Synesthetes: Synesthetic Metaphor

climate

There is a very interesting presentation on TED.com by a neurologist who has come up with innovative ways of treating his patients. In the third part of his presentation he talks of Synesthesia which is the ability to experience multiple sensory perceptions in place of one. For example tasting sound or seeing touch.

He points out that there is a part of the brain that, when damaged, disables the ability to understand metaphor and disables Synesthesia. He also demonstrates that we are all synesthetes with a simple experiment.

Understanding icons, in the context of this research, is a synesthetic experience and may show that contrary to my initial reservations, there is some truth to inherent meaning in icons that may be universal.

I have a blog post that is broader in scope than this neurologist’s conclusions. You can find his presentation under “Who Is A Synesthete?”

Here’s the Link: http://blog.grantczerepak.com/2008/11/15/synesthetes/

The moment you say “blue is cool” or “red is hot” you are expressing Synesthetic metaphor.

Here’s some audio recordings from MIT interviewing Synesthetes (each is about 1 minute):

Anyone who can make metaphor is expressing their own Synesthesia. I personally think this is an area of research that should be explored to help people develop their own Synesthetic abilities. It should also be explored to help us find commonalities in Synesthetic perception to develop Icons and Icon languages.

Richard Cytowic has written a book called, The Man Who Tasted Shapes.

I don’t agree with his separation of Synesthesia from common Synesthetic experience, but his insights are worth reading.

Further Links:

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Universe: The Fabrics of Perception

https://i2.wp.com/www.historyforkids.org/learn/greeks/clothing/pictures/weaving.jpg

I am working with the Latin language and it is helping me to classify my thoughts more effectively by understanding historical correlations in meaning. For example matter was considered a fabric. The term for light, “lume”, comes from the term loom which alludes to textile manufacture. In fact all of the textile terms merge with geometry where they were practically applied.

WEAVE: a fabric
POINT: a intersection
LINE: a line
ANG: a cut
HEIR: an area
VOL: layers
QUAL: a bundle

These terms have influenced our thinking for literally thousands of years. We still talk of the “fabric” of space, the fabric of time and “material” or whatever. We are unintentionally applying a metaphor. Yet it is a metaphor that has served us well.

At this point I present a scale that I have arrived at for human sensory perception.

outsideness

– 8 , – 2 , – 1 , 0 , + 1 , + 2 , + 8

where

8 is infinity

2 is two

1 is one

0 is zero

+ is positive

– is negative

– 8 : WEAVE below perception: Datrice
– 2 : POINT: below acception: Sortrice
– 1 : LINE: below exception: Matrice
0 : ANGE: exception: Natrice
+ 1 : HEIR above exception: Patrice
+ 2 : VOL: above acception: Fratrice
+ 8 : QUAL: above perception: Satrice

1. WHO: Eyes: Occipital Lobe: Speciatation of Matter.

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root ASTR for the night sky:

– 8 : WEAVISTER: below perception
– 2 : POINTISTER: below acception
– 1 : LINISTER: below exception
0 : ANGISTER: exception
+ 1 : HEIRISTER above exception
+ 2 : VOLISTER: above acception
+ 8 : QUALESTER: above perception

PhotonicPhotons, PhotonicElectrons, PhotoincIons, PhotonicGases, PhotonicLiquids, PhotonicSolids, PhotonicMolecules

2. WHAT: Ears: Temporal Lobe: Association of Matter

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root FUL for Electricity or “Lightning” which is interesting because it means we hear events.

– 8 : WEAVIFUL: below perception
– 2 : POINTIFUL: below acception
– 1 : LINIFUL: below exception
0 : ANGIFUL: exception
+ 1 : HEIRIFUL: above exception
+ 2 : VOLIFUL: above acception
+ 8 : QUALIFUL: above perception

ElectronicPhotons, ElectronicElectons, ElectronicIons, ElectronicGases, ElectronicLiquids, ElectronicSolids, ElectronicMolecules

3. WHEN: Nose: Brainstem: Attibution of Matter

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root FIED for Ions or burn which is interesting because it means we smell ions or things that are reactive.

– 8 : WEAVEFIED: below perception
– 2 : POINTFIED: below acception
– 1 : LINEFIED: below exception
0 : ANGFIED: exception
+ 1 : HEIRFIED: above exception
+ 2 : VOLFIED: above acception
+ 8 : QUALIFIED: above perception

IonicPhotons, IonicElectrons, IonicIons, IonicGases, IonicLiquids, IonicSolids, IonicMolecules

4. WHERE: Throat: Parietal Lobe: Domination of Matter

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root AER for Gases

– 8 : WEAVIER: below perception
– 2 : POINTIER: below acception
– 1 : LINIER: below exception
0 : ANGIER: exception
+ 1 : HEIRIER: above exception
+ 2 : VOLIER: above acception
+ 8 : QUALIER: above perception

GasicPhotons, GasicElectrons, GasicIons, GasicGases, GasicLiquids, GasicSolids, GasicMolecules

5. WHY: Mouth: Frontal Lobe: Ingestion of Matter

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root AEST for Liquids or “Sea” which is interesting because it means that the Sea is the surface of the water.

– 8 : WEAVIEST: below perception
– 2 : POINTIEST: below acception
– 1 : LINIEST: below exception
0 : ANGIEST: exception
+ 1 : HEIRIEST: above exception
+ 2 : VOLIEST: above acception
+ 8 : QUALIEST: above perception

LiquidicPhotons, LiquidicElectons, LiquidicIons, LiquidicGases, LiquidicLiquids, LiquiidicSolids, LiquidicMolecules

6. HOW: Body: Cerebellum: Deduction of Matter

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root TER for Liquids or “Earth” because it means that the creators of the word Earth meant “water”.

– 8 : WEAVITER: below perception
– 2 : POINITER: below acception
– 1 : LINITER: below exception
0 : ANGITER: exception
+ 1 : HEIRITER: above exception
+ 2 : VOLITER: above acception
+ 8 : QUALITER: above perception

SolidicPhotons,  SolidicElectons, SolidicIons, SolidicGases, SolidicLiquids, SolidicSolidsSolidic, Molecules

HOW MUCH: Gut: brain region unknown

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root DUCT for Counting which is interesting because this involves the digestive process.  Molecule literally means “soft stone”.  Another word for dung.

– 8 : WEAVIDUCT: below perception
– 2 : POINTIDUCT: below acception
– 1 : LINIDUCT: below exception
0 : ANGIDUCT: exception
+ 1 : HEIRIDUCT above exception
+ 2 : VOLIDUCT: above acception
+ 8 : QUALIDUCT: above perception

MoleculicPhotons, MoleculicElectrons, MoleculicIons, MoleculicGases, MoleculicLiquids, MoleculicSolids, MoleculicMolecules.

Note: The seven International System Units are:

– 8 : WEAVE: below perception: Candela
– 2 : POINT: below acception: Ampere
– 1 : LINE: below exception: Kelvin
0 : ANG: exception: Metre
+ 1 : HEIRabove exception: Second
+ 2 : VOL: above acception: Kilogram
+ 8 : QUAL: above perception: Mole

I posted all of the above, because I believe that classification is underrated. If we spent more time thinking about the aesthetics of our classification language, which is presently total crap, we might make more discoveries.

How much do we conceal from ourselves because we deceive ourselves into thinkng a dogmatic classification system won’t bear fruit.

Have you ever seen this guy?

https://relationary.files.wordpress.com/2007/11/mendeleevphoto.jpg

He beat his brains out letting the data talk to him and came up with this:

Periodic Table

When Dmitri Mendeleev created this table to describe periodic behaviour of the elements, many of the elements had not been discovered. However, the table projected what the properties of those elements would be making the search much easier.  Dmitri also was very good at making Vodka.

As I have discussed there are Satrice, Fratrice, Patrice, Natrice, Matrice, Sortrice and Datrice networks.  Each of them classify in different ways.  Understanding these networks and their classification are the road to new discoveries.  Networks are classification systems.

I just saw this in the New York Times:

knowledgemap

It is called a “Knowledge Map”.  It is a plot of the link clicking behaviour of a scientific community.  Not what they say is important, but where they are going that they think is important.  From this information it may be possible to reorganize knowledge to make it more accessible to everyone.

And that is what we are all here for getting and giving access.

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The Zen of Systems and Networks

zencircle01

My own work with Enterprise Frameworks and Networks has led me to come up with the following table.  It describes the Nodes and Links in a Complete System Network.  I am saying that the Nodes representing Goals, People, Time, Locations, Code, Data, Qualities and Quantities can all be represented as Scale-free Networks and that each of these Node Networks require only one datatype.  I am also saying that there are only three types of links in networks: recursive links within a set, multiple links between sets, single links between sets.  I know of no case where this has been attempted in the manner I am attempting to represent it.

systemnetworkslinks1

If you have been following my blog you are aware that I have been struggling for a long time to come up with a framework and a clean terminological set to describe systems.  I think I have come one step closer to that goal today.  The table above describes a Fact composed of eight Nodes (first white row illustrating entities) and the Links (last three white rows illustrating recursive, multiple and singular relationships) for each of the System Networks (Interrogative columns).  One of the interesting aspects of this System Network Model is every Fact is composed of a Unique Set of all eight Nodes.  However, all the Nodes in one Fact do not have to have Links to all the Nodes in another Fact.  Each Node within a Fact is independent regarding its Links.  Therefore you have a single set of System Facts with each Fact containing a single set of Interrogative Nodes each connected by their respective Link Networks.

I have recently been writing with the intent to challenge centrism on any one of these networks and advocate a more integrated view. I still remember dealing with data centrism, event centrism, user centrism, goal centrism, program centrism and schedule centrism over the course of my career. All of them have a role to play. My insight into all of these Nouns being Linked by Verbs in only three ways required me to look at all of the Enterprise Architectures and disengtangle the Nouns, Links and Verbs from the reasoning and representations that extend back beyond computing itself.

The Data Model below is a hybrid of Relational Models and Dimensional Models.  I call this an Associational Model.  It is using Relational Architecture to represent it.  However, I think that an alternate Entity-Attribute-Value (EAV) architecture called the Associative Model of Data would be better suited to the task.  I am using relational representation as I am still trying to communicate with a community only familiar with Relational technology.

The first thing to note about this model is Links are represented by Associations.  Associations link two Nouns using a Verb.  What is interesting about this model is every Verb, Association, Noun and Fact is unique.  The vertical connections are Many to Many relationships which allow two vertically adjacent Verbs, Associations or Nouns to have multiple unique relationships between each other.  What this means is there are no integrity problems (duplicate values) as the system network would enforce uniqueness.

amdschema031

The premise of this model is that the Nodes are not dimensions at all.  I am rejecting the traditional concept of dimensionality instead I am saying that there are three dimensions of Links: recursive, multiple and singular.  All we perceive are Facts, Nodes and the Links between them.

So you could come away with the following Zen koan:

entity without entity,

source without source,

path without path,

target without target,

size without size,

dimension without dimension.

Systema: Exteroception and Interoception

hugo-critchley.jpg

I was reading an article in Scientific American MIND this evening which discussed the research of Hugo Critchley on emotional intelligence and interoception. Interoception which is narrowly defined as the perception of stimuli inside the body. Interoception activates the brain’s right insular cortex and has lead Critchley to a broader definition of interoception. The reason being that not only perception of internal stimuli, but of emotion results in intense activity in the insular cortex. It has also been found that another center in the brain associated with ideas, motives and values often shows activity in conjunction with insular cortical activity. The right insular cortex appears to be the location where mind and body meet. Neurologically, you perceive hunger in the same way you perceive anger. You have a physical location for intuition, that “gut feeling”.

So, why do I bring this up? The main reason is I am thinking about Maslow’s hierarchy and the DIKW hierarchy. I have been struggling to substantiate a hexad as opposed to a tetrad for the number of layers of input and output and I think this provides another cornerstone for my argument. Interoception, the perception of stimuli inside the body, and exteroception, the perception of stimuli outside the body, fill the gap beneath data and divide Maslow’s physiological needs. I am proposing the following hexad:

  1. Green Hat: Wisdom. Self-Actualization. Conceptualization.
  2. Yellow Hat: Knowledge. Esteem. Contextualization.
  3. White Hat: Information. Belonging. Logicalization.
  4. Black Hat: Data. Safety. Physicalization.
  5. Red Hat: Intuition. Physiological. Humanization. Interoception.
  6. Blue Hat: Communication. Existential. Detection and Effection. Exteroception.

In my future discussions I am not going to talk about the movement of data or information or knowledge or stimuli. I am simply going to refer to input and output. Input ascends the hierarchy and output descends the hierarchy. From which level it originates is also irrelevant if it is ascending it is always input, if it is descending it is always output. The transformations are discrete. They are not increases or decreases in detail, but changes in perspective.

If you are following this lengthy thread you may notice my terms changing a bit each time. It is an iterative refinement of my understanding that is leading to these changes. Hopefully, I get closer to a final version with each change.