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Henry S Gurr ZMMQ SiteMaster. 1 June 2019, and 27 June 2022.XXXXXX .

Supplementary Information#2 for Henry S Gurr’s Unified Panorama View Into How Our Mind Works, Including Topics Of => Analogy, Metaphor, and Related Neural Cognitive Theories..

Articles & Books, Which Are Relevant To Henry S Gurr’s Proto Theory Panorama of How Our Mind Works.

This Page Is A Compilation Of Additional Information, Selected Because It Supports (or Is Relevant To) => SiteMaster Henry S Gurr’s Proto Theory of How Our Mind Works Click Here.

NOTE1: Readers Should Be Aware That There Are FOUR Continuation Pages Of “Supplementary Information” Which Are =>
…
1) Supplementary Information1, for Henry S Gurr’s Unified Panorama View Into How Our Mind Works.
…
2) Supplementary Information2, for Henry S Gurr’s Unified Panorama View Into How Our Mind Works. This is the WebPage you are reading right now.
…
3) Supplementary Information3, Featuring Professor James F Ross’ Book ‘Portraying Analogy’ … Which Very Much Is Working With “Metaphor” …. AND Is Relevant To (And Supports), Henry S Gurr’s Unified Panorama View Into How Our Mind Works.

4) Supplementary Information4, for Henry S Gurr’s Unified Panorama View Into How Our Mind Works.

… NOTE2: A Clickable Menu For This Page You Are Reading Now, Is ~8 Inches Below.

The Published Articles, Listed Below, On This Page You Are Reading Now => Were Selected Because Supports (Or Is Relevant To), Henry S Gurr’s Unified Panorama View Into How Our Mind Works.
… The Following Articles and Information were mostly found (and selected out of) Google Results Search, from wide variety of topic areas related to Mind, Consciousness, Brain Research, Neuron Physiology, Psychology, Artificial Intelligence, Decision Theory, Etc. Eventually our search will be expanded to include The Citation Index , and also expand to Google Advanced search, where we look for WebPages, that are themselves link to valuable article, already discovered. These articles are presented somewhat in order of their discovery. Material copied directly from the various articles below is sometimes shown in “quote marks”. These articles are presented somewhat in order of their discovery.
DISCLAMER: There is no claim that this compilation is anywhere near to =>
a) Exhaustive, b) Has the most important information in these fields, c) Is presented in a logical order, d) Has a good choice of excerpts from these Google Found Documents, or e) Even has an adequate balance of topics covered.
…You will find that for each article, listed we have presented perhaps too much information, and trust you the reader, can select what is of interest, and skip otherwise. This information is presented for what it is worth, in hopes, that it will be useful and revealing to those who are Friends In Mind!
WHAT HAVE I LEARNED FROM ALL THESE WEBPAGES LISTED BELOW?:
... Strange to say, I have not learned much at all! These Researchers & Thinkers, each have their own starting point and from there go on to develop their own conclusions, none of which go in similar directions.- The results of each of these workers does not fit or support the works other workers. Thus, for me, there is no sense of emerging convergence on what are the better conclusions, or even the better ways to go.
... For the most part, there is nothing wrong with what they say: And I find much that supports (with no disagreement to) my Henry Gurr's “Explanation (Theory) How Our Mind Works”, and conversely

Organization and Format Of This Page
Tor Each Published Article Listed Below, You Will See:

Clickable Menu: To Jump To An Item, Click On Its Blue Text Below.
If you wish to return here after jumping to the section, click the “Back” Arrow in your Internet Browser’s Upper Left Corner.

Part One: Articles
A) Programming a Parallel Computer: The Ersatz Brain Project
C) Search and Coherence-Building in Intuition and Insight Problem Solving
D) Embodied Meaning In A Neural Theory of Language
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Part Two: Books Which Support Henry Gurr’s Proto-Theory, And How To Read Them.
A1) “The Neural Theory of Metaphor”, by George Lakoff
| B!) “Portraying Analogy” by James F Ross
C!) “Fluid Concepts and Creative Analogies” by Douglas Hofstadter
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A) “Programming a Parallel Computer: The Ersatz Brain Project.”
Abstract:
… “There is a complex relationship between the architecture of a computer, the software it needs to run, and the tasks it performs. The most difficult aspect of building a brain-like computer may not be in its construction, but in its use: How can it be programmed? What can it do well? What does it do poorly? In the history of computers, software development has proved far more difficult and far slower than straightforward hardware development. There is no reason to expect a brain like computer to be any different. This chapter speculates about its basic design, provides examples of “programming” and suggests how intermediate level structures could arise in a sparsely connected massively parallel, brain like computer using sparse data representations.”
[SiteMaster Henry Gurr Comment: This discussion is confirming to my Henry S Gurr’s Proto Theory of Mind, Starting With Compact Explanation. Click Here. because of its many insightful assertions about Human Brains, such as the points below.]

https://link.springer.com/chapter/10.1007/978-3-540-71984-7_4

B) “How Your Mind Works and Why It’s Important To Know.” By Caroline Ferguson. [This article is an introductory overview of => “If you want to be able to manage your mind, it helps to understand something about what’s going on inside your head.”, < As stated by Caroline Ferguson. Below is what she very well and importantly says => ]
... So Why Is It Important To Understand How Your Mind Works
Because, ultimately, that knowledge gives you much more control over how to use the combined power of your conscious and unconscious minds to think in a more healthy, flexible, resilient and goal-supporting way.
... The benefits include improved self worth, far less emotional upheaval and a much greater ability to achieve what you want in life. [Which is also true of the benefits of Henry Gurr's “Explanation (Theory) How Our Mind Works. ]
https://carolineferguson.com/how-your-mind-works/

C1) “Psychological Constructivism: The [Student As] Independent Investigator, by Open Textbook for Hong Kong.” July 26, 2019.
Opening Two Paragraphs: [Important Ideas Underlined By Henry Gurr.]
… ”{:+The main idea of psychological constructivism is that a person learns by mentally organizing and reorganizing new information or experiences. The organization happens partly by relating new experiences to prior knowledge that is already meaningful and well understood. Stated in this general form, individual constructivism is sometimes associated with a well-known educational philosopher of the early twentieth century, John Dewey (1938-1998). Although Dewey himself did not use the term constructivism in most of his writing, his point of view amounted to a type of constructivism, and he discussed in detail its implications for educators. He argued, for example, that if students indeed learn primarily by building their own knowledge, then teachers should adjust the curriculum to fit students' prior knowledge and interests as fully as possible. He also argued that a curriculum could only be justified if it related as fully as possible to the activities and responsibilities that students will probably have later, after leaving school. +} To many educators these days, his ideas may seem merely like good common sense, but they were indeed innovative and progressive at the beginning of the twentieth century.
… A more recent example of psychological constructivism is the cognitive theory of Jean Piaget (Piaget, 2001; Gruber & Voneche, 1995). Piaget described learning as interplay between two mental activities that he called assimilation and accommodation. Assimilation is the interpretation of new information in terms of pre-existing concepts, information or ideas. A preschool child who already understands the concept of bird, for example, might initially label any flying object with this term even butterflies or mosquitoes. Assimilation is therefore a bit like the idea of generalization in operant conditioning, or the idea of transfer described at the beginning of this chapter. In Piaget's viewpoint, though, what is being transferred to a new setting is not simply a behavior (Skinner's “operant” in operant conditioning), but a mental representation for an object or experience.
… NOTE: The above is from a single Webpage, which is part of a much larger whole book, that may be accessed by a (at left0 Clickable Menu:
You may view this Menu & the remainder of this Webpage here =>
https://www.opentextbooks.org.hk/ditatopic/6150

C2) “The Key To Radical Constructivism.” By Alexander Riegler. Last update: Nov 28, 2003.
... ” … constructivism certainly comes in a huge variety of forms and versions. I felt challenged to get some grip on its sumptuousness — especially because people regularly ask me to provide some sort of overview. In fact they sometimes express their astonishment that what they considered a monolithic epistemology turns out to be a dappled[very complex] one. I have to admit that also for me it took some time to recognize the jungle as such and some more time to find my way through it. Please find below a (certainly still crude) version of the requested guide. Suggestions and corrections are welcome.
Click Here For Archive.org version of Alexander Riegler’s “The Key To Radical Constructivism.”
.----

[SiteMaster Henry Gurr Comment: ]
Concerning The Following SIX Articles About The “**AHA** Flash of Insight” .
… What is said in these SIX Articles, C1) thru C6) => Very Well Fits My “Proto Theory of how Our mind Works” and its emerging conclusions were developed during my 35 years of study of the consequences of the quite general sudden automatic spontaneous mental events, variously known as: Flash of Insight, Sudden **AHA**, Inspiration, Dawning, Lightning Strikes, Zeus, Epiphany, Revelation, Light-Bulb Turning On (as shown to in cartoons): These can collectively be called “Sudden Mental Arrivals Into Conscious Mind” These Sudden Mental Arrivals are from brain processes which are entirely unconscious. Yes indeed, our brain processes are completely hidden and entirely unconscious, and as you will learn, for very important reasons:
… But nevertheless, with close observation study of the Flash of Insight type of events, we can clearly see VERY amazing problem solving brain abilities, which have huge brain science implications that follow from it, when properly understood:
… The Flash of Insight, Like The Tip Of An Iceberg, can reliably be used to study the something very big hidden below: But just because you can’t see what’s causing it, doesn’t mean isn’t important, and can be ignored. (For examples see 1) the page concerning “Wave of crystallization” of Jules Henri Poincaré, Chapter 21, in Robert Pirsig’s Zen and the Art of Motorcycle Maintenance. Or 2) My article “Memory Perception Insight And Problem Solving. AHA! Click Here.
The Following SIX Articles Discuss Research Studies of The “**AHA** Flash of Insight” .

D1) “Incubation and Intuition in Creative Problem Solving,” By Kenneth J. Gilhooly. July 22, 2016.
Abstract:
… “Creative problem solving, in which novel solutions are required, has often been seen as involving a special role for unconscious processes (Unconscious Work) which can lead to sudden intuitive solutions (insights) [often called Flash of Insight ] when a problem is set aside during incubation periods. This notion of Unconscious Work during incubation periods is supported by a review of experimental studies and particularly by studies using the Immediate Incubation paradigm. Other explanations for incubation effects, in terms of Intermittent Work or Beneficial Forgetting are considered. Some recent studies of divergent thinking, using the Alternative Uses task, carried out in my laboratory regarding Immediate vs. Delayed Incubation and the effects of resource competition from interpolated activities are discussed. These studies supported a role for Unconscious Work as against Intermittent Conscious work or Beneficial Forgetting in incubation.”
… Keywords: creativity, intuition, problem-solving, incubation effect, insight problem solving

… [SiteMaster Henry Gurr Comment: This Author makes the significant point about their => “Delayed Incubation” and … “a role for Unconscious Work as against Intermittent Conscious work.” … You will see that, their “mental processes”, and “successful convergences”, and overall discussion fits VERY well to my => Henry S Gurr’s Proto Theory of Mind, Starting With Compact Explanation. Click Here. … You will especially see where the Authors here take up the VERY important topics of (in their own words) => “spontaneous breakthroughs into consciousness while attention is focused on other matters, or as very rapid solutions on returning to previously intractable problems.”: these are both important features of my Theory, especially because they are discussing many or the important properties of the Flash of Insight .type of automatic spontaneous Mental Arrival. ] …Authors continue ->
… “Creative problem solving involves the production of approaches and solutions that are novel to the solver even if not historically novel (Boden, 2004). Explaining the generation of personally novel solutions is an unresolved issue for the psychology of thinking and problem solving. Sometimes, problems seem to be solved by an immediate intuition or insight [often called Flash of Insight ] (e.g., Salvi et al., 2016) but, with difficult problems, a period of conscious analysis is usually needed, even if it does not directly lead to solution and the problem is set aside before solution. Why might setting a problem aside facilitate solution? One popular explanation is that setting creative problems aside for a period can allow unconscious processes to generate solution ideas, which are then experienced, either as spontaneous breakthroughs into consciousness while attention is focussed on other matters, or as very rapid solutions on returning to previously intractable problems. These solutions occurring apparently rapidly and without awareness of intermediate steps, will be experienced as akin to the dictionary idea of an intuition as a truth (a solution in this case) perceived without reasoning or analysis.”
… ”The value of setting a problem aside for facilitating solutions has been a concern of theorists in the area for at least the past 100 years. Wallas (1926, p. 80) drew on Poincaré’s (1910) earlier analysis of mathematical creation and labeled the stage in which a problem is not consciously processed as “Incubation.” (It is noteworthy that Poincaré himself did not use the term “Incubation” in his 1910 paper, although he reported four examples of incubation periods from his own experience of creative work in mathematics). In Wallas’s analysis, Incubation is proposed as a useful stage after conscious Preparation but preceding Illumination (or Inspiration) and Verification. Clues to processes underlying creative thinking should be found from analyses of when and why Incubation can be useful. Subjective reports by acknowledged creative thinkers over many areas of work have supported the existence of incubation phenomena (e.g., Poincaré, 1910; Ghiselin, 1952; Csikszentmihalyi, 1996). However, since such personal reports have often been given many years after the events described, the reliability of such reports is highly questionable. For example, frequently cited accounts by Coleridge (composition of poem Kubla Khan in a dream), Mozart (complete compositions coming to mind without error) and Kekulé (discovery of benzene ring in a dream) have proven to be false (Weisberg, 2006, pp. 73–78). Poincaré (1910) himself based his own analysis of creative thinking on self reports of problem solving episodes he had experienced nearly 30 years previously. This is actually rather curious, as Poincaré was an active researcher in mathematics at the time of making his analysis of creative thinking and could presumably have drawn on more recent episodes which would be less susceptible to recall problems. ..."
… The remainder of this excellent article is here =>
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4956660/
https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2016.01076/full

D2) “What happens When 'AHA!' Strikes.” By Research News. August 3, 2015
Opening Two Paragraphs:
… “Research at Drexel University shows sudden insights are real--and you can train your brain to have more
Insight--you know the feeling. It's that amazing idea, the solution that hits you like a bolt of lightning. It can come to you while you're mulling over a problem, or days later, when you're making a sandwich or mowing the lawn. And John Kounios has seen what your brain is doing when it has that "aha moment." “
… ”With support from the National Science Foundation's (NSF) Social, Behavioral and Economic Sciences Directorate, the Creativity Research Lab that Kounios heads at Drexel University uses electroencephalography (EEG) and other technology to record brain activity. The lab has been looking for something very specific: What goes on in the brain when a flash of insight hits. … “
… Remainder of article is here =>
https://beta.nsf.gov/news/what-happens-when-aha-strikes

D3) “Scientists Find 'AHA!' Favors a Prepared Mind.” By Physics.Org News. April 10, 2006.
Opening Three Paragraphs:
… ”Why do "AHA!" moments sometimes come easily and sometimes not at all? A new study reveals that patterns of brain activity before people even see a problem predict whether they will solve it with or without a sudden insight.”
… ”If you’ve experienced the highs and lows of creative thinking, you know that sometimes the creative well is dry, while at other times creativity is free flowing. It is during the latter times that problem solvers often experience so-called “Aha!” moments – those moments of clarity when the solution to a vexing problem falls into place with a sudden insight and one sees connections that previously eluded you.”
… ”But why do “AHA!” moments sometimes come easily and sometimes not at all? A new study reveals that patterns of brain activity before people even see a problem predict whether they will solve it with or without a sudden insight, and these brain activity patterns are likely linked to distinct types of mental preparation. … ”
… Remainder of article is here =>
https://phys.org/news/2006-04-scientists-aha-favors-mind.html

D4) “What Sudden Insights Look Like Inside The Brain”, by Rob Margetta, National Science Foundation:” Credit: Drexel University, August 4, 2015
Opening First Four Paragraphs:
… “Graduate student Brian Erickson, part of John Kounios' research team at Drexel University, studies live streaming electroencephalogram (EEG) data. Erickson and Kounios are currently analyzing EEG recordings to look for the reward signals in the brain generated when a moment of insight occurs.”
… ”Insight—you know the feeling. It's that amazing idea, the solution that hits you like a bolt of lightning. It can come to you while you're mulling over a problem, or days later, when you're making a sandwich or mowing the lawn. And John Kounios has seen what your brain is doing when it has that "AHA moment."
… ”With support from the National Science Foundation's (NSF) Social, Behavioral and Economic Sciences Directorate, the Creativity Research Lab that Kounios heads at Drexel University uses electroencephalography (EEG) and other technology to record brain activity. The lab has been looking for something very specific: what goes on in the brain when a flash of insight hits.”
… ”What Kounios has found has overturned some long-held beliefs in cognitive science about how quickly the brain can snap from a state of not knowing something to knowing it completely. He's also made discoveries that shed light on exactly how ideas emerge—including how your brain briefly blocks out visual information to focus on finding an answer to a tough question. … “
https://medicalxpress.com/news/2015-08-sudden-insights-brain.html

D5) “There Is No Such Thing as Unconscious Thought: A behavioral scientist unravels one of our most cherished conceptions.” By Nick Chater, July 24, 2018.
…EXPLANATION: Anything that we can call “Thought”, is always conscious, and thus there is, YES, “No Such Thing As Unconscious Thought”.
…Many thanks to Professor Chater for an illuminating & thoughtful article. Clearly, he & I have been working the same Vinyard for a long time.
…. This Article Attempts To Answer => …Why Do Solutions To Problems Suddenly Pop Into Our Minds? …AND, It Is Good To See That This Article 6 Times Focus On Variants Of “Solve The Problem”, Which You State In Your Own (Nick Chatter) Words As =>
a) [in response to] “our struggle to make sense of apparently baffling images”.[You Say] b) “Why do solutions to problems suddenly pop into our minds?”
c) [a person] “may experience a rather delightful feeling when, suddenly, their interpretation “pops out”
d) :” you find the pictures suddenly make sense”
e) “what feels like a “bolt from the blue” of sudden understanding.”
f) When the object does suddenly “pop out,” we have a sense of sudden insight, but no idea how to explain where it came from. Without warning, order emerges from chaos. We have no sense of getting “warmer” or “colder” before insight suddenly hits us”
g) Plus, many more.
While I See This Article As Mostly Correct, Yet There Are A Few Places That Are Confusing Or Confounding, Such As =>
…Without supporting explanation (or theory justification), you assert => “The phenomenon of sudden insight stems NOT from unconscious thought, but from the nature of the problem: Searching for a meaningful interpretation with few helpful and unambiguous clues.” <<Which by inference, you are saying, are steps all guided by conscious thinking.
…All the while for some reason => This article fails to recognize that each of these =>

https://nautil.us/there-is-no-such-thing-as-unconscious-thought-237152/

D6) “Incubation and Intuition in Creative Problem Solving.” By Kenneth J. Gilhooly, Front Psychol. 2016; 7: 1076. Jul 22, 2016.
Abstract Creative problem solving, in which novel solutions are required, has often been seen as involving a special role for unconscious processes (Unconscious Work) which can lead to sudden intuitive solutions (insights) when a problem is set aside during incubation periods. This notion of Unconscious Work during incubation periods is supported by a review of experimental studies and particularly by studies using the Immediate Incubation paradigm. Other explanations for incubation effects, in terms of Intermittent Work or Beneficial Forgetting are considered. Some recent studies of divergent thinking, using the Alternative Uses task, carried out in my laboratory regarding Immediate vs. Delayed Incubation and the effects of resource competition from interpolated activities are discussed. These studies supported a role for Unconscious Work as against Intermittent Conscious work or Beneficial Forgetting in incubation.
Keywords: creativity, intuition, problem-solving, incubation effect, insight problem solving
“Intuition: the power of the mind by which it immediately perceives the truth of things without reasoning or analysis; a truth so perceived, immediate, instinctive knowledge or belief.”
... From The Chambers Dictionary, 9th Edition, 2003, p. 778. Edinburgh:
... Creative problem solving involves the production of approaches and solutions that are novel to the solver even if not historically novel (Boden, 2004). Explaining the generation of personally novel solutions is an unresolved issue for the psychology of thinking and problem solving. Sometimes, problems seem to be solved by an immediate intuition or insight (e.g., Salvi et al., 2016) but, with difficult problems, a period of conscious analysis is usually needed, even if it does not directly lead to solution and the problem is set aside before solution. Why might setting a problem aside facilitate solution? One popular explanation is that setting creative problems aside for a period can allow unconscious processes to generate solution ideas, which are then experienced, either as spontaneous breakthroughs into consciousness while attention is focussed on other matters, or as very rapid solutions on returning to previously intractable problems. These solutions occurring apparently rapidly and without awareness of intermediate steps, will be experienced as akin to the dictionary idea of an intuition as a truth (a solution in this case) perceived without reasoning or analysis.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4956660/

D7) “Looking For A Likely Cause Of A Mental Phenomenon.” By Valentine, Dec 1, 2012. 34 comments are interesting. [Following excerpt give a sense of what author is thinking. ]
... The puzzle is how thought incubation works, ideally expressed in terms of neural systems or neuroanatomical structures. I'll first explain the phenomenon and then suggest the general reference class from which I'm hoping to get an answer.
The Phenomenon:
... Mathematicians frequently report that often one of the most helpful things they can do to solve a problem they're stuck on is step away from it. Jacques Hadamard (1949) examined his own experiences and also talked to many of his colleagues to work out what the common structure of this experience was, and determined that there seems to be a fairly predictable sequence to it:

... For instance, Henri Poincaré reported struggling to work on Fuchsian functions over the course of several weeks and then being forced to walk away from the proof he had been stuck on due to a planned vacation. One day he was stepping onto a bus with his mind certainly not on mathematics, and suddenly the key insight he needed to finish the proof appeared in his mind. It was as though a part of his mind had been secretly working on the problem and then brought the finished product into his awareness. In this particular case it also came with a feeling of total confidence that verification would pan out (although Hadamard notes that the validation step after the insight is still essential because sometimes that feeling of total confidence is mistaken).
https://www.lesswrong.com/posts/h2QdnJBbSwEE36jc9/looking-for-a-likely-cause-of-a-mental-phenomenon
*** *** *** ***

H) “Marcel Proust: Beyond the Madeleines.”, By Michael Norris, June 17, 2009: Has An Excellent Flash of Insight Example, Which Shows The “Release Of The Floodgates Of Memory!”
... ”He unconsciously dips the Madeleine into the tea, and sips the tea from the spoon in which he had dipped the morsel of cake. Then: “no sooner had the warm liquid mixed with the crumbs touched my palate than a shudder ran through me and I stopped…An exquisite pleasure had invaded my senses, something isolated, detached, with no suggestion of its origin.” He attempts to recreate the sensation, with diminishing results. Then suddenly the memory is revealed to him. He used to take these little cakes dipped in tea at Combray on Sunday morning, when he visited his Aunt Leonie. Suddenly, he experiences a flash back of memory, where he can see the town of Combray in color. He can see the square, the flowers in Swann’s garden, and water-lilies on the river Vivonne. The petit Madeleine has opened the floodgates of his memory.”
https://litkicks.com/Marc elProustBeyondTheMadeleines/ - comment-68905

I) In This You Tube Video Interview, It is Fun To Watch Richard Bach’s Ever Changing Face Expressions & Emotions, As He Explains His Insights & Discoveries In His => “Adventure of the Spirit -- A Thinking Allowed.” DVD With Jeffrey Mishlove.
... This is a very dynamic, fascinating Interview with Richard Bloch, author of top selling book Jonathan Livingston Seagull. Bach’s enthusiastic, animated, discussion of “The Power Of The Imagination” is Excellent! As he says “What I'm Doing Now.” He is “Interested In Imagination Vs The Psychic Mind”. What Bach says about Imagination, well fits the Imagination discussions of Samual Taylor Coleridge and Owen Barfield.
https://www.youtube.com/watch?v=eCPGJYhvO9w

J) “Mathematical Problem-Solving Via Wallas’ Four Stages of Creativity: Implications for the Undergraduate Classroom,” By Milos Savic, University of Oklahoma. TME, vol. 13, no.3, p.255
Abstract:
… “The central theme in this article is that certain problem-solving frameworks (e.g., Polya, 1957; Carlson & Bloom, 2005) can be viewed within Wallas’ four stages of mathematical creativity. The author attempts to justify the previous claim by breaking down each of Wallas’ four components (preparation, incubation, illumination, verification) using both mathematical creativity and problem-solving/proving literature. Since creativity seems to be important in mathematics at the undergraduate level (Schumacher & Siegel, 2015), the author then outlines three observations about the lack of fostering mathematical creativity in the classroom. Finally, conclusions and future research are discussed, with emphasis on using technological advances such as Livescribe™ pens and neuroscience equipment to further reveal the mathematical creative process."
… “Keywords: mathematical creativity, problem solving, proving, fostering creativity, incubation, creative process “
… [SiteMaster Henry Gurr Comment: You will see that, their overall discussion describes the importance of the study of “Mathematical creativity… for mathematics and mathematics education”. The Author makes the significant point about “Wallas’ four components (preparation, incubation, illumination, verification), as follows -> ” “[student work] is more likely to bear fruit when the mind is subsequently relaxed and able, subconsciously, to relate the ideas in a manner which benefits from quiet, unforced, contemplation." … This well fits => SiteMaster Henry S Gurr’s Proto Theory of Mind, Starting With Compact Explanation. Click Here. … You will especially see where the Authors here take up the following paragraph of VERY important topics of (in their own words) these are both important features of my Theory. ]

"What is essential in the individual is a state of mind prepared for mental activity that relates previously unrelated concepts. [Mathematical creativity] is often observed to occur after a period of intense activity involving a heightened state of consciousness of the context and all the constituent parts. And yet it is more likely to bear fruit when the mind is subsequently relaxed and able, subconsciously, to relate the ideas in a manner which benefits from quiet, unforced, contemplation."
http://www.milossavic.com/uploads/1/2/6/9/1269470/math_enthusiast_mps_wallas_published.pdf

K) “Students’ Creative Process in Mathematics: Insights from Eye-Tracking-Stimulated Recall Interview on Students’ Work on Multiple Solution Tasks.” By Maike Schindler & Achim J. Lilienthal. December 2, 2019.
Abstract:
… “Students’ creative process in mathematics is increasingly gaining significance in mathematics education research. Researchers often use Multiple Solution Tasks (MSTs) to foster and evaluate students’ mathematical creativity. Yet, research so far predominantly had a product-view and focused on solutions rather than the process leading to creative insights. The question remains unclear how students’ process solving MSTs looks like—and if existing models to describe (creative) problem solving can capture this process adequately. This article presents an explorative, qualitative case study, which investigates the creative process of a school student, David. Using eye-tracking technology and a stimulated recall interview, we trace David’s creative process. Our findings indicate what phases his creative process in the MST involves, how new ideas emerge, and in particular where illumination is situated in this process. Our case study illustrates that neither existing models on the creative process, nor on problem solving capture David’s creative process fully, indicating the need to partially rethink students’ creative process in MSTs.”
First paragraph of Introduction
… “Creativity is significant for innovation, working out original ideas, and finding new paths of thinking. Creativity has always been of major importance for the domain of mathematics. Mathematicians such as Hadamard and Poincaré have pointed this out, referring to moments of sudden illumination, so-called eureka moments that appeared when solving fundamental mathematical problems. Also, mathematics education research focuses increasingly on mathematical creativity (see, e.g. Leikin & Pitta-Pantazi, 2013; Sheffield, 2013; Singer, 2018) with the aim to prepare students for their current and future lives in our increasingly automated and interconnected high-technology-based societies and economies (Organization for Economic Co-operation and Development [OECD], 2014). It appears no longer sufficient for students to solve problems only with routine schemes or familiar heuristics. Footnote1 Educators aim to teach for creativity and to give students the opportunity to work creatively with mathematics (Silver, 1997). Students shall become able to think “out of the box”, to connect different topics while solving problems, to have Aha! experiences. … “
… Remainder of article is here =>
https://link.springer.com/article/10.1007/s10763-019-10033-0
Originally Published: International Journal of Science and Mathematics Education volume 18, pages1565–1586 (2020) Cite this article.

L) “The Princeton Companion to Mathematics.” Edited by Timothy Gowers, June Barrow-Green, Imre Leader.
... In this eclectic book’s, Chapter => “The Art Of Problem Solving”, Page 963, gives Many full quotations of workers in this field. Many of these mention the Sudden Solution To The Problem, which are recognizable as The Flash of Insight, but they mostly don’t use that term.
... Also mentioned in passing is ”Hadamard’s Four Phases of Problem Solving”. (See Next Below)
Click Here For Parts Of This Book, Available From Google.Books.

From Wikipedia => Jacques Salomon Hadamard (French): 1865 –1963) Was A French Mathematician Who Made Major Contributions In Number Theory, Complex Analysis, Differential Geometry, And Partial Differential Equations.
Hadamard On creativity:
... In his book Psychology of Invention in the Mathematical Field, Hadamard uses the results of introspection to study mathematical thought processes,   and tries to report and interpret observations, personal or gathered from other scholars engaged in the work of invention.   In sharp contrast to authors who identify language and cognition, he describes his own mathematical thinking as largely wordless, often accompanied by mental images that represent the entire solution to a problem. He surveyed 100 of the leading physicists of the day (approximately 1900), asking them how they did their work.
... Hadamard described the experiences of the mathematicians/theoretical physicists Carl Friedrich Gauss, Hermann von Helmholtz, Henri Poincaré and others as viewing entire solutions with "sudden spontaneousness".
... Hadamard described the process as having four steps of the five-step Graham Wallas creative process model, with the first three also having been put forth by Helmholtz:[6]: 56  Preparation, Incubation, Illumination, and Verification. [ Wallas' five stages added "Intimation" prior to Illumination, a sudden feeling of being about to find the solution to a problem.
https://en.wikipedia.org/wiki/Jacques_Hadamard

The Following FOUR Valuable Articles, Were Found By Google Search For … Hadamard’s Four Phases Of Problem Solving …. These Articles Are Shown Below, Because They Agree With And Support, Henry Gurr's “Explanation (Theory) How Our Mind Works.

M) “Hadamard: The Mathematician's Mind.” By Steve Hsu July 31, 2009,
I've been meaning to discuss the book The Psychology of Mathematical Invention in the Mathematical Field, by Jacques Hadamard. It was inspired by a lecture of Poincare to the French Psychological Society entitled "Mathematical Creation". Although I always considered Hadamard a 19th century figure (born 1865), the book was published in 1945 and he lived until 1963!
Here is the Amazon description:
... ”Fifty years ago when Jacques Hadamard set out to explore how mathematicians invent new ideas, he considered the creative experiences of some of the greatest thinkers of his generation, such as George Polya, Claude Lévi-Strauss, and Albert Einstein. It appeared that inspiration could strike anytime, particularly after an individual had worked hard on a problem for days and then turned attention to another activity. In exploring this phenomenon, Hadamard produced one of the most famous and cogent cases for the existence of unconscious mental processes in mathematical invention and other forms of creativity. Written before the explosion of research in computers and cognitive science, his book, originally titled The Psychology of Invention in the Mathematical Field, remains an important tool for exploring the increasingly complex problem of mental life.”
... ”The roots of creativity for Hadamard lie not in consciousness, but in the long unconscious work of incubation, and in the unconscious aesthetic selection of ideas that thereby pass into consciousness. His discussion of this process comprises a wide range of topics, including the use of mental images or symbols, visualized or auditory words, "meaningless" words, logic, and intuition. Among the important documents collected is a letter from Albert Einstein analyzing his own mechanism of thought.”
Hadamard emphasizes a four step process of invention, consisting of
”Preparation: conscious effort attacking the problem, including analysis of various methods and approaches; the outcome often appears fruitless “
”Incubation: a period of subconscious effort while the conscious mind is occupied with other matters “
”Illumination: the solution forms [and suddenly AHA, automatically spontaneously comes into] the conscious mind
”Verification: the solution is verified through conscious effort “
... This description agrees with my own Henry Gurr’s experience. It seems that certain activities like walking are good for Incubation, and the shower is a good time for Illumination. Over the past weeks I've been deliberately trying to follow this method in my own research, with modest success :^) I noticed that it is also useful for overcoming writer's block -- put aside the paragraph you are struggling with and walk around for five or ten minutes before resuming. The walk often allows a small conceptual reordering, enough to proceed.
[More recently Amazon quotes Library Journal says => “Thoughtful and articulate study of the origin of ideas. Role of the unconscious in invention; the medium of ideas — do they come to mind in words? in pictures? in mathematical terms? Much more. "It is essential for the mathematician, and the layman will find it good reading."
https://www.amazon.com/Psychology-Invention-Mathematical-Field/dp/0486201074

N) “A Descriptive Phase Model Of Problem-Solving Processes.” By Benjamin Rott, Birte Specht & Christine Knipping, Volume 53, pages 737–752, March 9, 2021.
Abstract Complementary to existing normative models, in this paper we suggest a descriptive phase model of problem solving. Real, not ideal, problem-solving processes contain errors, detours, and cycles, and they do not follow a predetermined sequence, as is presumed in normative models. To represent and emphasize the non-linearity of empirical processes, a descriptive model seemed essential. The juxtaposition of models from the literature and our empirical analyses enabled us to generate such a descriptive model of problem-solving processes. For the generation of our model, we reflected on the following questions: (1) Which elements of existing models for problem-solving processes can be used for a descriptive model? (2) Can the model be used to describe and discriminate different types of processes? Our descriptive model allows one not only to capture the idiosyncratic sequencing of real problem-solving processes, but simultaneously to compare different processes, by means of accumulation. In particular, our model allows discrimination between problem-solving and routine processes. Also, successful and unsuccessful problem-solving processes as well as processes in paper-and-pencil versus dynamic-geometry environments can be characterised and compared with our model.
https://link.springer.com/article/10.1007/s11858-021-01244-3

O) “Creativity In Problem Solving: Integrating Two Different Views Of [Sudden Unconscious] Insight.” By Per Øystein Haavold & Bharath Sriraman. September 2, 2021. Volume 54, pages 83–96, (2022)
Abstract Even after many decades of productive research, problem solving instruction is still considered ineffective. In this study we address some limitations of extant problem solving models related to the phenomenon of insight during problem solving. Currently, there are two main views on the source of insight during problem solving. Proponents of the first view argue that insight is the consequence of analytic thinking and a sequence of conscious and stepwise steps. The second view suggests that insight is the result of unconscious processes that come about only after an impasse has occurred. Extant models of problem solving within mathematics education tend to highlight the first view of insight, while Gestalt inspired creativity research tends to emphasize the second view of insight. In this study, we explore how the two views of insight—and the corresponding set of models—can describe and explain different aspects of the problem solving process. Our aim is to integrate the two different views on insight, and demonstrate how they complement each other, each highlighting different, but important, aspects of the problem solving process. We pursue this aim by studying how expert and novice mathematics students worked on two ill-defined mathematical problems. We apply both a problem solving model and a creativity model in analyzing students’ work on the two problems, in order to compare and contrast aspects of insight during the students’ work. The results of this study indicate that sudden and unconscious insight seems to be crucial to the problem solving process, and the occurrence of such insight cannot be fully explained by problem solving models and analytic views of insight. We therefore propose that extant problem solving models should adopt aspects of the Gestalt inspired views of insight.
https://link.springer.com/article/10.1007/s11858-021-01304-8

P1) “MATHEMATICAL DISCOVERY: HADAMARD RESURECTED.” By Peter Liljedahl, Simon Fraser University, Canada.
... In 1943 Jacques Hadamard gave a series of lectures on mathematical invention at the École Libre des Hautes Etudes in New York City. These talks were subsequently published as The Psychology of Mathematical Invention in the Mathematical Field (Hadamard,1945). In this article I present a study that mirrors the work of Hadamard. Results both confirm and extend the work of Hadamard on the inventive process. In addition, the results also speak to the larger context of 'doing' and learning mathematics.
... What is the genesis of mathematical creation? What mechanisms govern the act of mathematical discovery? This "is a problem which should intensely interest the psychologist. It is the activity in which the human mind seems to take the least from the outside world, in which it acts or seems to act only of itself and on itself" (Poincaré, 1952, p. 46). It should also intensely interest the mathematics educator, for it is through mathematical discovery that we see the essence of what it means to 'do' and learn mathematics. In this article I explore the topic of mathematical discovery along two fronts, the first of which is a brief synopsis of the history of work in this area. This is then followed by a glimpse at a study designed to elicit from prominent mathematicians ideas and thoughts on their own encounters with the phenomenon of mathematical discovery. https://www.emis.de/proceedings/PME28/RR/RR116_Liljedahl.pdf

P2) “How to Solve It.” By George Pólya, First edition Princeton University Press, Genre Mathematics, Problem Solving.
... “How to Solve It (1945) is a small volume by mathematician George Pólya, describing methods of problem solving. This book has remained in print continually since 1945.”
... In this book are described “Four principles Of Solving, which are fully given in the Wikipedia Article. Readers should know that Hadamard’s Problem Solving much emphasizes sudden automatic Mental Arrivals, such as the Flash of Insight, but Polya’s Problem Solving minimally mentions Insight.
https://en.wikipedia.org/wiki/How_to_Solve_It
https://en.wikipedia.org/wiki/George_Polya

P3) “How Creativity in Humor, Art, and Science Works: Arthur Koestler’s Theory of Bisociationl” By Maria Popova. [This is an excellent introductory overview of Arthur Koestler’s seminal book The Act Of Creation Mr. Koestler’s work essentially starts with Mental Arrivals such as the Flash of Insight, and refines & extends to be more general and include a much wider rang of important mental phenomena. ]
... ”New Yorker cartoon editor Bob Mankoff presented his theory of humor as “a conflict of synergies,” which reminded me of a wonderful concept from Arthur Koestler’s seminal 1964 anatomy of creativity, The Act Of Creation (public library). Koestler coins the term bisociation to illustrate the combinatorial nature of creativity — the reason it operates like a slot machine, relies on the mind’s pattern-recognition machinery, and requires the synthesis of raw material into “new” ideas.”
... Koestler, in his seminal 1964 (book) anatomy of creativity, The Act Of Creation , shows two diagrams of, his theory, each showing a path of mental progression 2D plane. And then tells us that the bisociation mental event happens at the intersection of two diagrams positioned perpendicular planes. This article shows these two diagrams in their perpendicular orientation.
https://www.themarginalian.org/2013/05/20/arthur-koestler-creativity-bisociation/

P4) “Full Text For Arthur Koestler’s Book => “The Act of Creation” [This version is images, and can not be searched or copy text words. It is 19 MB is size, and will take a long time to load. You may find the load fails, and may have to try several times for success. ]
Click Here For Full Text Of Koestler’s Book.

Q) “A Very Useful Book: “The Rough Guide to Travel Survival” '' By Doug Lasky.
…You might want to purchase this because => You will find good general survival advice, as well as the survival technique => “Follow Water Down Stream”, on pages 186 thru 191. (See Blue Link Below.)
… You Should ALSO Should Carefully Think About This Survival Rule => Which By Happenstance Is A Good Analogy To How Our Brain Works.

WHY IS THIS BOOK MENTIONED HERE?
…The idea => Always Move Towards Inevitable Problem Solution, Also Applies To => How Our Problem Solving Brain Works
.. To find a Best or Near Best Solution (Answer) our brain “Slides To Better & Better”: This, is analogous to “Water sliding down a series of gullies”, similar to water flowing down a steep mountain stream. So “All Is Slide To Better & Better Partial Fit Problem Solution!”, is analogous to a liquid going downhill, following & guided by valleys, to lowest energy level.
This GoogleBooks “Preview” Seems To Show The Entire Book, Full Text.

R) “How to Find Civilization When You Have No Idea Where You Are.” By Elise Xavier 2013.
…This WebPage gives an excellent, expanded full discussion that follows fairly well, the above-mentioned “Tough Guide To Travel Survival “
Click Here For This Article, And AFTER This Page Comes Up, Please Ignore (The At Right) Photos and Advertisements.

S) “What to do When You’re Lost in the Woods.” By Montana Hiking Trails, Maps, and Guides.
…If hopelessly lost in a remote mountainous region (problem to be solved), Survival Manuals Suggest This Rule (A general means of solving problem) => “One good rule on self rescuing is to follow water downhill. Generally speaking, roads and civilization lie downhill of a mountain, so following a stream downhill can be a smart move.”
Click Here For This Entire Article.

T) “Cognitive Mechanisms Underlying the Creative Process” by . Professor of Psychology Liane M. Gabora.
A well written, very interesting & illuminating article that “…proposes an explanation of the cognitive change that occurs as the creative process:
....And, it is good to see that, 5 times, there is a focus on variants of “solve the problem”, and that the creative outcomes can be understood in Gabora’s words as => “best captures the properties” OR => “concept that best categorizes”.
https://arxiv.org/ftp/arxiv/papers/1310/1310.1678.pdf

V) “Secrets Of The Creative Brain.” By Nancy C. Andreasen, Atlantic Monthly,
July/August 2014 Issue. ''' [An interesting article, that has marginal application to “Theory Of Mind”. ]
... A leading neuroscientist who has spent decades studying creativity shares her research on where genius comes from, whether it is dependent on high IQ, and why it is so often accompanied by mental illness.
... As a psychiatrist and neuroscientist who studies creativity, I’ve had the pleasure of working with many gifted and high-profile subjects over the years, but Kurt Vonnegut—dear, funny, eccentric, lovable, tormented Kurt Vonnegut—will always be one of my favorites. Kurt was a faculty member at the Iowa Writers’ Workshop in the 1960s, and participated in the first big study I did as a member of the university’s psychiatry department. I was examining the anecdotal link between creativity and mental illness, and Kurt was an excellent case study.
... He was intermittently depressed, but that was only the beginning. His mother had suffered from depression and committed suicide on Mother’s Day, when Kurt was 21 and home on military leave during World War II. His son, Mark, was originally diagnosed with schizophrenia but may actually have bipolar disorder. (Mark, who is a practicing physician, recounts his experiences in two books, The Eden Express and Just Like Someone Without Mental Illness Only More So, in which he reveals that many family members struggled with psychiatric problems. “My mother, my cousins, and my sisters weren’t doing so great,” he writes. “We had eating disorders, co-dependency, outstanding warrants, drug and alcohol problems, dating and employment problems, and other ‘issues.)While mental illness clearly runs in the Vonnegut family, so, I found, does creativity. Kurt’s father was a gifted architect, and his older brother Bernard was a talented physical chemist and inventor who possessed 28 patents. Mark is a writer, and both of Kurt’s daughters are visual artists. Kurt’s work, of course, needs no introduction.
... For many of my subjects from that first study—all writers associated with the Iowa Writers’ Workshop—mental illness and creativity went hand in hand. This link is not surprising. The archetype of the mad genius dates back to at least classical times, when Aristotle noted, “Those who have been eminent in philosophy, politics, poetry, and the arts have all had tendencies toward melancholia.” This pattern is a recurring theme in Shakespeare’s plays, such as when Theseus, in A Midsummer Night’s Dream, observes, “The lunatic, the lover, and the poet / Are of imagination all compact.” John Dryden made a similar point in a heroic couplet: “Great wits are sure to madness near allied, / And thin partitions do their bounds divide.”
https://www.theatlantic.com/magazine/archive/2014/07/secrets-of-the-creative-brain/372299/

W1) “Explaining How The Mind Works: A New Theory..” By ResearchOutreach.org, November 15, 2019.
Abstract & Opening First paragraph:
… “How and why do humans think and act in the ways that we do? To answer this question, Dr Paul Badcock and his colleagues have recently proposed a theory of the human brain that combines evidence from evolutionary and developmental psychology, neuroscience, and biology. This theory posits that the human brain is a complex adaptive system, composed of relatively specialised and domain-general structures that work in tandem to generate adaptive responses to the environment. Arguably, their Hierarchically Mechanistic Mind (HMM) model brings us closer to a comprehensive understanding of the brain.”
… ”The desire to understand the greatest enigma of all – our own minds – has been the driving force behind many scientific endeavours, leading to the development of theories and experiments aimed at explaining the mechanics of being human. Human thoughts, feelings, and behaviours are rooted in the brain, where a complex network of cells receives information from the internal and external environment, transforming this information into our experience of ourselves, the world around us, and our relationships with it. It goes without saying that how this happens is still being explored. … ”
… Remainder of article is here =>
https://researchoutreach.org/articles/explaining-how-the-mind-works-new-theory/

W2) “How Your Mind Works and Why It’s Important To Know.” By Caroline Ferguson, “A Mindset Trainer and Speaker Who Works With-Potential Leaders.”
Abstract + First 4 Sentences:
… “ Whatever mindset issues have you feeling stuck --– like procrastination, limiting beliefs, low self-worth, perfectionism or consistently failing to achieve goals –-- you’ll learn plenty of practical tips when you sign up to my newsletter. Changing your mindset [to where you better understand ‘How Your Mind Works’] is the first step to changing your world.”
… ”If you want to be able to manage your mindset, it helps to understand something about what’s going on inside your head.”
… ”You don’t have to be a brain surgeon or neuroscientist to be curious about the contents of your skull. The human brain is the most complex thing in the universe and you get to own one – how amazing is that?”
… ”Let me explain some of how it works. (Bear in mind that this is a very simple explanation. The reality is far more complex.) …. “ [Then Caroline makes some very important points => ]
“So Why Is It Important To Understand How Your Mind Works?”
... ”Because, ultimately, that knowledge gives you much more control over how to use the combined power of your conscious and unconscious minds to think in a more healthy, flexible, resilient and goal-supporting way.”
... ”The benefits include improved self worth, far less emotional upheaval and a much greater ability to achieve what you want in life.”
... ”One of the functions of the unconscious mind is to create and maintain habits – and that’s something I’m going to come back to in my next post, when I talk about how your mind forms habits – both good and bad – and how you can use this knowledge to your advantage.”
… [SiteMaster Henry Gurr Comment: As you will see in this very good presentation, Caroline Ferguson, in simple, well-organized & concise terms, outlines the different parts of our Human Mind, and the essential operations of each. … Overall, what Caroline presents in Outline Form, very well fits my own “Theory of how Our Mind Works”: And because Caroline’s “Outline” is so good, you may want to come back to it (for re-orientation), you happen to get lost & disoriented in reading my Theory. AND YESThere are many really important reasons you should know, as Caroline Furgeson says ! => “How Your Mind Works and Why It’s Important To Know.” “ … And my theory is one of the best places to start:
… Altogether, what Caroline Ferguson’s “Outline” fits well to Henry Gurr’s Theory, and can provide a very good Orientation Structure for => SiteMaster Henry S Gurr’s Proto Theory of Mind, Starting With Compact Explanation. Click Here.
… Caroline’s Whole Article Is Here =>
https://carolineferguson.com/how-your-mind-works/

W3) “The New Science of Mind and the Future of Knowledge.” By Eric Kande.
Abstract:
… “Understanding mental processes in biological terms makes available insights from the new science of the mind to explore connections between philosophy, psychology, the social sciences, the humanities, and studies of disorders of mind. In this Perspective we examine how these linkages might be forged and how the new science of the mind might serve as an inspiration for further exploration.”
“Main Text”
… ”Ever since Socrates and Plato first speculated on the nature of the human mind, serious thinkers have sought to understand themselves and human behavior in general. For earlier generations, that quest was restricted to the intellectual framework of philosophy. In the late twentieth century, however, a school of philosophy concerned with the human mind merged with cognitive psychology, the science of the mind; both then merged with neuroscience, the science of the brain. The result was a new, biological science of the mind. The guiding principle of this new science is that mind is a set of processes carried out by the brain, an astonishingly complex computational device that constructs our perception of the external world, fixes our attention, and controls our actions. Many people—including policy makers—are beginning to realize that the central challenge confronting science in the twenty-first century is a better understanding of the human mind in biological terms.”
… ”Two world leaders have already responded to this challenge. Shimon Peres, the president of Israel, announced at the 2013 World Economic Forum that the lack of a firm biological understanding of the human mind is one of the great problems confronting the world. He initiated the million-dollar Global B.R.A.I.N. Prize for breakthroughs in brain science that translate into treatments of brain disorders. In his 2013 State of the Union address, President Barack Obama independently boosted brain science with the announcement of a massive, multibillion-dollar public and private initiative to understand the human brain. In years to come, this BRAIN initiative may provide a scientific basis for understanding all brain disorders—not just psychiatric disorders, but neurological disorders as well, especially Alzheimer’s disease, Huntington’s disease, and amyotrophic lateral sclerosis. … “
… Remainder of article is here =>
https://www.sciencedirect.com/science/article/pii/S0896627313009914

W4) “Explaining How The Mind Works: A New Theory. How And Why Do Humans Think And Act In The Ways That We Do? ” November 15, 2019
... ”To answer this question, Dr Paul Badcock and his colleagues have recently proposed a theory of the human brain that combines evidence from evolutionary and developmental psychology, neuroscience, and biology. This theory posits that the human brain is a complex adaptive system, composed of relatively specialised and domain-general structures that work in tandem to generate adaptive responses to the environment. Arguably, their Hierarchically Mechanistic Mind (HMM) model brings us closer to a comprehensive understanding of the brain.”
... ”… Dr Paul Badcock has recently proposed a model of the brain that synthesises major paradigms from psychology, neuroscience, and biology to explain why and how we think and act in the ways that we do.”
... ”Their hypothesis, called the Hierarchically Mechanistic Mind (HMM), combines two established claims. The first claim, formulated by Dr Badcock’s colleague, Professor Karl Friston, postulates that the human brain is a hierarchical ‘prediction machine’ that strives to improve its model of the world by generating adaptive cycles of perception and action that operate synergistically to reduce our uncertainty about the environment. The second claim, based on Tinbergen’s famous four questions in ethology, proposes that to understand human thoughts and behaviours, hypotheses must be developed and tested across multiple levels of analysis in psychological science. In other words, researchers seeking to explain psychological traits should endeavour to understand why a given trait might be adaptive, along with how it emerges from the dynamic interplay between evolutionary, developmental, and real-time mechanistic processes.”
https://researchoutreach.org/articles/explaining-mind-works-new-theory/

X1) “The Unreasonable Effectiveness Of Deep Learning In Artificial Intelligence.” By Terrence J. Sejnowski.
Abstract:
… ”Deep learning networks [in Artificial Intelligence] have been trained to recognize speech, caption photographs, and translate text between languages at high levels of performance. Although applications of deep learning networks to real-world problems have become ubiquitous, our understanding of why they are so effective is lacking. These empirical results should not be possible according to sample complexity in statistics and nonconvex optimization theory. However, paradoxes in the training and effectiveness of deep learning networks are being investigated and insights are being found in the geometry of high-dimensional spaces. A mathematical theory of deep learning would illuminate how they function, allow us to assess the strengths and weaknesses of different network architectures, and lead to major improvements. Deep learning has provided natural ways for humans to communicate with digital devices and is foundational for building artificial general intelligence. Deep learning was inspired by the architecture of the cerebral cortex and insights into autonomy and general intelligence may be found in other brain regions that are essential for planning and survival, but major breakthroughs will be needed to achieve these goals.”
… [SiteMaster Henry Gurr Comment: The Author Sejnowski makes the following significant point that “Artificial Intelligence, Deep learning Networks have been trained to recognize speech, caption photographs, and translate text between languages at high levels of performance.” But why it works so well is not understood. To help with this, I think that modern Artificial Intelligence needs => SiteMaster Henry S Gurr’s Full Extensive Proto Theory of Mind, Starting With Compact Explanation. Click Here. …AND modern Artificial Intelligence needs understand the virtues of the Biological Brain Neural Network Optimizing Problem Solving Associative Memory, and the Hopfield Neural Network Model, ]
https://www.pnas.org/doi/10.1073/pnas.1907373117

X2) “Search and Coherence-Building in Intuition and Insight Problem Solving.” Makes Many Good Assertions.
Abstract:
… “Coherence-building is a key concept for a better understanding of the underlying mechanisms of intuition and insight problem solving. ''However, there is still no proper framework defining the general principles of coherence-building. We propose a four-stage model of coherence-building. The first stage starts with spreading activation restricted by constraints. This dynamic is a well-defined rule based process. The second stage is characterized by detecting a coherent state. We adopted a fluency account assuming that the ease of information processing indicates the realization of a coherent state. The third stage is designated to evaluate the result of the coherence-building process and assess whether the given problem is solved or not. If the coherent state does not fit the requirements of the task, the process re-enters at stage 1. These three stages characterize intuition. For insight problem solving a fourth stage is necessary, which restructures the given representation after repeated failure, so that a new search space results. The new search space enables new coherent states. We provide a review of the most important findings, outline our model, present a large number of examples, deduce potential new paradigms and measures that might help to decipher the underlying cognitive processes.”
… [SiteMaster Henry Gurr Comment: The Authors make the following significant point about their “rule-based coherence-building processes.” You will see that, their overall discussion describes “mental processes”, and “successful convergences” that fit well to => SiteMaster Henry S Gurr’s Proto Theory of Mind, Starting With Compact Explanation. Click Here. … You will especially see where the Authors here take up the VERY important topics of (in their own words) “Spreading Activation”, AND their “A Model of Coherence Building”: these are both important features of my Theory. ]
… “Bowers et al. (1990) seminal work on “Intuition in the context of discovery” coherence was supposed to be the key process underlying intuition and insight. Coherence results from a widely unconscious and guided search process, which converges in an integrated representation of the given information, which surpasses the threshold to consciousness.
In greater detail, the guiding stage is driven by spreading activation within mnemonic networks (Collins and Loftus, 1975). Those activation patterns build up to an implicit and unconscious “perception of coherence” (Bowers et al., 1990, p. 74). This tacit perception of coherence guides the thought toward a more “explicit perception in question.” It is important to note that Bowers et al. (1990) did not assume that such an implicit coherent representation is equal to the later consciously experienced coherence, but provides a fragmentary representation which could be enriched gradually by accumulating information.”
“Eventually, the integrative stage provides the result of a completed accumulation process. The activation within the network becomes so strong that it crosses the threshold to consciousness. At this stage coherence is, recognized as a hunch, which needs to be validated by an analytic validation process. …
… [SiteMaster Henry Gurr Comment: Continued below are author’s own words, which summarize their own Ideas and Observations. Their discussion, is at base, very similar to Henry Gurr’s Proto Theory of How Our Mind Works. ….In particular they form =. “A postulate that a coherent state is closely related to Gestalt circuits” and How does a person realize that a coherent state is reached?” ]
[SiteMaster Henry Gurr Comment Continued: In the following passages the authors report a research, which looks for (in their own words) => “a transition in a person’s behavior while solving a series of digit string problems.” … In these passages please especially note the underlined passages, added by myself. END HSG Comment.]
… “The participants, were asked to solve a puzzle when “ .. confronted by strings composed of three different digits. E.g., the string 1 1 4 4 9 4 9 4. There are two rules that have to be obeyed: to solve the puzzle.
… “The strings were composed in a way that they either could be solved by this step-wise or sequential method, or much faster by realizing that there is a hidden rule, where the solution to the problem is already determined after the second attempt, since the sequence of the reduced digits is symmetrical [see Wagner et al. (2004) for the details of the task.
… ”The number reduction task allows the moment of time to be determine when participants utilize the hidden rule. A sudden drop in the solution time is detectable, which could not be explained by step-wise learning process. Haider et al. (2013) postulated that after a large number of attempts implicit processes extract and detect the underlying regularity of the given sequences. This enters a processing shortcut resulting in a much higher process fluency. Such distinct behavioral changes could be realized consciously by the participants. The realization allows insight to be gained consciously into the symmetric nature of the response strings.”
… ”Another indicator that helps to realize a coherent state is the change of the affective state. This addresses the famous Aha! experience. The Aha! is described by a few dimensions, such as suddenness, positive affect, or the feeling of being right (Topolinski and Reber, 2010; Danek et al., 2013; Danek and Wiley, 2016). It seems conceivable that such changes could easily be detected by the problem solver and could lead to the re-evaluation of the problem-solving process.”
… ”It is important to note that an Aha! experience is not a proper predictor for the correctness of the solution …. “
“Stage 3: Evaluation”
… ”At this stage the result of the coherence-building process is evaluated. The problem solver validates whether the solution fits the given requirements and meets the desired goal. The solution is either found and coherent or the result is incorrect, which necessitates a restart of the search.”
… ”Heider (1946) called a coherent state a state of balance. The given elements (information) fit together and there are no contradicting relations between the given elements. Following Heider’s account explains the need for coherence. Incoherence leads to tension within the system and there is a tendency toward a balance state. This might explain, why at the first place the cognitive system has a drive toward coherence. Heider’s field theoretical approach addressed the relations between persons and objects. Heider aimed at providing the determinants of social behavior and social perception. Beyond that, we propose that Heider’s account is generally applicable to situations where mutual relations of interdependent information are given. It provides a rule-based framework explaining the dynamics of coherence-building. … “
“Open Questions and Limitations.”
… ”An important premise that the four-stage model made is that constraint satisfaction and binding are the basic processes, one at a cognitive, the other a neural level. There are alternative accounts that question the idea of binding by synchrony (Hayworth, 2012) or provide alternative accounts for the combination of information, such as the latching mechanism provided by Amati and Shallice (2007), Song et al. (2014) or binding by convolution introduced by Thagard and Stewart (2011). We leave this question open to be answered by future work. We are positive about the fact that our model would also work with an alternative binding process.”
… ”Another open point is why the system tends to search for a coherent or state of balance? Related to this point is the question, is it possible that there are problems where imbalance is necessary to solve the problem? Furthermore, it would be helpful to determine at an individual level, which traits of characteristics of personality increase the probability of finding coherence.”
… ”The notion of a rule-based account is also questionable. This refers to the notion of dual systems. Dual system accounts in general differentiate between a fast, unconscious, unlimited, holistic (system 1) and a slow, deliberate, logical, restricted system (system 2) (Evans, 2008; Kahneman, 2012). Insight and intuition are often assigned to system 1 processes. For many years, there have been discussions, whether such two separate systems, modes or processes are necessary, plausible, well-defined and complete (Evans, 2008; Kruglanski and Gigerenzer, 2011; Kahneman, 2012; Evans and Stanovich, 2013; Mega et al., 2015).”
… ”In our line of argumentation, we followed Kruglanski and Gigerenzer (2011) who proposed a rule-based account in which the rules range between an explicit and implicit level. We think this account is also supported by the modeling accounts we reviewed above (Hélie and Sun, 2010; Thomson et al., 2015).”
… ”In contrast, Evans and Stanovich (2013) disagree with this proposal and argue that there are clear indicators for two systems. Most important would be the fact that only system 2 supports hypothetical thinking and showed heavy working memory load. Again, we are not in a position to resolve this discussion right now, but we think that our model might help to search for unified processes which vary in the processing stage.”
… ”In sum, we hope to demonstrate a more general model on insight and intuition which shows that insight and intuition are the two different sides of the same coin. ”
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5447020/

Y1) “Embodied Meaning In A Neural Theory Of Language. [ = NTL ]” By Jerome Feldman* and Srinivas Narayanan
International Computer Science Institute, University of California,
Berkeley, CA 94720, USA Accepted 26 August 2003
… [SiteMaster Henry Gurr Comment: Below are author’s own words, which summarize their own Ideas and Observations. This discussion, is at base VERY SIMILAR to Henry Gurr’s Proto Theory of How Our Mind Works.
… NOTE: Authors Feldman& Narayanan appear to be continuing from (and are building beyond Prof George Lakoff’s “The Neural Theory of Metaphor” : AND MOREOVER => Please especially notice, that Feldman* and Narayanan discussion of “Embodied Meaning”, as is in their “Neural Theory Of Language” => is VERY CLOSELY RELATED to Lakoff’s “The Neural Theory of Metaphor “ , which you may study in the Book Listings BELOW. ]
… ”The Neural Theory Of Language (NTL) approach to language suggests that the complex synergy that supports grasping is the core semantics of the word. We choose this particular example because there is a great deal known about the intricate distributed neural circuitry involved in grasping by monkeys and humans. We will briefly review some of the key findings and then demonstrate their relevance for the NTL theory of meaning. The action of grasping has both a motor component (what you do in grasping) and various perceptual components (what it looks like for someone to grasp and what a graspable object looks like). There are other modalities involved as well, such as the somato-sensory component (what it feels like to be grasp something or to be grasped yourself). Both the meaning of a word and its defining behavior are context dependent - you grasp differently for different objects and purposes. The theory also entails that the meaning of a noun (e.g. cup) depends on its possible uses or affordances (Gibson, 1979). There is both linguistic evidence (from classifier languages) and imaging data (Tettamanti et al., 2002) supporting this idea that the meaning of a noun depends on the uses of the underlying thing. Mirror neurons in monkeys and their homologs in people (Buccino et al., 2001) suggest an overlapping substrate for the execution of actions and for the perception of the same action. This is a plausible neural basis for the fact that an action word, like grasp, denotes grasping, being grasped, or observing grasping. More generally, there is increasing evidence for the multi-modal neural substrate for actions and action words. Rizzolatti and coworkers, over the last 20 years have shown that frontal area F4 contains neurons that integrate motor, visual, and somato-sensory modalities for the purpose of controlling actions in space and perceiving peri-personal space (the area of space reachable by body parts) or their activity. (Fogassi, Gallese, Fadiga, & Rizzolatti, 1996a; Fogassi et al., 1996b; Fogassi et al., 1992; Gentilucci et al., 1988; Gentilucci, Scandolara, Pigarev,
[This article here continues with a long list of references, but is omitted. ]
… ”But there seems to be a complexity barrier. How could the meaning of an action word be the activity of a vast distributed network of neurons? The key to solving this in the model and, we believe also in the brain, is parameterization. A motor action such as grasping involves many coordinated neural firings, muscle contractions, etc. but we have no awareness of these details.” … ”What we can be aware of (and talk about) are certain parameters of the action – force, direction, effector, posture, repetition, etc. The crucial hypothesis is that languages only label the action properties of which we can be aware. That is, there is a fixed set of embodied features that determine the semantic space for any set of concepts, such as motor actions. … “
… ”The full description of how an ECG system would analyze and enact an utterance is beyond the scope of this paper (Bergen & Chang, 2002), but an example should help convey the flavor of the model. The basic operation in ECG analysis is constructional composition, which we will now illustrate. Consider the phrase ‘‘on the table’’. Following the principles of embodied semantics, the ECG meaning of (this sense of) ‘‘on’’ is an instance of the image schema for support. The parser places a support schema in the semantic specification (SemSpec) with two open roles: one for the supported item and one for the supporting item. The semantics of (one sense of) ‘‘table’’ includes the fact that it is a probable supporting item so the parser unifies the 390 J. Feldman, S. Narayanan / Brain and Language 89 (2004) 385–392 correct senses of on and table, yielding a composed SemSpec element for subsequent analysis. A discussion of how the system determines which table is involved is can be found in Feldman (2002). As the analysis continues, each construction that is recognized gives rise to additional elements and connections in the semantic specification, which is the basis for enactment. In the case of being asked to pass the salt, the result would be a general SemSpec for a personal request linked to an X-schema for passing the salt, assuming the hearer decided to comply with the request. The salt-passing schema would itself be the composition of sub-schemas for locating the salt, reaching for it, grasping it, and placing it near the requester. The enactment of any such schema can not be totally specified by language and depends also on the situation. But it does seem that ECG can explain what is conveyed by language and how it links to the underlying embodied semantics. The ECG paradigm is also being extended to gestures accompanying language as well as to the intonation and emotional tone of the utterance. You can imagine many ways that someone might ask for the salt that would be radically different in emotion. There are planned ECG constructions that link from prosodic features e.g. a strident voice to meaning, e.g., lack of respect. Much work remains to be done, but the basic ideas on embodied word learning, active simulation, and metaphorical interpretation appear to form the basis for a biologically plausible model of language acquisition and use. As should be obvious by now, the theory predicts that any utterance will simultaneously match multiple constructions and thus activate multiple brain circuits. The synthesis of embodied meaning and its subsequent enactment is essentially the same task faced in visual or other perceptions of a complex ongoing situation. One should not expect language to be any more (or less) localized than other perceptions and action.”
http://www1.icsi.berkeley.edu/~snarayan/B+L.pdf

Y2) “The Spur Of The Moment: What Jazz Improvisation Tells Cognitive Science.” Published: 28 March 2018. AI & Society, Volume 34, pages 251–268, (2019)
…What excites me Henry Gurr, about what these authors have to say is that => They have a very good wide gauge & holistic understanding of what is going on in the minds of music players, and in expressing this very well:
…In addition, they are close to offering a Theory of How Our Mind Works!! And as such, most of their Article supports and corroborates my (Henry Gurr’s) own “Explanation (Theory) Of How Our Mind Works”.
https://link.springer.com/article/10.1007/s00146-018-0838-4

Y3) “Mapping The Brain's Metaphor Circuitry: Metaphorical Thought In Everyday Reason.” By George Lakoff.
…This insightful article is closely related to my (Henry Gurr’s) own “Explanation (Theory) Of How Our Mind Works”. And has the following words I have added underlines, and it is immediately evident that George Lakoff and I have been working common ground … independently & for many-a-year! =>

This Full Article Is Available At Either Of These Links =>

At This Point, Readers Should Please Be Aware That Part of My “Explanation (Theory) Of How Our Mind Works” is => My Henry Gurr Metaphor Theory =>
…1) Is based on what we can commonly observe, especially The Flash of Insight, and other similar Mental Arrivals.
…2) Is consistent with Neural Networking.
…3) Emphasizes that => Consciousness in our mind is an automatic brain generated, single coherent unified “right now” view of the world:
…4) Emphasizes that =>The Flash of Insight, and other similar Mental Arrivals, are created as general solutions to the problem of => How to best respond to our second by second sensory input from our surrounding environment.
,,,5) Bottom Line: From this, it is seen that our mind’s ability to see and use Metaphor, is part of a much larger, more general, & more inclusive brain process (called by HSG “Partial Fit Solutions”), which indeed includes Consciousness itself!.
,,,D) Readers will find my Theory, will compliment this articles point of view, and likely to extent George Lakoff’s current conclusions, for seeing into “How Our Brain Works”.
For example Readers will find Henry Gurr’s Very Viable Explanation Of How Our Mind So Easily “Sees” Metaphor. AFTER This Page Comes Up, Please Scroll Down To So Easily & Effectively Use

Y4) “The Neural Theory of Metaphor”, By George Lakoff, University of California at Berkeley. January, 2009. [Lakoff’s Conclusions Are Is VERY Closely Related To The (20 Inches ABOVE) Article=> “Embodied Meaning In A Neural Theory Of Language [ = NTL ]” by Jerome Feldman* and Srinivas Narayanan. ]

The below writing of George Lakoff , appeared in an earlier version =>
R. Gibbs. 2008, The Metaphor Handbook, Cambridge University Press.
-http://www.neurohumanitiestudies.eu/archivio/SSRN-id1437794The_Neural_Theory_of_Metaphor.pdf -

[SiteMaster Henry Gurr Comment: Below are Professor Lakoff’s complete article of own words, which summarize his own Ideas and Observations. Although Prof Lakoff’s own trail of discovery, originates from a different arena, he has many conclusions similar to those in Henry Gurr’s SiteMaster Henry S Gurr’s Proto Theory of How Our Mind Works, Starting With Compact Explanation. , posted on ZMMQ Click Here.
… This abovementioned similarity, is seen most especially seen in Prof Lakoff’s below statements when he uses such words as => a) “Best”, b) “Better”, c) “Best Fit”, d) “Make Sense”, e) “Maximum”, f) “Give Rise To”, g) “Energy”(minimum):
… Prof Lakoff sentences with these words. are REMARKABLY CLOSE conclusions to those of HSG Theory!! See especially the Bold’s and Underline’s by HSG below. ]
... … … …
… ”The neural revolution is changing our understanding of the brain and the mind in radical ways, and that is no less true in the theory of metaphor. It is 30 years since Mark Johnson and I wrote Metaphors We Live By in 1979. Though the fundamental outlines of what we discovered remain as valid today as they were then, developments in brain science and neural computation have vastly enriched our understanding of how conceptual metaphor works. This is an intermediate report, as of January 2009. You may well ask why anyone interested in metaphor should care about the brain and neural computation. The reason is that that what we have learned about the brain explains an awful lot about the properties of metaphor. For example, have you ever asked why conceptual metaphor exists at all, why we should think metaphorically, why metaphors should take the form of cross-domain mappings? Have you thought about …”
… ”You may well ask why anyone interested in metaphor should care about the brain and neural computation. The reason [again] is that that what we have learned about the brain explains an awful lo t about the properties of metaphor. . For example, have you ever asked why conceptual metaphor exists at all, why we should think metaphorically, why metaphors should take the form of cross-domain mappings? Have you thought about how our metaphor system is grounded in experience, or about why certain conceptual metaphors are widespread around the world or even universal? Have you wondered about how whole systems of philosophical or mathematical thought can be built up out of conceptual metaphors.”
… ”The neural theory explains all this. It explains more as well: Why metaphorical language should take no longer to process than non-metaphorical language. Why some sentences of the form X is Y make sense as metaphors and why others fail. How conceptual metaphors can play a role in abstract concepts. These and other wondrous properties of conceptual metaphors fall out once one considers metaphor theory from the perspective of the brain.”
… ”In 1988, Jerome Feldman came to Berkeley as director of the International Computer Science Institute, and he and I formed the NTL (Neural Theory of Language) group. Feldman is one of the founders of the theory of neural computation, and we have been working together since then. Feldman’s landmark book, From Molecule to Metaphor surveys much of the work of our group, and is a must-read for metaphor theorists. As a background both to reading that book and to our discussion of metaphor, I offer a brief and overly simple introduction to the neural theory of language (NTL)” . (( Electronic copy available at: http://ssrn.com/abstract=1437794 ))

A Brief Introduction to NTL
… Every action our body performs is controlled by our brains, and every input from the external world is made sense of by our brains. We think with our brains. There is no other choice. Thought is physical. Ideas and the concepts that make them up are physically “computed” by brain structures. Reasoning is the activation of certain neuronal groups in the brain given prior activation of other neuronal groups. Everything we know, we know by virtue of our brains. Our physical brains make possible our concepts and ideas, everything we can possibly think is made possible and greatly limited by the nature of our brains. There is still a great deal to be learned about how the brain computes the mind. NTL combines what is known scientifically with linking hypotheses based on neural computation.

The Shaping of the Brain
… We are born with an enormously complex brain with hundreds of precisely and beautifully structured regions and highly specific connectivity from every region to many other regions. Each neuron has connections to between 1,000 and 10,000 other neurons. Between birth and the age of five, roughly half of the neural connections we are born with die off. The ones that are used stay; the others die. That is how are brain is shaped, and such a shaping is necessary if the brain is to learn to do the huge number of things it does.
… The flow of neural activity is a flow of ions that occurs across synapses — tiny gaps between neurons. Those synapses where there is a lot of activity are “strengthened” — both the transmitting and receiving side of active synapses become more efficient.
… Flow across the synapses is relatively slow compared to the speed of computers: about 5 one-thousandths of a second (5 milliseconds) per synapse. A word recognition task — Is the following word a word of English? — takes about half a second (500 milliseconds). This means that word recognition must be done in about 100 sequential steps. Since so much goes into word recognition, it is clear that much of the brain’s processing must be in parallel, not in sequence. This timing result also shows that welllearned tasks are carried out by direct connections.

Neuronal Groups
… Jerome Feldman and colleagues, in the 1970’s, developed an account of “structured connectionism” — not PDP connectionism! In PDP connectionism, where all computation is distributed over an entire network and nothing is “localized” — that is, no meaning or function can be assigned to any single neuron or any small collection of neurons in the network. Only very restricted parts of the brain work that way.
… On the other hand, structured connectionism takes into account the local structure that exists in the brain. Neuronal groups (of size, say, between, 10 and 100 neurons) are modeled as “nodes” which are meaningful and which enter into neural computation. Since each neuron can have between 1,000 and 10,000 neural connections, nodes can “overlap,” That is, the same neuron can be functioning in different neuronal groups, or “nodes.” The firing of that neuron contributes to the activation of the each node it is functioning in. Though single neurons either fire or not, neuronal groups contain neurons that fire at different times, making the group active to a degree depending on the proportion firing at a given time.
… The modeling of neural computation is done over networks with nodes, connections, degrees of synaptic strength, and time lapses at synapses.

Embodiment and Simulation Semantics
… The link between body and brain is central to the concept of semantics-assimulation in NTL. Suppose you imagine, remember, or dream of performing certain movements. Many of the same neurons are firing as when you actually perform that movement. And suppose you imagine, remember, or dream of seeing or hearing something. Many of the same neurons are firing as when you actually see or hear that thing.

… Mirror neurons occur in fiber bundles connecting pre-motor/SMA cortex (which choreographs actions) with the parietal cortex (which integrates perceptions). The same mirror neurons fire when you perform an action or you see someone else performing that action. The mirror neurons are thus “multi-modal,” that is, they are active not only when acting or perceiving the same action, but when imagining that you are perceiving or performing an action. Now a word like, “grasp,” applies both to performing and perceiving grasping — that is, it is multimodal.
… Simulation semantics is based on a simple observation of Feldman’s: if you cannot imagine someone picking up a glass, you can’t understand the meaning of “Someone picked up a glass.” Feldman argues that, for meanings of physical concepts, meaning is mental simulation — that is, the activation of the neurons needed to imagine perceiving or performing an action. Thus, all mental simulation is embodied, since it uses the same neural substrate used for action, perception, emotion, etc.
… One thing we know is that not all imagination or memory is conscious, and so not all mental simulations are. That is why we typically have no conscious awareness of most such simulations.
… A Meaningful Node is a node that, when activated, results in the activation of a whole neural simulation, and that when inhibited inhibits that simulation. Inferences occur when the activation of one meaningful node, or more, results in the activation of another meaningful node.
… NTL, following the theory of simulation semantics, suggests that the neural circuitry characterizing the meaning of “grasp” is the neural circuitry in the mirror neurons that are activated when imagining either performing or perceiving grasping.
… The meaning of concrete concepts is directly embodied in this manner. There is now considerable evidence that perceiving language activates corresponding motor or perceptual areas. For example, He kicked the ball activates the foot area of the primary motor cortex.

Activation and Inhibition
&#133; A flow of ions across a synapse may either contribute to the firing of the postsynaptic neuron, or may help to inhibit such firing — depending on whether the charges of the ions are positive or negative. The activation of neural simulations constitutes meaningful thought.
… We obviously don’t think all possible thoughts at once. Indeed, most possible thoughts are either unactivated or positively inhibited most of the time.

Mutual Inhibition
… Two neuronal groups can be connected so that each inhibits the activation of the other when there is an active flow of ions of the opposite charge. This is called mutual inhibition. This occurs, for example, when there are two inconsistent, but equally available, ways of looking at a situation.
… This is common in politics, where a strict conservative worldview is typically inconsistent with a nurturing progressive worldview. That is, they are mutually inhibitory. But many people have both worldviews active in different areas of their lives, and can think of a given situation first from one worldview and then from the other. When one is activated, the other is inhibited.

Spreading activation: Neurons that fire together wire together
… Spreading activation at the behavioral level has been the mainstay of psycholinguistics for decades - NTL models link this behavior to neural structure. When two neuronal groups, A and B, fire at the same time, activation spreads outward along the network links connecting them, which we experience as a chain of thought. During learning, spreading activation strengthens synapses along the way. When the activation spreading from A meets the activation spreading from B, a circuit may be formed. The more A and B fire together the stronger the synapses forming links in circuit. As we shall see, this the basic mechanism by which primary metaphors are formed.

Neural maps
… We are born with neural circuitry that effectively activates a “map” of one part of the brain in another part of the brain. For example, the 100 million neurons coming out of the retina grow connections before birth from the retina to other areas including the primary visual cortex at the back of the brain. These connections form a “topographic map” of the retina in V1. That is, the connections preserve topology (relative nearness), though not absolute orientation or absolute distance. When neurons next to each other coming from the retina fire, the corresponding neurons fire in V1 and are next to each other in V1.
… Len Talmy (2000) has observed that spatial relations in human languages preserve topology as well. For example, containers remain containers no matter how their boundaries are stretched or contracted, and paths remain paths, no matter how they wind around. Terry Regier (1997) has constructed computational neural models of topographical maps of the visual field that can compute image schemas with topological properties, and accurately learn the words for a nontrivial range of spatial relations in a variety of languages.
Neural Binding
… Imagine a blue square. We know that color and shape are not computed in the same place in the brain: they are computed in quite different areas. Yet the blue square appears to us as a single whole — not as separate squareness and blueness. The name given to this phenomenon is “neural binding.” Neural binding is responsible for two or more different conceptual or perceptual entities being considered a single entity.

There are three types of neural bindings:
… (1) Permanent obligatory bindings, e.g., in your stored mental image of a parrot, the feathers are green. There is a permanent obligatory binding in the neural representation for the parrot image, between the neuronal groups that characterize feather-shapes and those, elsewhere in the brain, that characterize the green color.
… (2) Permanently-ready-but-conditional bindings, like the bindings in the neural structure for an election-night map on which any given state can be either red or blue depending on the outcome of the vote.
… (3) Nonce bindings that occur on the fly as they happen to arise in context.

It is not known just how neural binding operates in the brain. One hypothesis is that neural binding is the synchronous firing of nodes. Lokendra Shastri has modeled the computational structure necessary to carry out binding in such a theory.

Neural Choreography
… In general, the premotor cortex and supplementary motor area (SMA) choreograph specific actions, like grasping. Grasping has a neural structure of its own. There are, in addition, neural connections between the pre-motor/SMA and the primary motor cortex – M1. M1 is laid out topographically according to the neurons as they are connected to the body. For example, neurons connected to the hand are in the same region of M1, with neurons connected to the index finger next to neurons connected to the middle finger. The whole body is topographically connected to the neurons in M1.
… Each M1 neuronal group can perform only a simple action, like opening the elbow or pointing the index finger. In order to pick up a bottle, those simple M1 actions must be sequenced and choreographed. The premotor cortex/SMA does the choreography, having learned neural circuits that fire in complex sequential patterns. As each premotor/SMA neuron fires, a connection to M1 makes the right M1 neurons fire, which in turn moves certain muscle groups in the body. Picking up a bottle is like an exquisite ballet with choreographic instructions being carried by the connections to the neurons in M1, which individually control each little movement.
… When the bindings are in place, the Premotor/SMA Circuitry + bindings + PrimaryMotor Circuitry acts seamlessly like a single simple circuit.

Circuit Types
… NTL modeling assumes that, as our neural circuitry is being shaped by experience, certain relatively simple basic types of neural circuits emerge, as follows. The research includes ways in which circuits with these properties can be formed.
… What is important for the study of thought is not the study of precise neural circuitry, but rather the study of the kinds of computations that neural circuitry can carry out. An important topic in the neural theory of language is exactly what kinds of circuit types are necessary for human thought — for frames, image-schemas, conceptual metaphor, lexical items, grammatical constructions, and so on.
… Neural bindings play a crucial role, forming complex circuits by binding nodes in one circuit type to nodes in another circuit type.

The winner-take-all circuit:
… • Two or more subcircuits, say A and B, with mutually inhibiting connections between them.
… • When A is firing B cannot fire, and conversely.

Winner take all circuits apply, for example, to high-level “worldview” circuits that make sense in a single way of a wide range of experiences — in politics these might be conservative and progressive worldviews. You might understand a range of experiences using one world-view or the other, but not both at once.

A Note on Gestalt Nodes
… What I will call a “gestalt node” is a subcollection of neurons forming a subcircuit within a given circuit. The gestalt node acts like a traffic cop, directing activation within the circuit and directing activation into and out of the circuit. This allows the gestalt node to form a computational “unit” out of the larger circuit that it is part of; e.g., a “unit” like a frame, an event sequence, a metaphor, etc.
… Though all the neurons in the brain are ultimately linked to all other neurons by some pathways or other, or by many pathways, that does not mean that everything activates everything else. The existence of such traffic cop circuits allows the circuitry of the brain to do a vast number of special jobs.

A Schema Circuit:
… • A collection of nodes, say, A, B, C, and D and a “gestalt node” G.
… • When G is firing, all of A, B, C, and D fire.
… • When a sufficient set of A, B, C, or D is firing, G fires, which results in all other nodes firing. One especially salient node can be sufficient in some cases, or there can be a threshold where the total activation summed over all the nodes is above G’s threshold and results in G firing.
… • When G is inhibited, at least one of the other nodes is inhibited.

… Schema Circuits characterize the structure of frames. Frames are special cases of schemas. The entire frame corresponds to G and the roles correspond to A, B, C, D, etc.. Schemas circuits also characterize the circuitry that allows image-schemas and X schemas to function as schemas.
… In a gestalt, the whole is more than just the sum of its parts. Accordingly, in a schema circuit, the whole — G — cannot be inhibited and all of its parts activated. The activation of even some of the salient parts activates the whole. And the activation of the whole activates all the parts.
A Linking Circuit:
… • Two nodes, A1 and A2, a circuit L connecting A1 with A2, and G, the gestalt node of circuit L.
… • When A1 and G are firing, A2 is firing. But when A2 is firing, A1 need not be firing. Thus, activation flow is asymmetric from A1 to A2.
… • When A1 is firing and G is not, the linking circuit L is not active. (That is, G “gates” the connection L.)
… • When A1 and A2 are both firing, gestalt node G is firing and the linking circuit L is active.
Note: A1 can fire without A2 firing. This can happen if G is inhibited from firing, thus making the link L from A1 to A2 inactive. Think of G as a traffic cop regulating the flow from A1 to A2.

… Linking Circuits are used in metonymy: Within a frame F, one semantic role A may “stand for” another B. A metonymy is characterized by:
(1) A schema consisting of gestalt node F and at least nodes A, B, and X;
(2) A connection L linking A to B asymmetrically, with gestalt node G gated by X. That is, G fires only if X is firing.

For example, in The ham sandwich wants his check, the frame F is the restaurant frame, the ham sandwich plays the role Dish (A), his refers back to the entity that plays the role Customer (B), and L characterizes the metonymic link from the Dish (A) to the Customer (B), while X is the condition that the waiter/waitress identifies the Customer B primarily in terms of the Dish B. ….

Binding circuits:
… When neural binding occurs, the nodes bound together act as if they characterize the same entity: every circuit activated by one is activated by the other, and every circuit activating one activates the other.
… A common theory of binding holds that the nodes that are neurally bound fire in synch. There are other theories, and none is accepted as having been proven.
ID Links:
… You are the same person you were as an infant, though you certainly have changed. That change means that circuits characterizing you as an infant must not be the same as those characterizing you now. One suggestion for how a neural system accomplishes this uses the concept of an Essence as a semantic role of the frame for an entity. On this hypothesis, we can characterize an ID Link.

An ID Link between A and B consists of:
(1) a linking circuit from the circuit for one entity A to the circuit for another entity B;
(2) a neural binding identifying the Essence role of A and the Essence role of B.

ID links characterize connectors across mental spaces, identifying A in one space as the same entity as B in another space, even though they may have different properties in different spaces.

Two-way linking circuits:
… A two-way circuit linking nodes A1 and A2 is comprised of two opposite one way linking circuits, with a gestalt node creating a unit from the two linking circuits. Here are the properties of two-way linking circuits:
… • Nodes A1 and A2. Linking circuits L1 and L2. Gestalt nodes G1 and G2. Gestalt node G.
… • First linking circuit: From A1 to A2 via linking circuit L1, with activity directed by gestalt node G1.
… • Second linking circuit: From A2 to A1 via linking circuit L2, with activity directed by gestalt node G2.
… • The overall gestalt circuit: Linking circuits L1 and L2 with gestalt node G.
• When G is activated, both links are activated. When G is inhibited, both links are inhibited.
… Two way-linking circuits provide the kinds of connectivity used in grammatical constructions and lexical items, where there is a two-way connection between a lexical meaning and a lexical form, or a grammatical meaning and a grammatical form structure.

Mappings
Mappings are unidirectional multiple linking circuits, each governed by a single gestalt node, and with those linking gestalt nodes governed altogether by a single gestalt node. Here are some examples:

Metaphor
Metaphor mappings apply to schemas of all sorts, whether image-schemas, frames, action sequences, or narratives. They map “source domain” schemas and their roles to “target domain” schemas and their corresponding roles.

Metaphorical Mapping:
Two schemas S1 with roles A1, B1, …, and S2 with roles A2, B2, … .
Linking circuits LS, LA, LB, that respectively link schema S1 to Schema S2, role A1
… to role A2, role B1 to role B2, and so on.
Gestalt nodes GS, GA, GB, … governing linking circuits LS, LA, LB, … .
Gestalt node G governing GS, GA, GB,... .

When G is inhibited, GS, GA, GB, etc.. are all inhibited and activation is shit off in all the links. When G is activated, DS, GA, GB, etc. are all activated, and activation flows from Schema node S1 to Schema node S2 and through all the links between roles.
When Schema 1 and Schema 2 are activated, G is activated.

Mental Space Mapping:
A “mental space” M consists of circuitry used to run a simulation activated by a Semantic Structure.
A Semantic Structure SS consists of the circuitry characterizing such semantic “units” as
… frames, image schemas, X-schemas, metaphorical maps, metonymic maps, blending
… maps, etc. together with neural bindings integrating them into a whole.
'''A cross-space relation R consists of two mental spaces M1 and M2 and a semantic
structure SS with roles bound to elements of each space. '''
… A mental space mapping MSMap consists of:
… A linking circuit L from M1 to M2.
… A collection of ID Links from elements EM1[i] of M1 to elements of EM2[i] of M2.
… A gestalt node G governing L and all the ID Links.

A “space builder” is a linguistic element or construction B that activates R and G.
… For example, take the sentence If Clinton had been President of France, there would have been no scandal over his affair. The mental spaces are: M1 = The US during Clinton’s presidency with EM1(1) = Clinton and SS1 = his affair in the US, and M2 = France at that time, EM2(1) = A Clinton-correlate and the role played by EM2(1) is the President of France who has an affair in France with no scandal; L1 is the circuit that identifies A1 (the real Clinton) with A2 (the Clinton correlate ≠ Clinton). The SS indicates that M1 is taken as fitting reality and M2 is not.

Extension Circuit:
… • A semantic structure SS1, containing nodes A1, B1, C1, D1,… and a gestalt node G1 governing SS1.
… • Gestalt node G2 governing nodes C2, D2, … . … • A Linking Circuit L with gestalt node G linking G2 asymmetrically to G1.
… • Mutually inhibitory links between C2, D2, …, and C1, D1, … respectively.
… • SS2 consisting of SS1 with C2, D2, … replacing C1, D1,… .
When G is firing, SS2 is activated and SS1 is inhibited.
When G1 is firing, SS1 is activated and SS2 is inhibited.

Extension Circuits characterize radial categories (See Lakoff, 1987, Case Study 3). For example, suppose SS1 characterizes the concept of mother and SS2 characterize the concept of stepmother, where the birth frame of mother is inhibited while the marriage frame remains active.

X-schema circuit:
… • A gestalt node
… • State nodes
… • Action nodes
… • Connections, both activating and inhibiting
… • Conditional Choice nodes
… • Timing nodes

… X-schemas, or “executing schemas,” do things, via bindings that activate other circuits. Every action node is preceded and followed by a state node, with activation spreading from states to actions to states. Timing nodes coordinate the lengths of states and actions (which may be instantaneous or elongated). Iterated actions are formed by loops from the state following an action to the state preceding the action. Conditional actions are formed by gatings — cases where activations from both nodes A and A’ are needed to activate node B. Conditional Choice nodes have outputs going to two or more other nodes, with gatings that determine the choices, perhaps probabilistically.

… The gestalt node activates the initial state and the final state inhibits the gestalt node. Actions typically have initial and final states, initiating and concluding actions, central actions, and may have purposes. A purposive action is one with a desired state. The purpose is met if the desired state is active after the central action, and if so, the action is concluded. Each action can be neurally bound to the gestalt node of another complex Xschema, to produce quite complex actions.

… X-schemas characterize the structures of states and actions, referred to as “aspect” in linguistics. Aspects can be durative or instantaneous, stative or active, completive or open-ended, iterative or non-iterative.
… When connected to the body via the primary motor cortex, pre-motor/SMA Xschemas can carry out actions. X-schemas can also define scenarios within frames or narratives and carry out chains of reasoning, by sequentially activating mental simulations.

Blending Maps:
… Blending maps are complex maps: They take two or more sources and map them to a single target. The source has two or more gestalts, G1, …, Gn. The target has a single gestalt, H. The linking circuits consist of either neural bindings or identification links (with bindings of essences).

… Examples will be given below.

Conceptual Blends
… Conceptual blends are carried out by blending maps, where the crucial circuitry is neural binding circuitry. We will discuss this further below. In short, blending can be seen as a form of complex binding.

… The point of these characterizations of circuit types is that, in NTL, one has to be explicit about the computational properties of neural circuitry. Any cognitive analysis must be able to be carried out by the brain and by the relatively simple circuit types of this sort. As we shall see, different mental operations require different types of neural circuitry that performed very specific neural computations.

Neural Systems Are Best-Fit Systems
… It is a common cognitive phenomenon that a fact that fits an overall conceptual organization is remembered better than a fact either in isolation or one that contradicts an overall conceptual organization. Ideas make sense when they fit a whole system of ideas.

… Similarly, a linguistic compound makes sense when it fits into a coherent context. '''
Take the classic example of “pumpkin bus” — coined on a school outing. There were two buses and the road home passed a pumpkin patch. One of the buses was designated to stop there for students who wanted to buy a pumpkin. It was called the “pumpkin bus,” and the compound was instantly understandable because it fit the context.”
… Compare two sentences: “Bill drank a soda” and “Bill drank an elephant.” To get the meaning of the sentences, you need to do a mental simulation, in which Bill is drinking and a frame is activated in which a soda is bound to the patient role in the frame of drinking, which requires that it be a liquid and consumable, which it is. In “Bill drank an elephant,” again the drink frame requires a consumable liquid. Since an elephant is neither — binding the concept of an elephant to the patient’s role in the drink scenarios runs up against neural inhibition. However, context may change things. Elephant is a brand of Danish beer, and so the sentence may refer to Danish drinking experience. Or second, one could imagine a context in which an elephant was sacrificed by being cut up and put in a blender and liquefied so that one could drink it.
… What determines “fit”? Maximizing the number of overall neural bindings — including context and overall knowledge — without contradiction that is, without encountering any mutual inhibition. By maximizing bindings you engage as much as possible of what is already in the brain. And making maximal use of strong synaptic weights, that is, circuitry that has the highest prior probability of being activated.

Image schemas and Cogs
… Terry Regier (1997) has constructed a neural computational model for how a range of spatial relations concepts can be computed by a neural network that shares certain propoerties with human brains. Narayanan (1997) has constructed a neural computational model of the structure of events, that is, X-schemas. Dodge and Lakoff (2006) have speculated on many of the details involved. Gallese and Lakoff (2005) have shown that certain action circuitry has the structure of frames. They have further speculated that the meanings of grammatical elements and constructions are characterized by “Cogs,” that is, secondary neural structures (e.g., pre-motor/SMA cortex) that bind to structures in primary cortex, e.g., motor and visual. This would explain why grammatical meanings are “abstract” in the sense that they have a very general structure but lack specific details.

… We are now ready to discuss how all of this changes old metaphor theory into the neural theory of metaphor.

The Old Theory
Metaphors We Live By was written back in 1979, before the era of brain science and neural computation. Nonetheless, certain results from that era have stood the test of time: …

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ATTENTION: Here about 26 inches of Lakoff “The Old Theory”, have been omitted, because not really relevant to Henry Gurr “Theory of How our mind Works”.
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… Thus, activating a metaphor activates very complex integrated brain circuitry, and a given node may occur in many circuits made active by the metaphor. The more integrated the circuitry activated by the metaphor mapping, the better the “fit” of the metaphor to other brain structures. A vehicle used for travel is typically a container, which is the same as the container in the metaphor A Relationship is A Container.

A metaphor mapping is a complex circuit which, when activated, activates many other circuits via linking and binding circuitry. This makes possible metaphorical inferences: Source domain inferences that are mapped combine with target domain knowledge via binding to produce new inferences: If lovers are “stuck” in relationship, if the relationship isn’t “going anywhere,” then they are not making progress toward common life goals. If the lovers are “going in different directions,” then they may not be able get to the same destinations, which means metaphorically that their common life goals may be inconsistent.

This Above Discussed => “Neural Theory of Metaphor” (NTL) perspective provides a very different way of thinking about such complex metaphors. The brain is a best-fit system. Inferences are new activations that arise via prior activations. Bindings and linkings form integrated circuits that result in activations that arise via prior activations. This bindings and linkings give rise to inferences.

Consider our existing conceptual system where:
(1) A Relationship is a Container,
(2) A Vehicle is a Container in which the Travelers are close together,
(3) Intimacy is Closeness,
(4) Lovers are intimate,
(5) A Vehicle is an Instrument for Travel,
(6) and Lovers are Travelers.

Container is (1) names the same neural structure as Container in (2).
Closeness in (2) names the same neural structure as Closeness in (3)
Intimacy in (3) names the same neural structure as Intimacy in (4)
Vehicle in (5) names the same neural structure as Vehicle in (2)
Lovers in (4) names the same neural structure as Lovers in (6)
Travelers in (6) names the same neural structure as Travelers in (2)

The result is a very tightly integrated neural system—a system that fits together very well. The Love Is a Journey metaphor mapping fits our knowledge, including primary metaphors like (1) and (3) and commonplace knowledge like (2), (4) and (5).

Primary Metaphors The neural theory of metaphor (NTM) got its real impetus from three Berkeley dissertations done in 1997 — by Srini Narayanan, Joe Grady, and Christopher Johnson. Narayanan’s dissertation was key. He modeled metaphors as neural mappings and formulated certain metaphors for international economics. He then showed that the results of source domain inferences from the domain of physical motion and action are mapped onto the international economics target domain, interact with the logic of the target domain and produce metaphorical inferences.

Johnson studied metaphor acquisition in young children and found 3 stages:
Stage (1) source domain only;
Stage (2) experiences where the source and target domains are both active (“conflated”); at this stage, children learn to use source domain words with target domain meanings and grammar, then later
Stage (3) children use the words metaphorically, with nothing from the source domain present.

Putting together the Johnson and Narayanan results yields the following hypothesis: In situations where the source and target domains are both active simultaneously, the two areas of the brain for the source and target domains will both be active. Via the Hebbian principle that Neurons that fire together wire together, neural mapping circuits linking the two domains will be learned. Those circuits constitute the metaphor.

Grady called such metaphors “primary metaphors” and observed that they are learned by the hundreds the same way all over the world because people have the same bodies and basically the same relevant environments, and so will have very much the same experiences in childhood in which two domains are simultaneously active, and so will learn neural metaphorical mappings linking those domains naturally, just by functioning in the world. Just living an everyday life gives you the experience and suitable brain activations to give rise to a huge system of the same primary metaphorical mappings that are learned around the world without any awareness.

By best fit, different cultural frames will combine with those primary metaphors and give rise to different metaphor systems. The Love Is a Journey metaphor is a good example. The primary metaphors that ground the Love Is a Journey metaphor are:
… • Purposes are Destinations: Every day there is a correlation between achieving a purpose and reaching a destination, as when you have to go to the refrigerator to get a piece of fruit or a cold beer.
… • Difficulties are Impediments to Motion: A difficulty is something that inhibits your achievement of some purpose, which is metaphorically reaching a destination. Hence, difficulties are conceptualized metaphorically as impediments to motion to a destination.
… • A Relationship Is a Container (a Bounded Region of Space): People who are closely related tend to live, work, or otherwise spend time in the same enclosed space — you family in your home, your co-workers at the office, and so on.
… • Intimacy is Closeness: The people you are most intimate with are typically the people you have spent time physically close to: your family, spouse, lover, and so on.
In each case, a correlation in experience is realized in the brain as the co-activation of distinct neural areas, which leads to the formation of circuits linking those areas.
A Structural Prediction.
… This Neural Theory of Metaphor, says that complex metaphors that are extensions of existing primary metaphors bound together should be easier to learn and understand than conceptual metaphors that are totally new — since they just involve new binding and other connecting circuitry over existing conceptual metaphors. They should also seem more natural. ''' Take, for example, the sentence My job is a jail. (1) A jail is restricts someone freedom of motion to destination. …
… This Neural Theory in general predicts that the most immediate component metaphors for a complex metaphor will be activated and used in the mapping. In short, in most cases, new conceptual metaphors that are easy to learn and make sense of are using conceptual mappings that pre-exist, frame-based knowledge that pre-exists, and adding connections in the form of circuitry that binds, links, maps, extends, and forms gestalts.

A Processing Prediction
… This Neural Theory of Metaphor makes an important prediction in the case of conventional conceptual metaphorical mappings that are realized by fixed brain circuitry. When you hear a metaphorical expression, the literal meanings of the words should activate the source domain circuitry and the context should activate the target domain circuitry, and together they should activate the mapping circuit. The result is an integrated circuit, with activation of both source and target domains and processing over both at once. Thus, understanding language that makes use of a conventional conceptual metaphor should take no longer than normal frame-based Nonmetaphorical Processing. “
This result has been shown over and over, as in the example, My job is a jail.

… The neural theory thus contradicts old two-step theories (prior to conceptual metaphor theory) that claim that the source domain is processed first and then the mapping operates to process the target domain. Time of processing studies contradict this view.

Asymmetry
… Each neuron fires asymmetrically, with the flow of ions from the cell body down the axon, spreading out from there. Different neurons have different firing capacities depending on the receptors at the synapses that regulate ion flow. Those neurons that fire more tend to develop greater firing capacities. And those involved in physical bodily functioning tend to fire more. For this reason, the metaphorical maps learned are asymmetric and tend to have physical source domains (though some have social source domains).

The literature abounds with obvious examples.
… • More Is Up: Our bodies are constantly monitoring physical height more than computing abstract quantity.
… • Affection is Warmth: Temperature is always there to be monitored; affection isn’t.
… • Intimacy Is Closeness: We constantly monitor how close we are to objects, more than we judge intimacy. …

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ATTENTION: Here about 16 inches of Lakoff’s “Examples” and “Conceptual metaphors”, have been omitted, because not really relevant to Henry Gurr “Theory of How our mind Works”.
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Inferences
A meaningful node in a neural circuit is a node that can activate a mental simulation.

An inference occurs when:
… • the activation of a collection of meaningful nodes (the antecedent situation) in a neural circuit leads to the activation of one or more other meaningful nodes (the consequence)
… • and when the activation of the antecedent nodes is necessary for the consequence
… • and when the inhibition of one or more consequence nodes results in the inhibition of one or more antecedent nodes.

Inferences are simply consequences of the meaningfulness of nodes in simulation semantics, the spreading of activation, and best-fit constraints (the consequences fit the antecedents best). Recall that the maximization of binding is one of the characteristics of the best-fit property of any neural system. In short, maximizing binding can lead to inferences.

Metaphorical inferences
A metaphorical inference occurs when: …

• a metaphorical mapping is activated in a neural circuit, • there is an inference in the source domain of the mapping, • and a consequence of the source domain inference is mapped to the target domain, activating a meaningful node. For example, suppose the sentence is We’re driving in the fast lane on the freeway of love. In the travel domain, driving in the fast lane on the freeway activates the inferences that (1) the vehicle the travelers are in is going a lot faster than usual, (2) the driving is exciting and (3) it can be dangerous (the travelers can suffer physical harm). “Freeway of love” activates the target domain of love and source domain of travel, resulting in the activation of the Love Is a Journey metaphorical mapping. The metaphorical inferences are that

(M1) the relationship the lovers are in is developing a lot faster than usual, (M2) the development of the relationship is exciting, and (M3) it can be dangerous (the lovers can suffer psychological harm). These inferences are activated when the circuitry is activated in the processing of the sentence. The totality of source domain inferences does not have to proceed before any of the target domain inferences. Source domain inferences will be mapped as soon as they are activated.

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ATTENTION: Here about 30 inches of Lakoff “Mapping Gaps”, “Image-schema Preservation”. “Mental Spaces”, “Binding”, “Metaphors versus blends”, Optimality of Blending” “Better Analyses with Metaphoric Blends”, “Metaphoric Inferences” and “Mapping Gaps”, have been omitted, because not really relevant to Henry Gurr “Theory of How our mind Works”.
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Mental Spaces
A “mental space” from an NTL perspective is a mental simulation characterizing an understanding of a situation, real or imagined. The “space” is not a specific place in the brain, but rather the totality of the neural circuitry used wherever in the brain it is located. The entire space is governed by a gestalt node, which makes the mental space a “unit” which, when activated, activates all the elements of the mental space.

Good Reason:
If an element appears in the blend, it should have meaning. And if it arises by inference, it will be tied into the logic of the blend. Since blending maps apply to simulation spaces to yield another simulation space, and since simulations get meaning through their embodiment, this follows immediately.
… • Metonymic Tightening: Relationships between elements from the same input should become as close as possible within the blend. For instance, Western images of personified Death often depict the figure as a skeleton, thus closely associating the event of death with an object that, in our more literal understandings, is indirectly but saliently associated with it. When there is a neural binding between A and B, all the circuitry activating and activated by either A or B act together as if A and B were a single entity. This is “tightening.” Since blending maps contain identifying linking circuits, which contain bindings, they give rise to “tightening.” [<A form of increasing coherence.] In the case of the Grim Reaper discussed by Fauconnier and Turner, a commonplace metonymy is activated: The Cause Stands for the Result. Here the Cause is Death and the Result is the Skeleton. The Blend has the following structure …

Emergence
Emergence is the occurrence in a blend of an entity or proposition that does not exist in any of the blend “inputs.” Emergence is explained by inference in neural systems. Blending maps and other maps and bindings across conceptual structures can give rise to inferences not present in any “input.”
… ….Consider the example, “In France, Clinton’s affair wouldn’t have mattered.” In the blend target, Clinton, the American Chief Executive is identified with the position of the French Chief Executive in France. Since the French don’t care about politicians’ sexual liaisons, we get the inference that “In France, Clinton’s affair wouldn’t have mattered.” This “emergent” inference does not occur in either of the inputs: France, where Clinton was not chief executive of France, and the US, where Clinton’s affair did matter. It arises by maps and inferences arising from simulations when those mapping circuits are activated. …

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ATTENTION: Here about 26 inches of Lakoff “Better Analyses with Metaphoric Blends”, “The Role of Metaphor in Abstract Concepts”, “Metaphor in Systems of Thought”, Metaphorical Language”, and “The Use of Metaphoric Language” have been omitted, because not really relevant to Henry Gurr “Theory of How our mind Works”.
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Better Analyses with Metaphoric Blends
… …. Certain classic analyses in the blending literature which are seen as nonmetaphoric blends really should be seen as metaphoric blends. For example, there is a common metaphor in which Breaking a Record Is Winning a Race Against the Previous Record-holder. Thus, a few years ago when Mark McGwire and Sammy Sosa were both attempting to break Babe Ruth’s home run record, the press represented the situation metaphorically as a race with Ruth — and each other. In the daily papers, McGwire and Sosa were represented by how many games they were “behind” or “ahead” of Ruth’s 60 home run performance. They were spoken of as “catching up” or “falling behind.” The classic blending analysis misses this metaphor.
… The same metaphor occurred in the situation many years back when the yacht Great America tried to break the San Francisco to Boston record through the Northwest Passage set a hundred years before by the yacht Northern Light. Accordingly, the metaphor had the Great America in a “race” with the Northern Light — even though they sailed 100 years apart. The newspapers daily reported how many days “ahead” of the Northern Light the Great America was. Again, the classic blending analysis misses the metaphor. The moral: A neural theory analysis forces us to notice analyses we might otherwise miss. The reason is this. As soon as record-breaking is at issue, the general metaphor will be made active. If it is used, then there is a better fit than if it is not used. In short, the best-fit principle by which neural networks operate prefers such analyses. Remember: the more existing high-activation-weight circuitry that is activated, the better the fit between the current situation and the prior state of the brain. This may sound counterintuitive. If you are a scientist trying to give an analysis of some data, you use Ockham’s Razor—the minimum that you need to hypothesize. So if you are a traditional descriptive linguist seeing your job, not as involving the brain, but as writing down the shortest possible written analysis of some sentences you encounter, you try to hypothesize the minimum. You don’t hypothesize a primary metaphor as part of the analysis unless some element of the sentence forces you to. But if you are a cognitive linguist or any other cognitive scientist whose job is to start with the brain, then you start with how the brain works and what is in it when you start. That includes all the primary metaphors and a whole conceptual system. And you start with the best-fit property, and that affects the analysis you give of what the brain would be doing. Let’s consider another class of cases with the same moral. There are two widely used metaphors rarely analyzed as such. …

The Use of Metaphoric Language
… ….The neural theory of metaphor also makes sense of the use of metaphoric language in context. We know that metaphor does not reside in words [printed on paper] but in ideas [that are perceived mentally]. This is especially clear from cases of metaphorical ambiguity, where the same words evoke different readings using different metaphors. “It’s all downhill from here” may in a given situation mean “it’s getting easier” (Ease of Action Is Ease of Motion) or “it’s getting worse” (Down is Bad). Either conceptual metaphor can apply to the spatial meaning of “down” in “downhill.” In a neural account, both metaphors activate to the spatial meaning of “down,” but the metaphors are mutually inhibitory. Only one can be activated, depending on context.
… Consider a metaphorically ambiguous sentence like “Let’s move the meeting ahead two days.” If uttered on a Wednesday, it could refer to either Monday or Friday, depending on which metaphor for time is used — moving-ego or moving-time. Since they are mutually contradictory, the metaphors are mutually inhibitory. The neural theory can explain Lera Boroditsky’s classic experiment at San Francisco airport. She showed that, for people waiting for a plant to come in, the motion of the plane toward them primed the moving time metaphor and they gave the answer “Monday,” two days ahead of the moving time. Those who were on the plane and coming off were primed by being on the moving object, and they gave the answer “Friday,” two days ahead of the moving ego.
… The neural theory explains the priming in these cases. The two time metaphors are mutually inhibitory. What tips the scales is the priming – the neural activation of either a moving time or moving ego in the spatial domain.

What makes metaphorical language meaningful?

Language is meaningful when the ideas it expresses are meaningful. Conceptual metaphors are meaningful when they are grounded. They are grounded, first, by source domain embodiment, and second by the embodiment of the source and target domains of the primary metaphors being used.

Summary: What Does the Neural Theory Provide?
… The neural theory provides a much better understanding of how thought and language work and of how metaphorical thought fits into the picture. It also provides explanations for a host of phenomena. And it changes how one does metaphor analysis — and redefines what metaphor analysis is.

The neural theory explains:
… • Why there should be conceptual metaphor at all; what conceptual metaphors are physically; why we have the metaphors we have, how the system is grounded, and why certain conceptual metaphors are widespread around the world.
… • How metaphorical inferences work; why they should exist; how they operate in context, and how they interact with simulations.
… • All of the properties of the old metaphor theory, the theory as described by myself and Mark Johnson in Metaphors We Live By and by myself in the essay “The Contemporary Theory of Metaphor.” • How metaphors can function indirectly in the characterization of abstract concepts.
… • How a small number of metaphors can organize a whole system of thought and become the principles on which one lives one’s life.
… • How metaphorical language works as a simple extension of non-metaphorical language.
… • Why metaphors differ from blends, and why blends do not do the job of metaphors. The neural theory also clarifies what the study of metaphor is about, namely,
… • Showing how metaphorical understanding is grounded in basic human experience via primary conceptual metaphors; • Showing how primary metaphors contribute to complex conceptual metaphors;
… • Showing how both primary and complex metaphors contribute to the meanings of words, complex expressions, and grammatical constructions;
… • Showing how conceptual metaphor plays a role in abstract concepts and overall conceptual systems (as in politics, philosophy, and mathematics);
… • And, finally, showing how conceptual metaphors contribute to the understanding of language and other uses of symbols.

How Does a Metaphor Analyst Make Use of All This?

… Metaphor analysts rarely know neural computation, and they shouldn’t be expected to. The Neural Theory of Language Project has figured out a way to let linguists be linguists and not computer or brain scientists. We have invented a notation that correlates with circuitry with the appropriate computational properties, but can be used by analysts without worrying about the computational details. Thus, consider a notation like:

Metaphor: LoveIsAJourney
Source Domain: Journey
Target Domain: Love
Mapping:
… Travelers —> Lovers
… Vehicle —> Relationship
… Destinations —> LifeGoals
… ImpedimentsToMotion —> Difficulties
Evokes:
… Purposes Are Destinations Metaphor,
… ….With Destinations = Self.Source.Destinations
… ….Purposes = Self.Target.LifeGoals

… Difficulties Are Impediments to Motion Metaphor,
… ….With Impediments to Motion = Self.Source.ImpedimentsToMotion
… ….Difficulties = Self.Target.Difficulties

… Intimacy Is Closeness Metaphor,
… ….With Closeness = Self.Source.ClosenessOf TravelersInVehicle
… ….Intimacy = Self.Target.IntimacyOfLovers

… A Relationship Is A Container Metaphor,
… ….With Container = Self.Source.Vehicle
… ….Relationship = Self.Target.Relationship

… The statement that this is a metaphor corresponds to the appropriate mapping circuit. The name of the metaphor corresponds to the appropriate gestalt node. The arrows (“—>”) correspond to linking circuits. The statement of the mapping specifies what maps to what. The equal signs (“=”) specify the neural bindings. The “evokes” statement sets up linking circuits activating the “component” metaphors, with neural bindings between LoveIsAJourney (called “Self” in the formalism) and the various component metaphors. There can be, and often is, a chain of “evokes” statements that ultimately lead to primary metaphors that ground the metaphor system in experience.
… ….This formalism is easy for metaphor analysts to learn and use. It can be converted by algorithm to computational neural modeling programs that, say, take a sentence as input and produce an analysis as output. There are corresponding formalisms for grammatical and lexical constructions, metonymies, frames, image-schemas, and so on. The technical term for the notational system is Embodied Construction Grammar .

Conclusion
This is where we are in the Neural Theory of Metaphor (NTL) as of January 2009. We have a reasonable early approximation to the kinds of computations that neuronal groups must perform to characterize frames, metaphors, metonymies, mental spaces, and blends. A parsing program to use these kinds of computations is being constructed. Thousands of frames and hundreds of metaphors have been analyzed informally to date and can readily be converted to the notation system. And we know enough about natural metaphor learning to understand how the metaphor system gets built up just by functioning in our everyday lives.”
… END George Lakoff’s NTL Article. References have been omitted

''' NOTE: Readers Should Be Aware That George Lakoff’s Above Article Is A Continuation of (and Builds Upon) His Previous Work, Such As George Lakoff and Mark Johnson’s =>
… “Metaphors We Live By” in 1979.
… “Philosophy In The Flesh: The Embodied Mind And Its Challenge To Western Thought.” in 1999.

Z) “The Information: A History, A Theory, A Flood.” By James Gleick Excerpt From EPILOG, About 4 Pages Down. => Underlined below agrees with Henry Gurr's “Explanation (Theory) How Our Mind Works.
... “The birth of information theory came with its ruthless sacrifice of meaning-the very quality that gives information its value and its purpose. Introducing The Mathematical Theory of Communication, Shannon had to be blunt. He simply declared meaning to be "irrelevant to the engineering problem." Forget human psychology; abandon subjectivity.”
... “He knew there would be resistance. He could hardly deny that messages can have meaning, "that is, they refer to or are correlated according to some system with certain physical or conceptual entities." (Presumably a "system with certain physical or conceptual entities" would be the world and its inhabitants, the kingdom and the power and the glory, amen.) For some, this was just too cold. There was Heinz von Foerster at one of the early cybernetics conferoences, complaining that information theory was merely about "beep beeps," saying that only when understanding begins, in the human brain, "then information is born-it's not in the beeps." “
... “Others dreamed of extending information theory with a semantic counterpart. Meaning, as ever, remained hard to pin down. "I know an uncouth region," wrote Borges of the Library of Babel, "whose librarians repudiate the vain and superstitious custom of finding a meaning in books and equate it with that of finding a meaning in dreams or in the chaotic lines of one's palm.” “
... “Epistemologists cared about knowledge, not beeps and signals. No one would have bothered to make a philosophy of dots and dashes or puffs of smoke or electrical impulses. It takes a human-or, let's say, a "cognitive agent"-to take a signal and turn it into [meaningful] information. "Beauty is in the eye of the beholder, and information is in the head of the receiver," says Fred Dretske. At any rate that is a common view, in epistemology-that "we invest stimuli with meaning, and apart from such investment, they are informationally barren." But Dretske argues that distinguishing information and meaning can set a philosopher free. The engineers have provided an opportunity and a challenge: to understand how meaning can evolve; how life, handling and coding information, progresses to interpretation, belief, and knowledge [And Meaning].”

…Our Problem Solving Brain => In The Process Of Generating (Constructing, Creating, Forming, Assembling, Building, Making, Producing), These Optimal (Best or Near Best) Problem Solutions => These MEANINGS ARE ALSO THERE, Right-Before-Our-Mind’s-Eye.
For Full Explanation Click Here, and AFTER Page Comes Up, Scroll Down to Please learn to quickly “spot” these. .
... “Still, who could love a theory that gives false statements as much value as true statements (at least, in terms of quantity of information)? It was mechanistic. It was desiccated. A pessimist, looking backward, might call it a harbinger of a soulless Internet at its worst. "The more we 'communicate' the way we do, the more we create a hellish world," wrote the Parisian philosopher-also a historian of cybernetics-Jean- Pierre Dupuy.”
Gleick FootNote =>
I take "hell" in its theological sense, i.e., a place which is void of grace-the undeserved,
Click Here For GoogleBook Version Of James Gleick’s Book. AFTER This Comes Up, Scroll To EPILOGUE, Then Down 4 Pages For Above Excerpts. Underlineds above, agrees with Henry Gurr's “Explanation (Theory) How Our Mind Works”.
NOTE: Serious Researchers may ask me for => FullText}HistoryTheoryFlood=gleick-the-information-535-paginas

T) “What Is Sketch Engine?” [Information About & Uses of Sketch Engine, are shown here, to help readers know of its unique abilities. Available as a Free Trial. ]
... Sketch Engine is the ultimate tool to explore how language works. Its algorithms analyze authentic texts of billions of words (text corpora) to identify instantly what is typical in language and what is rare, unusual or emerging usage. It is also designed for text analysis or text mining applications.
... Sketch Engine is used by linguists, lexicographers, translators, students and teachers. It is a first choice solution for publishers, universities, translation agencies and national language institutes throughout the world.
What Exactly Can Sketch Engine Do?
LINGUISTS AND LEXICOGRAPHERS
Sketch Engine processes texts of billions of words and, within seconds, finds instances of the word, phrase or phenomenon and presents the results in the form of Word Sketches, concordances or word lists.
TRANSLATORS
Aligned parallel corpora are a source of translation suggestions as produced by real translators. Word Sketches help identify idiomatically correct word combinations and help use words like native speakers do.
TERMINOLOGISTS
Sketch Engine’s next generation term extraction and bilingual term extraction combine statistics and linguistic analysis to yield unprecedented quality. Extracted terms require very little manual cleaning or post-processing, if any at all.
TEXT ANALYSIS
Perform co-occurrence analysis, term extraction or generate frequency lists which take advantage of morphological analysis and part-of-speech tagging.
PRODUCT NAMING
Get ideas for product names and check the feelings and ideas they invoke. Check how such words are used by your competitors.
TEACHERS AND STUDENTS
Word Sketch and Concordance are the ideal tools to quickly understand how a word or phrase is used in context. Or try SKELL!
https://www.sketchengine.eu/

NOTE1: Readers Should Be Aware That There Are FOUR Continuation Pages Of “Supplementary Information” Which Are =>
…
1) Supplementary Information1, for Henry S Gurr’s Unified Panorama View Into How Our Mind Works.
…
2) Supplementary Information2, for Henry S Gurr’s Unified Panorama View Into How Our Mind Works. This is the WebPage you are reading right now.
…
3) Supplementary Information3, Featuring Professor James F Ross’ Book ‘Portraying Analogy’ … Which Very Much Is Working With “Metaphor” …. AND Is Relevant To (And Supports), Henry S Gurr’s Unified Panorama View Into How Our Mind Works.

4) Supplementary Information4, for Henry S Gurr’s Unified Panorama View Into How Our Mind Works.

FromC&pFmSupplm1Hsg27Apr19,2Jun19,25Jun22,24-25April24, ~5-13May24. + EditRpg18May19
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