
pun) the next step is to specify the format or syntax of a valid expression in
Neurocosmology notation. The general
form of a neuro-cosmology expression is in the form of a commutatively diagram,
and it looks something like this:
All
instances of information from the physical subspace to the mind subspace will
be in this form, where PHI is the
object as it exists in space-time, Z-term is the information of the object
being transmitted through physical substance via light, sound, smell etc. PHX is in this instance the composite of all
the intermediate biologic information-state spaces necessary for information transduction
(i.e., sensation). This was comprised
of no less than stimuli, transmission of sensory output and neurological
processing and coding in the brain.
B-term is the process of sending (transmitting) the final product of
sensation to the mind for the purpose of perception. It is an axiom of neuro-cosmology that this expression in the
form presented above is both a necessary and sufficient condition for an
instance of perceptional experience to have in it an
information
content which was assimilated from an external object which did in fact exist
in the space-time realm (there is a world external to our senses!). That is to say that all the information we
have about the outside world was obtained in this way. If it hasn't occurred to you yet it may be
easier to use the following approximation when doing Neurocosmology
PSI
= the self perceiving mind--perceptual space: contents of awareness
PHX
= the living body -biological space: what chemistry refers to as
"organic" and all things related to it.
PHI
= objective, material, space-time reality --physical: what physics refers to as
space, time, mass, energy
Thus
any information that can come into being is one of 3 categories or combinations
of the 3.
The following is a list of all the major
state-operator-state expressions required to map information flow through the
physioinformatic system.
Neuro
cosmology states that basically that
perceptual states are a result of a brain state. However perceiving a uniform, coherent perception at
any given time, the state of perception, at ANY given time is called PSI, an
instant of perception which is all we ever have. Information coming from the
outside, causing neuro structures to fire on the sensory cortex is sensation.
The brain correlates that sensation with all its other relevant internal
functioning and all layers of psychosocial elements and the gestalt of all
brain function in consciousness equals perception.
ANY
contains a subspace of possible expressions; everything I could possibly
perceive is herein contained. Rather than matter and energy we're referring to
perceptual state-space. The perceptual state is always related to some
biologically parameterized state of the brain. The term for these biologically
parameterized states of the brain is PHX. This refers to all those entities and
processes discussed within the life sciences.
So PSI wishes to perform an action in the
outside world. By means of a cognitive operator PSI initiates the required
parameters of PHX, via a biological operator, to throw a ball, for example: a
PSI to PHX information transection resulting in a PHI operation: the ball
flying. So, information from the PSI subspace transferred information (via
these various operators) to the PHX
subspace which in turn transferred information to the PHI subspace. The
principle which derives from this dynamic is that whenever a PSI subspace has influenced
a PHI subspace some PHX subspace has mediated the transfer of information.
Neurocosmology comes from the expression
space and you define it with perceptual parameters. KHI- state of PHI whose form can only be accounted for by
positing the willful action of PSI via PHX acting on raw PHI, etc. KHI
The
diagram you see here is the biocybernetic loop. It is a very good way for
understanding all the elements of how a human interacts with a computer. If there is a mind then no matter what the particulars
of a disability, what have you, there is a way to interface that mind with a
communications technology.
Thus
it follows that with in the notational system described the necessary and
sufficient conditions for mapping the information flow through the
physio-informatic system is covered by the following:
A Mind (symbol: PSI) as the beginning of
all expression and the end of all perception; the foundation of the whole
process.
An Organism/Life (symbol: PHX) system
facilitating that perception and expression via sensory and motor actions (biological/physiological
factors).
An Interface system which is a two-fold
element (for a very high level technology which applies this thinking: Bot Masters)
Expressional (symbol: SNS): some
mechanism senses/captures some motor action as input from the human (e.g., mouse click, facial
movement).
Perception symbol: SKY): some mechanism
which renders results of the expression back to the human (e.g., screen, audio screen reader for the blind, etc.)
SKY-that product of KHI having been
manipulated by PSI so as to change PSI.
Synectic languaging structure in which we
have a generic metaphor to talk about anything; the goal of this notational
languaging system is to is to allow you to linguistically navigate to any far
reaching PSI space that you want to be involved in.
Move
into a higher state of abstraction connecting more information.
e.g., Sensory physiology is talking about the
PHX specific state spaces which are involved in transducing and transmitting
information to the central nervous system, which is part of the PHX system we
think is highly related to.
These
three fundamental state spaces are required to describe the complete system.
Information
that is described by the state of an external computational system
Information
that is described by a the state of a physiologic system
Information
that is described by the state of perceptible components of a conscious
experience
Each
of these systems is considered to be a fundamental source of information. It is
also presumed that there is an ordered flow of information between these 3
fundamental state spaces. As information is exchanged between these three
state-spaces there are direction specific boundary crossing transfer functions
which restrict/bias/interfere and/or otherwise constrain/restrain the
capacity/fidelity. From the perspective of the physiologic system there is an
information exchange with a persistent external information system and an
emergent internal information system. Thus it is considered a basic tenant for
this model that the body (comprised of all its information processing
physiologic systems) mediates the exchange of information between the computer
and conscious experience. This at first glance may seam some what obvious to
the casual observer. However it is this physiologic mediation of information
(with all of its specific processes)which is the basis for the development of
this reference architecture for developing and optimizing interactive human
computer interface systems..
Simply
put the 3 coupled state spaces of the interactive human computer interface
system being proposed may be described (from the perspective of a conscious
human user of this interactive interface system) as being comprised of/by an
external computational system, the imperceptible physiologic processes which
mediate the exchange of information with that system and conscious experience
and the perceptual qualities of experienced information
Information,
which is externally generated - Phi –Physics
Information,
which is biologically/physiologically mediated - Phx – Life
Information,
which is directly experienced - Psi – Mind (Perception and Intention of
Expression)
The
following discussion covers the efforts to demonstrate the capacity to increase
perceptual dimensionality.
In addition to the new models of mapping information flow was the identification of new mathematical models and representation systems that would give insight to complex phenomena. . New graphical methods of mathematical analysis were being developed which would bring insight into biology.
The following images represent the nature of this “new math”
The development of fractal (fractional dimension ..or non
integer dimension) geometry which was used in several ways to help develop an
understanding of complex systems and their states. Of particular interest was
the work of Price, Sale and Warner
which begin to explore the use of the deterministic iterative model of
mathematical analysis to gain insight on what happens when you alter the
various parameters of the base expression to be iterated. What was discovered
was that one could see complex yet identifiable changes in the rendered
geometry which demonstrated the basic premise of fractal geometry that initial
conditions of seed values and the basic algorithm 
Early
work by David J. Warner, Steven H. Price, S. Jeffrey Sale, in the above
images,
showed that the basic fractals which were
common in the popular media and scientific literature were useful tools for
gaining insight as to the nature of iterative systems. The images above show
that a simple change on the basic algorithm can led to very ordered systems
which are predicted by the change in the base formula. Ie z^2+c gives the basic
fractal but a progression to z^n +c ..where n is 0-4 shows that the number of
symmetries varies as n-1 but the individual patterns are fairly constant (that
is they look to be of the same class)
The
above images demonstrate the nature of iterative, deterministic functions they
also show that a “difference “ can be characterized both visually and
quantitatively.
The basic concept which was utilized from this observation/exploration was that for a given initial condition a unique result would occur and that this method could be used to begin to quantitatively characterize the specific complex dynamics which were intrinsic in the physiological data. This new tool was then applied to physiology to begin to explore the utility of using this description to gain a higher level of insight to the complex state dynamics of the physiological systems. This was important for the development of a robust physiological system which states of information can be inferred form the unique dynamics which could be measured by various instruments. To begin to move forward in the development of a theoretical model of physioinformatics it was necessary to demonstrate that the assumption about being able to uniquely characterize a measured physiological state space dynamic and to link it to a specific information condition of a physiological system.. To establish a relationship between the geometric, the quantitative and the physiologic the following experiment was done
The
following discussions show an early exploration into these methods
These
new mathematical insights were applied to the EEG which is a very complex
system.
CHACTROPIC
DYNAMICAL ANALYSTS OF THE EEC
The
mechanisms generating normal and abnormal rhythms in the brain are poorly
understood but are usually attributed to a combination of sinusoidal
oscillations and stochastic noise. Quantitative analysis of the EEC has
emphasized application of the FET and statistical analysis of the resulting
power spectra. It is now possible to perform chaotropic dynamical analysis of
the EEC. Phase portraits are obtained
by imbedding the EEG time series in a multidimensional space using various time
lags. Phase portraits can be rendered graphically in
2 and 4 dimensions. Lyapanov
exponents, fractal dimensions and Poincare sections can also be obtained. Inspection of phase portraits during 3/sec
spike and wave suggests the presence of a low dimensional state space. EEC during normal eyes open condition suggests
the presence of a high dimensional state space. In deterministic systems, low dimensional state spaces have low
information content and limited response capability. High dimensional
state spaces have
rich response repertoire. chaotropic dynamical analysis of
the EEC provides a powerful theoretical structure within which to interpret
normal and abnormal findings. chaotropic dynamical analysis is an important new
approach to quantitative investigation of electro physiologic measures such as
EEC and MEG.
The Compressed Dimensional Array: a new topographic technique for EEC analysis
The mechanisms generating
the EEC are poorly understood but are
thought to involve non-linear deterministic dynamics. The complexity parameter is an important mea sure of
dimensionality but displays usually do not permit of this parameter comparisons
between many EEC channels over
time. The complexity parameter is
obtained by embedding the time series in progressively higher dimensions until
a scaling property emerges. This dimension is then selected for the Compressed
Dimensional Array (CDA) - The
complexity parameter is then calculated for two second epochs and arrayed in a single
display on an graphics workstation so as to appear as a topographic contour in
which elevation represents the complexity parameter permits a Real-Lime
interaction with this array convenient Areas
method of dimensional analysis.
of low dimensionality appear as easily The CDA provides a new recognized valleys. method of visualizing
dimensionality of the EEC and reveals subtle features of clinical and
scientific interest.
The
use of new graphical techniques which enabled the researcher to gain a greater
degree of insight into the phenomena was applied to the problem of extending
the perceptual dimensionality of research data. Initially EEG data was used to test the utility
of this exploratory mode, it wasn’t
long however that other data sets were evaluated with these methods.
The
following series of images shows the progression from the standard methods of
analysis to a visually rich technique. (it will be asserted that this is
consistent with the reference architecture being developed in this thesis.) The
fundamental idea here is to use the humans natural ability to perceive
differences in space, color, and structure to help elucidate the various
features embedded in the data.
Traditional EEG data is of this nature
From
the images below it can be seen that
this “spatial temporal” iso surface technique enables the detection of
structural components in data that was normally seen as not having any
intrinsic structure.
The
technique developed for exploring d characterizing the electro physiological
data can be shown to be of value for displaying the data in a way in which the
various different modes of EEG seen clinically can be easily classified . The
images below illustrate that point in that they show the various conditions
seen clinically, evoked potentials, anesthesia states, eyes open relaxed
normal. All in a very “perceptible” form.