Letter to Thad (Why has AI stalled)
The field of Artificial Intelligence (AI)I currently boasts successes in various efforts (i.e. IBM’s Big Blue that beat the world champion, Garry Kasparov in chess; Brooks, R.; Spectrum IEEE.org, October 2021, pg. 49) or DeepMind defeating Go champion Lee Se-dol (Thompson, N., Greenwald, K, Lee, K.; Manso, G.; Spectrum IEEE.org, October 2021, pg. 51) or the rapid improvement in spoken word recognition, and the analyzing of medical scans and autonomous automobiles. Since 1956 (reference here), AI has become invaluable to both business and research. But there has been no real advancement in the way AI “thinks” and many current investigators into AI are still frustrated by this lack in AI’s ability to “think like people”. This article points to three specific ways in which researchers have unwittingly limited the possible outcomes of their studies. By disregarding these factors they’ve created for themselves a morass of false turns and dead-ended paths. These factors are: 1) assuming and modeling a generalized intelligence (‘g’) instead of multiple intelligences. 2) over-looking the importance of emotional intelligence in learning, and 3) ignoring any possible role that brainwaves may contribute to cognitive processing.
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- Assuming and modeling a generalized intelligence (‘g’)
instead of multiple intelligences
Currently, AI’s processes are all done with what psychologists think off as “bottom-up processing,” (reference here) or what is more commonly known as inductive reasoning. Al uses digital code and rapid memory and retrieval to scan examples and quickly match them with past attempts that led to a successful outcome. With this binary based process (digital 0’s and 1’s), AI has been able to defeat world champions not by using the variety of intelligences humans are capable of but by the rapid deployment of basic processes. The speed of their processes is far greater than what the human brain can match. But they are still not capable of abstract thought or deductive reasoning. Bottom-up processing can understand and draw conclusions from a set of data but, unfortunately, the amount of data needed to train all but the simplest neural-networks is astronomical and the cost in energy is extremely prohibitive.
AI’s calculations can be applied successfully to all sorts of difficult problems and their solutions are fast, effective but not abstract as human thinking can be. If our goal is for AI to think like people, it must have equivalent structures and processing capabilities. A toddler applies its skills to novel situations because the calculations are concrete but the ability to generalize is an abstract process. Perhaps we can design programs that mimic higher order reasoning that develops in humans as well as self-awareness but our attempts to do so have led to unavoidable problems such as the overwhelming need for power and data to train the AI or its catastrophic forgetting (reference here) while training for a new task.
Unlike AI research, our understanding of human intelligence processes and brain functioning has changed considerably since 1956.
“Psychologists have long debated how to best conceptualize and measure intelligence (Sternberg, 2003). These questions include how many types of intelligence there are, the role of nature versus nurture in intelligence, how intelligence is represented in the brain, and the meaning of group differences in intelligence.” Introduction to Psychology – 1st Canadian Edition. Authors: Charles Stangor and Jennifer Walinga
In the early 1980’s Howard Gardner published the following definition:
An intelligence is the ability to solve problems, or to create products, that are valued within one or more cultural settings.” -- Howard Gardner, FRAMES OF MIND (1983)
With this definition and worldwide study into what diverse cultures have determined what was ‘smart’, Dr. Gardner and his colleagues proposed identifying seven, distinct intelligences: Verbal-Linguistic, Mathematical-Logical, Visual-Spatial, Intrapersonal, Interpersonal, Bodily-Kinesthetic, and Musical-Rhythmic. This theory was well received and very soon thereafter became basic in the field. Although not many innovations have been derived from this theory yet, its overarching concepts have become pivotal in the understanding of intelligence.
There are many ways in which we are naturally smart. There are the familiar intelligences we know from IQ tests (verbal, quantitative and visual/spatial). But we can also think smart with music, body movement and emotional reasoning.
Every physiologically and mentally typical person acquires in childhood the ability to make use, as both sender and receiver, of a system of communication that comprises a circumscribed set of symbols (e.g., sounds, gestures, or written or typed characters). In spoken language, this symbol set consists of noises resulting from movements of certain organs within the throat and mouth. In signed languages, these symbols may be hand or body movements, gestures, or facial expressions. By means of these symbols, people are able to impart information, to express feelings and emotions, to influence the activities of others, and to comport themselves with varying degrees of friendliness or hostility toward persons who make use of substantially the same set of symbols. https://www.britannica.com/topic/language#ref27156
Emotional intelligence does not reason the same way verbal reasoning does. The rules and steps in their problem-solving processes are notably different. Our feelings have their own logic (based upon a fractal that starts with the duality: Attract/Repulse), and their own specific language. Verbal Intelligence starts with the duality of Yes/No. Spatial Intelligence with Here/There or Near/Far. All our intelligences have their own languages, and each language is based on an individual, primal duality. For the emotional intelligences this language begins with behavior. Our first language is not spoken. Our first language is behavior, even the single cell animal displays the primal duality as Attraction / Repulsion.
2) The impact of Emotional Intelligence has Upon Our Ability to
Learn and Perform Abstract Reasoning
All forms of life, even the single cell varieties, are learning and responding bio-machines. In his book, The Biology of Belief, Bruce Lipton[1], a noted cellular biologist, described how the single cell perceives and makes judgments about its environment. He told how the single living cell will either move toward a food supply or away from a toxin introduced to its neighborhood. It senses its environment and responds, hopefully, in a beneficial way. The single cell critter learns and reacts in a goal directed or purposive manner. Even the novice student of psychology should recognize this as “Stimulus > Response” (S>R), the basic unit of learning. All complex learning and deep contemplation rest on this foundation: S>R.
Goal directed behavior is displayed by all the multi-celled organisms evolved from the single cell. All life learns and reacts to survive.
That all behavior is purposive has been a key axiom of psychology since the 1940’s.[2] And, as the theory of natural selection suggests, the efficiency, accuracy, and predictive validity with which any form acts will increase its survival equivalently, allowing it a greater probability of passing on its characteristics to the next generation.
Even an embryo displays goal-directed responses to increase the likelihood of its success. Dr. Lipton also illustrated how the fetus reacts to its mother's emotional state during pregnancy. The mother’s stress level will cause the baby to develop in skeletal/muscular mass, coordination, and “life-saving reflex behavior” when the mother’s stress is high. Or the embryo will invest its resources in internal growth and learning when their mother’s stress is low.
In other words, if their mother perceives the world as hostile, frustrating and/or frightening, the embryo will devote more of its developmental energy to increasing its abilities to be strong, agile, and quick to react, or if the mother is relaxed and at peace in her world, the fetus will develop more of its ability to learn and heal. The fetus responds to its mother’s reactions in a way to increase the probability of its success once born, thus setting their balance up or down along the scale between “brain and brawn.” In effect, the embryo prepares itself for the world it perceives it will be delivered into. All life strives to understand and react correctly to its environment.
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Exclusively using one intellectual modality and language to teach about another is deficient. One modality does not completely translate into another. It can enhance and edify but not replace it.
So, why are researchers still using the concept of a single intelligence (denoted by a small ‘g’) in their studies? Why are we continuing to search for an intelligence we know doesn’t exist? It distorts scientists’ thinking and causes biases which misdirects efforts. One way these biases have impacted researchers is to lead them to think that some combination of Verbal-Linguistic and Mathematical-Logical intelligences must be the principal part of ‘g” or general intelligence. In fact, the emotional intelligences historically were described as unreliable and irrational and attributed mainly to women when, in fact, they are our intellectual foundation. The best single predictor of school success is verbal intelligence, but the best predictor of life success and satisfaction is emotional intelligence (Goleman Reference here). This misjudgment has led researchers to attempt the creation of higher order neuro-networks without their foundations.
Humans are not thinking creatures with emotions on the side that often are irrational and difficult to work with. In truth, we are feeling beings with some specific higher order processing abilities added to our basic thinking structures, which are a majority emotional. The brain’s structure developed over eons, building itself up layer by layer. In general, we talk about three main layers of the brain as: 1) Survival (brain stem, pons, cerebellum; reptilian), 2) Emotional, (mid-brain; mammalian) and 3) Executive (pre-frontal and frontal lobes; primate to Homo-Sapien). Each layer is built upon the previous and extends the pre-existing functions. Emotions evolved extending the physical sensations that make up our sensory feedback from our physical world. And then abstract thinking evolved from emotional intelligence in an effort to understand and improve our emotional responses to our environment each layer assisting the previous in being successful. Our ability to think abstractly, verbally, and quantitatively were all built upon the logic of feelings, feelings on sensation, music on feelings and sensations.
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We are not born with the rich set of emotions we have as adults. As we grow and then age, we create many names for new feelings. Like the colors of a rainbow, our adult emotions exist on a spectrum and vary in both intensity, direction and aspect. The number of potential ways to feel is uncountable. An infant is not capable of all those subtle and nuanced differences. The complexity of our emotional world grows in direct proportion to our cognitive abilities and the understanding of our experiences.
At first, we have only two emotional states: arousal and calm (on and off). But as we grow and develop, our emotions divide and multiply like living cells. Below is a typical developmental chart showing the normal times at which the ordinary infant and toddler display new feelings:
The direction of our emotional development is from the obvious to subtle and from global to specific. At first, the infant is either aroused or at ease. They are either on or off. When they are on, they exhibit distress when they are off, they sleep. And when they demonstrate their feelings, they do so with their entire body. Watch a baby cry, every part of them scrunches, trembles, and quakes.
Because this process of emotional development starts with few feelings but ends with many, it's called emotional differentiation (or: the making of different emotions). The figure above is a good representation, but we have our own one we affectionally call ED the Fractal. It’s our version of Emotional Differentiation and is represented graphically by a fractal. To help explain ED, let me describe fractals briefly. A fractal is a simple shape and process repeated over and over, generating a complex and often striking visual image. Shown are a couple of famous examples: Fractals have the potential to be helpful in describing how we learn by using semantically opposite concepts or dualities (up/down, good/bad, high/low, etc.) in all areas of learning, automatic through our knowledge base and experience.
Alfred Laing’s Spiral Fantasy Julius Tree (Artist unknown)
Fractals and fractal dimensions can be used to describe and create elaborate, irregular, complex, and creative structures from the simplest of shapes and processes. They also help us in measuring a shoreline on a map or how specific compartments in an organizational structure fill a certain space.
Like the development of a fractal, we believe that we learn our emotions and even our higher, abstract reasoning with an especially straightforward process repeated over and over millions or billions of times. This iteration is exactly how a fractal works. Accordingly, we've decided to use one to illustrate how our feelings develop.
We based ED on a famous fractal named, The Sierpinski Triangle, which looks like this:
You can see how uncomplicated the shape (an equilateral triangle) and the process is (cutting out smaller triangles from the larger one). At each step, you mark each side of the triangle in half and then cut out the triangle made when you connect these marks with straight lines.
This process can go on indefinitely. In fact, theoretically you can continue cutting out an infinite number of triangles and always have more small triangles to subdivide repeatedly. You will never reach a point when there is no original triangle left.
http://en.wikipedia.org/wiki/Sierpinski_triangle
Along these lines our fractal, ED, looks like this:
This diagram begins with two triangles. One represents the self-conscious part of our personalities (the Me - my personality, all of me that I am conscious of, this is what psychologists call the ego). The second triangle stands for everything else (or the Other). The first is everything inside myself and the second is everything else, everything outside of me.
At about eight months old, the infant is starting to be aware of itself as separate from the world. This begins a developmental process called individuation and typically continues until about the age of three. This wakening of self-conscious awareness allows the child to make judgments about itself and the world as two different things and starts the creation of what are known as the executive functions of cognition. These functions exist in other animals but are not as sophisticated or elaborate as in Homo-sapiens.
The executive functions are the mental equivalent of their namesake: the Boss. They contain the skills needed to make executive decisions. As they "go on-line" and begin to work, they allow the child to draw new and different conclusions about themselves and their environment. These tasks include knowing the stove is hot (reality testing), calming themselves when angry or frightened (affect regulation), learning to wait (impulse control), foresight, protecting their feelings (emotional defenses), judging good from bad and several others. The Ego-Boundaries are Reality Testing, Thought Processing, Judgment, Emotional Synthesis, Impulse Control, Affect Regulation, Object Relations, and Defensive Functioning.
At the beginning of this process, the baby develops a sense of individuality and around 8 months old can make some broad and absolute conclusion about themselves and their world. Are they feeling pain from gas or a rash’s constant irritation? In other words, do they feel bad? If they feel bad, then they don't like themselves. If they feel good? Then they do like themselves. At first, these judgments are primitive and expressed globally (i.e., “Good Me” or “Bad Me”.) With the latter opinion they will feel distress; with the former, pleasure. How do they feel about the Other (at this point their caregiver)? If they are comfortable and secure with it, they feel affection. If they don't then they fear it.
These are black and white judgments of Me vs. Other and this polarized judgment of good or bad, is the genesis of all our emotions. We are either attracted to or repulsed by the Other. It is straightforward: attract or repulse (like or dislike.) The baby decides: Good Other or Bad Other and Good Me or Bad Me. With this the child’s first four feelings are experienced (affection, fear, pleasure, and distress) all variations of Attraction and Repulsion, the root of emotional reasoning.
As time progresses and the child develops, these subdivisions of emotion (affection, fear, pleasure and distress) are further divided by the application of good and bad and lead to the further development of emotions. Sad and happy, shame and joy, love and rage are all reflections and modifications of our original judgment of good and bad, like and dislike. We have many names for our emotions, but we have many more feelings than names.
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The Causal Chain from Belief to Action and Back:
We are constantly interacting with our environment (both internal and external). It is like being always engaged in a three-way conversation between our perception of the external environment, our ego, and the repository of past experiences, our memories with which we interpret and judge ourselves and the world. The following graphic represents these conversations.
[In the following, ‘>’ means “leads to”]
. . . Belief or Expectation >
Expectation & Sensation > Perception > Meaning/Understanding > Emotion > Motivation > A Decision to Act > Behavior > Consequence > New Sensation > New Perception > New Meaning > New Interpretation > New Belief > … etc.
Another way of describing this would be by the formula:
[Note: Where B = a behavior, B(n) New Behavior, B(o) Old Behavior, F Mind force or motivation, K constant of individual based on history of resistance and rigidity to change, etc.]
Additionally, as adults, we can feel more than one thing at a time. Since we can localize the expressions of our emotions in a particular area of our body (for example, a raised eyebrow, a crossing of the arms, a slight shoulder lift, or a tightening of a stomach muscle, etc.) This demonstrates that we can express different things at one time. We can say one thing with words and express the opposite with several intelligences other than verbal. Multiple intelligences allow us to communicate complex ideas efficiently.
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The Performance Curve and Human Learning
Human learning and performance are correlated highly with emotional stress and anxiety. If we have a positive relationship with our emotions, then we can use them to maximize our ability to think effectively. The performance curve looks like this:
This dynamic is involved in all human activities. It is true for work and play, for children and adults alike. It is at work in a high-powered business meeting and active in a game of Mario Brothers with the kids. If we have test anxiety or a problem with public speaking, the Performance Curve helps explain and gives us options that can help us smooth things out and control our worries.
On the left of the curve, when there is little to no stress there is mediocre performance. If we just don’t care . . . say . . . about school, then we will probably not do the work required to do well there. We won’t study. We won’t practice or prepare for a test and probably won’t even read the book. We’ll most likely look bored in class or be disruptive. And, consequently, we will not do well on tests, homework, or class participation.
But if doing well in school becomes more important, we will begin to try harder. When we don’t do our work, we’ll probably feel guilty and nervous and maybe study more. If a test is coming soon, we start to feel anxious. This annoying little feeling, this unease, motivates us to get rid of it by preparing for the upcoming test. So then, these little feelings of fear and guilt help us do better.
There is a maximum in how well we can do and a point where guilt and worry no longer motivates but shuts us down. We are finite and limited creatures. So, at some point, the Performance Curve stops going up. It levels off and we enter a state of performance athletes have nicknamed The Zone. Psychologists call it optimal performance and say it’s a peak experience.
This top-of-the-curve state is a highly enjoyable and satisfying condition. Our mood is elated. We feel as if our mind, body, and soul are one, completely in sync. Our perceptions are brilliantly clear, and our decisions are lightening fast and dead-on accurate. Being in The Zone is one of the most motivating mental states we can have. It is intoxicating, even addictive.
But it’s also awfully difficult to stay at the top of the curve. Like a friction-less ball on the top of a smooth hill, our ability to perform tends to roll down either one way or the other. We either fatigue or become over-confident, get bored or worry. So, in one way or the other, we begin to be less successful than when in The Zone.
Remember all stress is not bad and success itself causes an increase in pressure. Most people will attest that a wedding is sometimes nerve-racking but not necessarily a terrible thing. This is as true with a raise or promotion at work, an award, or a victory. All come with added responsibilities and higher expectations for future performance. We call them new challenges, new reasons to try again but they are stressful and taxing.
To be sensitive enough with ourselves to know our current placement on this curve is the mark of high Emotional Intelligence. It allows us to judge and react in a way to push ourselves back toward optimal performance. This self-awareness is a measure and indicator of mental health. Sometimes we must try harder. Sometimes we need to lay-off, walk away or relax. Knowing when to do what is the key to doing our best. AI does not have self-awareness and therefore no emotional intelligence with which to improve its performance.
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The critical area of psycho-social development was studied by Eric Erickson. He developed a stage theory showing how each developmental stage is driven by a conflict which needs to be resolved before moving on to solve the next conflict. He extended development to the full life cycle and not simply the first few years of a life, although here we are concerned with only the first few of his stages. They are as follows:
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Stage |
Basic Conflict |
Important Events |
Outcome |
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Infancy (birth to 18 months) |
Trust vs. Mistrust |
Feeding Bonding and communicating with caregivers |
Children develop a sense of trust when caregivers provide reliability, care, and affection. A lack of this will lead to mistrust. |
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Early Childhood (1.5 to 3 years) |
Autonomy vs. Shame and Doubt |
Toilet Training |
Children need to develop a sense of personal control over physical skills and a sense of independence. Success leads to feelings of autonomy, failure results in feelings of shame and doubt. |
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Preschool (3 to 5 years) |
Initiative vs. Guilt |
Exploration of abilities |
Children need to begin asserting control and power over the environment. Success in this stage leads to a sense of purpose. Children who try to exert too much power experience disapproval, resulting in a sense of guilt. |
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School Age (6 to 11 years) |
Industry vs. Inferiority |
Elementary School |
Children need to cope with new social and academic demands. Success leads to a sense of competence, while failure results in feelings of inferiority. |
We rely upon its Emotional Intelligence to maximize our performance. And psycho-social factors have profound impact upon emotional learning and then upon all reasoning. Therefore, the resolution of Erikson’s conflicts influence how well reasoning can operate within the general thinking process.
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3) Brainwaves: Another Factor Over-Looked by Cognitive Researchers
There is a phenomenon associated with and produced by brain activity that has received minimal attention in our research. It is our brain waves, which we can pick-up with electrodes on the outside of a working brain inside a skull.
This is accomplished with an electro-encephala-graph (eeg). We didn’t know much about them except for the little we had learned in school. Except for the one case I had in my practice, a child who suffered with epilepsy, I had never the need more in my career. Generally, we know that their level of activity correlates highly with the elevation in the arousal of consciousness. The behavioral impact of the arousal levels is well known and descriptions of them at various amounts of processing are written in detail.
If brainwaves are inconsequential side-effects of brain activity and represent global arousal and nothing more, we can end the discussion here. But if they have any meaningful role in producing our consciousness and if we dismiss them as unimportant because of this, we do so at our own intellectual peril. Are our brain waves thoughts? Are they meaningful, clearly broadcasted, representative of conscious arousal or simply a noise made by many electric signals, jumbled fragments of signals, meaningless, and partially broadcasted? Why has no one asked this question? Does this thoughtlessness due to some potential prejudice of ours?
Do our brain waves leave our brain? Yes, of course they do or we would not be able to measure their signals with EEG sensors attached to the outside our heads. Are parts of our brain able to detect and to understand them? Can we establish the existence of two-way communication between brain-waves and brains?
It is recently reported that birds navigate thousands of miles efficiently and accurately by way of sensing the earth’s magnetic field using a sensitized protein found mainly in their beaks and eyes. Looking for this protein or a similar substance in human brains, researchers have discovered the existence of magnetite concentrated in four locations in the human brain (reference to Why Is There Magnetite in the Brain? June 11, 2019 By Ross Pomeroy & RCP Staff) or
the cerebellum, brainstem, occipital lobe, and left frontal lobe. These locations suggest the purpose for which the brain is utilizing this magnetic substance, potentially a source of feedback.
The brainstem:
“is associated with various vital functions, such as the sleep-wake cycle, consciousness, and respiratory and cardiovascular control. It also houses the majority of the cranial nerve nuclei and facilitates communication between the cerebrum, spinal cord, and cerebellum by relaying neural tracts.” (https://www.kenhub.com/en/library/anatomy/cerebellum-and-brainstem)
The Cerebellum:
[is the area at the back and bottom of the brain, behind the brainstem. The cerebellum has important functions relating to movement and coordination, including:
- Maintaining balance: The cerebellum has special sensors that detect shifts in balance and movement. It sends signals for the body to adjust and move.
- Coordinating movement: Most body movements require the coordination of multiple muscle groups. The cerebellum times muscle actions so that the body can move smoothly.
- Vision: The cerebellum coordinates eye movements.
- Motor learning: The cerebellum helps the body to learn movements that require practice and fine-tuning. For example, the cerebellum plays a role in learning to ride a bicycle or play a musical instrument.
- Other functions: Researchers believe the cerebellum has some role in thinking, including processing language and mood. However, findings on these functions are yet to receivefull exploration. ] [https://www.medicalnewstoday.com/articles/313265#function]
The Occipital lobe:
is associated with the initial processing of visual stimulus
The Left frontal lobe:
is the part of the brain that helps people to organize, plan, pay attention, and make decisions. Parts of the frontal lobe may mature a few years later in people with ADHD [https://www.aacap.org/AACAP/Families_and_Youth/Facts_for_Families/FFF-Guide/ADHD_and_the_Brain-121.aspx]
Deficits in the frontal lobes are suspected in the development of Attention Deficit Hyperactivity Disorder (ADHD) [Note: Delta waves (Δ - < 4 Hz.) Dominant in infants up to 1 year old – higher Δ means lower awareness of the world – higher Δ means higher ADHD and learning disabilities – drowsy state].
The way we measure/describe brainwaves is with frequency (level of conscious arousal) and globally.
, amplitude (strength), and (Hue or meaning - cool and warm colors). These are the three attributes that emotions can be described by: 1) Object or target, 2) Intensity of the feeling (amplitude), and 3) Wavelength (determining which emotion).
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Vectors |
= |
Length |
Direction |
Color |
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Brainwaves |
=
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Amplitude |
Frequency - measures arousal which is attention an required when focusing on the target |
Wavelength |
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Emotions |
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Intensity |
Object |
Which Emotion? |
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What is being measured? |
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Strength or Intensity |
Targeting |
What hue on the visible spectrum? |
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Many believe that all consciousness remains in the brain but we know that brainwave do not.
Brain waves may be the gestalt we need to allow the training of AI to be affordable and flexible. If the brain can sense and interpret its own activity, then there exists the potential of direct feedback to the brain creating the ability to self-reflect on our current level of mental arousal etc.. This is the start of abstract thinking. Then the mind and a wholistic consciousness can form the possibility of top-down processing, which would increase tremendously the efficiency of learning. Modelling it in our neuro-networks should allow AI the ability to “think more like humans”.
If all this is true, consciousness is rooted in and supported by the bottom-up, digital processing of the brain and/or computer. A feedback loop of brain functioning back to the brain would allow self-reflection and then that ability could lead to higher order thinking.
The patterns of brain waves already have meanings, even though generalized. According to research, brain waves have five speeds categorized as distinct levels of arousal. They are:
Delta (Δ - < 4 Hz.) Dominant in infants up to 1 year old – higher Δ means lower
awareness of the world – higher Δ means higher ADHD and learning disabilities
– drowsy state
Theta (Θ – 4-8 Hz.) Higher creativity – daydreaming – better memories, emotions, and sensations – between wakefulness and sleep – awake child up to 13 years old
Alpha (A – 8-12 Hz.) Dominates frontal and occipital lobes – normal relaxed adults – alter and relaxed – increased A by deep breathing and closed eyes – high A and Θ = abstract thinking and self-control - action state – accomplishing tasks and mental work
Beta (B – 13-30 Hz.) higher anxiety – better analytic problem solving – judgement
Gamma (Γ > 30 Hz.) information rich task processing (bottom-up) – simultaneous processing – multi-tasking – good memory
Brainwaves compose a continuum from unconsciousness of the world to daydreaming or drowsiness to creative and emotional thinking then to relaxed alertness (the Zone?) increased self-control to anxious but alert and ultimately to high data processing. As both the performance curve and the spectrum of brainwaves both measure arousal/stress they both are measuring the same thing and therefore brainwaves can be placed on the performance curve much like this:
“Brainwaves are crucial to all aspects of brain functioning thoughts, emotions, and behaviors.” (From Good Therapy’s website https://www.goodtherapy.org/blog/psychpedia/brain-waves.)
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Earlier in this paper, it was suggested that feelings could be described by a vector mathematically in terms of 1. Length, 2. Direction, and 3. Color. Brainwaves are described mathematically with three descriptors: 1. Amplitude (measures intensity,), 2. Frequency (measures energy or arousal essential for focusing on a target), and 3. Wavelength (identifies color – warm or cool). Therefore, just like the deduction that “If A = B and B = C; Then A must = C”, Brainwaves, like affect can be described with vectors, subject to vector analysis, etc. For instance:
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Starting with the proposition that the mind as well as the brain must be subject to natural law as they ARE natural phenomenon. They are most evident to us on the macro level, so for this article we would like to start a discussion/investigation focused, for now, on the macro level. In the future though, it would be wise to research all levels of reality to see if the processes within both the brain and mind have analogous known natural law. So, we start with looking at Newton’s Laws of motion.
It is important that we have a mathematical language that can be used to communicate the relationships between these variables. I think it might be interesting to pursue what follows:
motivation, a product of Idea x Affect x Personality Constant.
Motivation applied through time equals mental work.
Mental Force = motivation = Cp
As momentum equals mass x acceleration –
Mental Stamina should = K(i) x f(p)dt
These formulas, when first conceived, were meant to begin a conversation and not be the end of one. They are meant to be a way to explore the components of the mind in mathimatical language for a possible way to write their relationships into algorithms. There are probably more. There might be less. They need to be tested, at this point they are speculation based on our understanding of psychology and natural science.
Although we have done no technical research on these ideas so cannot prove their value at this time. But the fact is that when these principles are applied they produce diagnoses and behavioral interventions considered to be supperior to the educational professionsls who used them.
[ADD Thad’s mock-up results here]
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Mental Laws of Motion Physical Laws of Motion
Mental Laws of Motion and Newton’s Laws of Physical Motion are a mirror reflection of each other (like two hands coming together making a near perfect match. Matching random hands like this is an exceptionally low probability event as there are so many sized and shaped hands. Only if the two hands are attached to the same body does this probability increase. This mirroring of the laws of motion suggests that they may have a connection and act like a synapse between mind and body. By them are the laws of physics and meta-physics are possibly connected. If this is true, however, then brainwaves are not an inconsequential side effect of brain activity but are an intended product of the brain. In fact, they may be the main product of the brain much like a radio that produces unseen waves to broadcast and be obtained by a receiver. And if our brainwaves are being received and interpreted by our brains, it is reasonable to suggest that our brains are utilizing self-reflection, a critical skill required in abstract thinking and achieve a gestalt understanding of our brain’s working.
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In conclusion, we believe that there are three significant errors that researchers have made in studying AI and brain functioning. First, it is a mistake to assume that all mental functions exists only within the brain and “do not leave their source” as brain wave obviously do. And second, ignoring the potential for further studying as an essential part of the brain and significantly impacting on our abilities to self-reflect and think abstractly. And thirdly, that homo-sapiens are not primarily thinking beings with some un-wanted side-effects of brain processing such as emotions. The truth is that our feelings are central to who we are and not peripheral. The beginning of thought development goes back to the single cell animal that will move away from a toxin in its environment and towards food in the same. This is the most primitive decision a living being makes. It is a display of thinking, the ability to decide whether to approach or move away from something in the physical environment. Attraction and Repulsion is the first duality involved in reasoning, emotional reasoning. Quantitative reasoning appears when a preschool child first learns to count. Verbal/Linguistic reasoning begins early in development with acquisition of receptive language but doesn’t begin expressive language until their first word is vocalized, most often displayed about a year after birth.
By limiting our investigation to only the brain by believing that consciousness only exists within the brain, we automatically diminish the importance of brainwaves as they clearly travel out from the brain creating a measurable field, already being interpreted in a gross or global manner as a measure of conscious arousal. Unfortunately, we have a priori determined the nature and function of brainwaves thus we may have overlooked a potential explanation of how the digital, bottom-up processing of the brain is elevated and extended by the gestalt workings of the mind.
References Here
Fluid reasoning represents the capacity to think logically and solve problems in novel situations. This construct is central to theories of human intelligence (Carroll, 1997; Cattell, 1987; Gray et al., 2003; Horn, 1988; Horn and Cattell, 1967; McArdle and Woodcock, 1998). M ar 28, 2008
Fluid intelligence involves comprehension, reasoning and problem solving, while crystallized intelligence involves recalling stored knowledge and past experiences.
Fluid intelligence and crystallized intelligence rely on distinct brain systems despite their interrelationship in the performance of many tasks.
[1] THE BIOLOGY OF BELIEF Bruce Lipton etc. pg. 145-6
[2] Tolman, E.C. (1932). Purposive Behavior in Animals and Men. New York: Appleton-Century-Crofts.
A Comparison Between
Today’s Research on Human and Artificial Intelligence:
Suggesting a Paradigm Shift for Studying Both
By Kenney, D; Roppel, T; et al
The field of Artificial Intelligence (AI)I currently boasts successes in various efforts (i.e. IBM’s Big Blue that beat the world champion, Garry Kasparov in chess; Brooks, R.; Spectrum IEEE.org, October 2021, pg. 49) or DeepMind defeating Go champion Lee Se-dol (Thompson, N., Greenwald, K, Lee, K.; Manso, G.; Spectrum IEEE.org, October 2021, pg. 51) or the rapid improvement in spoken word recognition, and the analyzing of medical scans and autonomous automobiles. Since 1956 (reference here), AI has become invaluable to both business and research. But there has been no real advancement in the way AI “thinks” and many current investigators into AI are still frustrated by this lack in AI’s ability to “think like people”. This article points to three specific ways in which researchers have unwittingly limited the possible outcomes of their studies. By disregarding these factors they’ve created for themselves a morass of false turns and dead-ended paths. These factors are: 1) assuming and modeling a generalized intelligence (‘g’) instead of multiple intelligences. 2) over-looking the importance of emotional intelligence in learning, and 3) ignoring any possible role that brainwaves may contribute to cognitive processing.
# # #
- Assuming and modeling a generalized intelligence (‘g’)
instead of multiple intelligences
Currently, AI’s processes are all done with what psychologists think off as “bottom-up processing,” (reference here) or what is more commonly known as inductive reasoning. Al uses digital code and rapid memory and retrieval to scan examples and quickly match them with past attempts that led to a successful outcome. With this binary based process (digital 0’s and 1’s), AI has been able to defeat world champions not by using the variety of intelligences humans are capable of but by the rapid deployment of basic processes. The speed of their processes is far greater than what the human brain can match. But they are still not capable of abstract thought or deductive reasoning. Bottom-up processing can understand and draw conclusions from a set of data but, unfortunately, the amount of data needed to train all but the simplest neural-networks is astronomical and the cost in energy is extremely prohibitive.
AI’s calculations can be applied successfully to all sorts of difficult problems and their solutions are fast, effective but not abstract as human thinking can be. If our goal is for AI to think like people, it must have equivalent structures and processing capabilities. A toddler applies its skills to novel situations because the calculations are concrete but the ability to generalize is an abstract process. Perhaps we can design programs that mimic higher order reasoning that develops in humans as well as self-awareness but our attempts to do so have led to unavoidable problems such as the overwhelming need for power and data to train the AI or its catastrophic forgetting (reference here) while training for a new task.
Unlike AI research, our understanding of human intelligence processes and brain functioning has changed considerably since 1956.
“Psychologists have long debated how to best conceptualize and measure intelligence (Sternberg, 2003). These questions include how many types of intelligence there are, the role of nature versus nurture in intelligence, how intelligence is represented in the brain, and the meaning of group differences in intelligence.” Introduction to Psychology – 1st Canadian Edition. Authors: Charles Stangor and Jennifer Walinga
In the early 1980’s Howard Gardner published the following definition:
An intelligence is the ability to solve problems, or to create products, that are valued within one or more cultural settings.” -- Howard Gardner, FRAMES OF MIND (1983)
With this definition and worldwide study into what diverse cultures have determined what was ‘smart’, Dr. Gardner and his colleagues proposed identifying seven, distinct intelligences: Verbal-Linguistic, Mathematical-Logical, Visual-Spatial, Intrapersonal, Interpersonal, Bodily-Kinesthetic, and Musical-Rhythmic. This theory was well received and very soon thereafter became basic in the field. Although not many innovations have been derived from this theory yet, its overarching concepts have become pivotal in the understanding of intelligence.
There are many ways in which we are naturally smart. There are the familiar intelligences we know from IQ tests (verbal, quantitative and visual/spatial). But we can also think smart with music, body movement and emotional reasoning.
Every physiologically and mentally typical person acquires in childhood the ability to make use, as both sender and receiver, of a system of communication that comprises a circumscribed set of symbols (e.g., sounds, gestures, or written or typed characters). In spoken language, this symbol set consists of noises resulting from movements of certain organs within the throat and mouth. In signed languages, these symbols may be hand or body movements, gestures, or facial expressions. By means of these symbols, people are able to impart information, to express feelings and emotions, to influence the activities of others, and to comport themselves with varying degrees of friendliness or hostility toward persons who make use of substantially the same set of symbols. https://www.britannica.com/topic/language#ref27156
Emotional intelligence does not reason the same way verbal reasoning does. The rules and steps in their problem-solving processes are notably different. Our feelings have their own logic (based upon a fractal that starts with the duality: Attract/Repulse), and their own specific language. Verbal Intelligence starts with the duality of Yes/No. Spatial Intelligence with Here/There or Near/Far. All our intelligences have their own languages, and each language is based on an individual, primal duality. For the emotional intelligences this language begins with behavior. Our first language is not spoken. Our first language is behavior, even the single cell animal displays the primal duality as Attraction / Repulsion.
2) The impact of Emotional Intelligence has Upon Our Ability to
Learn and Perform Abstract Reasoning
All forms of life, even the single cell varieties, are learning and responding bio-machines. In his book, The Biology of Belief, Bruce Lipton[1], a noted cellular biologist, described how the single cell perceives and makes judgments about its environment. He told how the single living cell will either move toward a food supply or away from a toxin introduced to its neighborhood. It senses its environment and responds, hopefully, in a beneficial way. The single cell critter learns and reacts in a goal directed or purposive manner. Even the novice student of psychology should recognize this as “Stimulus > Response” (S>R), the basic unit of learning. All complex learning and deep contemplation rest on this foundation: S>R.
Goal directed behavior is displayed by all the multi-celled organisms evolved from the single cell. All life learns and reacts to survive.
That all behavior is purposive has been a key axiom of psychology since the 1940’s.[2] And, as the theory of natural selection suggests, the efficiency, accuracy, and predictive validity with which any form acts will increase its survival equivalently, allowing it a greater probability of passing on its characteristics to the next generation.
Even an embryo displays goal-directed responses to increase the likelihood of its success. Dr. Lipton also illustrated how the fetus reacts to its mother's emotional state during pregnancy. The mother’s stress level will cause the baby to develop in skeletal/muscular mass, coordination, and “life-saving reflex behavior” when the mother’s stress is high. Or the embryo will invest its resources in internal growth and learning when their mother’s stress is low.
In other words, if their mother perceives the world as hostile, frustrating and/or frightening, the embryo will devote more of its developmental energy to increasing its abilities to be strong, agile, and quick to react, or if the mother is relaxed and at peace in her world, the fetus will develop more of its ability to learn and heal. The fetus responds to its mother’s reactions in a way to increase the probability of its success once born, thus setting their balance up or down along the scale between “brain and brawn.” In effect, the embryo prepares itself for the world it perceives it will be delivered into. All life strives to understand and react correctly to its environment.
# # #
Exclusively using one intellectual modality and language to teach about another is deficient. One modality does not completely translate into another. It can enhance and edify but not replace it.
So, why are researchers still using the concept of a single intelligence (denoted by a small ‘g’) in their studies? Why are we continuing to search for an intelligence we know doesn’t exist? It distorts scientists’ thinking and causes biases which misdirects efforts. One way these biases have impacted researchers is to lead them to think that some combination of Verbal-Linguistic and Mathematical-Logical intelligences must be the principal part of ‘g” or general intelligence. In fact, the emotional intelligences historically were described as unreliable and irrational and attributed mainly to women when, in fact, they are our intellectual foundation. The best single predictor of school success is verbal intelligence, but the best predictor of life success and satisfaction is emotional intelligence (Goleman Reference here). This misjudgment has led researchers to attempt the creation of higher order neuro-networks without their foundations.
Humans are not thinking creatures with emotions on the side that often are irrational and difficult to work with. In truth, we are feeling beings with some specific higher order processing abilities added to our basic thinking structures, which are a majority emotional. The brain’s structure developed over eons, building itself up layer by layer. In general, we talk about three main layers of the brain as: 1) Survival (brain stem, pons, cerebellum; reptilian), 2) Emotional, (mid-brain; mammalian) and 3) Executive (pre-frontal and frontal lobes; primate to Homo-Sapien). Each layer is built upon the previous and extends the pre-existing functions. Emotions evolved extending the physical sensations that make up our sensory feedback from our physical world. And then abstract thinking evolved from emotional intelligence in an effort to understand and improve our emotional responses to our environment each layer assisting the previous in being successful. Our ability to think abstractly, verbally, and quantitatively were all built upon the logic of feelings, feelings on sensation, music on feelings and sensations.
# # #
We are not born with the rich set of emotions we have as adults. As we grow and then age, we create many names for new feelings. Like the colors of a rainbow, our adult emotions exist on a spectrum and vary in both intensity, direction and aspect. The number of potential ways to feel is uncountable. An infant is not capable of all those subtle and nuanced differences. The complexity of our emotional world grows in direct proportion to our cognitive abilities and the understanding of our experiences.
At first, we have only two emotional states: arousal and calm (on and off). But as we grow and develop, our emotions divide and multiply like living cells. Below is a typical developmental chart showing the normal times at which the ordinary infant and toddler display new feelings:
The direction of our emotional development is from the obvious to subtle and from global to specific. At first, the infant is either aroused or at ease. They are either on or off. When they are on, they exhibit distress when they are off, they sleep. And when they demonstrate their feelings, they do so with their entire body. Watch a baby cry, every part of them scrunches, trembles, and quakes.
Because this process of emotional development starts with few feelings but ends with many, it's called emotional differentiation (or: the making of different emotions). The figure above is a good representation, but we have our own one we affectionally call ED the Fractal. It’s our version of Emotional Differentiation and is represented graphically by a fractal. To help explain ED, let me describe fractals briefly. A fractal is a simple shape and process repeated over and over, generating a complex and often striking visual image. Shown are a couple of famous examples: Fractals have the potential to be helpful in describing how we learn by using semantically opposite concepts or dualities (up/down, good/bad, high/low, etc.) in all areas of learning, automatic through our knowledge base and experience.
Alfred Laing’s Spiral Fantasy Julius Tree (Artist unknown)
Fractals and fractal dimensions can be used to describe and create elaborate, irregular, complex, and creative structures from the simplest of shapes and processes. They also help us in measuring a shoreline on a map or how specific compartments in an organizational structure fill a certain space.
Like the development of a fractal, we believe that we learn our emotions and even our higher, abstract reasoning with an especially straightforward process repeated over and over millions or billions of times. This iteration is exactly how a fractal works. Accordingly, we've decided to use one to illustrate how our feelings develop.
We based ED on a famous fractal named, The Sierpinski Triangle, which looks like this:
You can see how uncomplicated the shape (an equilateral triangle) and the process is (cutting out smaller triangles from the larger one). At each step, you mark each side of the triangle in half and then cut out the triangle made when you connect these marks with straight lines.
This process can go on indefinitely. In fact, theoretically you can continue cutting out an infinite number of triangles and always have more small triangles to subdivide repeatedly. You will never reach a point when there is no original triangle left.
http://en.wikipedia.org/wiki/Sierpinski_triangle
Along these lines our fractal, ED, looks like this:
This diagram begins with two triangles. One represents the self-conscious part of our personalities (the Me - my personality, all of me that I am conscious of, this is what psychologists call the ego). The second triangle stands for everything else (or the Other). The first is everything inside myself and the second is everything else, everything outside of me.
At about eight months old, the infant is starting to be aware of itself as separate from the world. This begins a developmental process called individuation and typically continues until about the age of three. This wakening of self-conscious awareness allows the child to make judgments about itself and the world as two different things and starts the creation of what are known as the executive functions of cognition. These functions exist in other animals but are not as sophisticated or elaborate as in Homo-sapiens.
The executive functions are the mental equivalent of their namesake: the Boss. They contain the skills needed to make executive decisions. As they "go on-line" and begin to work, they allow the child to draw new and different conclusions about themselves and their environment. These tasks include knowing the stove is hot (reality testing), calming themselves when angry or frightened (affect regulation), learning to wait (impulse control), foresight, protecting their feelings (emotional defenses), judging good from bad and several others. The Ego-Boundaries are Reality Testing, Thought Processing, Judgment, Emotional Synthesis, Impulse Control, Affect Regulation, Object Relations, and Defensive Functioning.
At the beginning of this process, the baby develops a sense of individuality and around 8 months old can make some broad and absolute conclusion about themselves and their world. Are they feeling pain from gas or a rash’s constant irritation? In other words, do they feel bad? If they feel bad, then they don't like themselves. If they feel good? Then they do like themselves. At first, these judgments are primitive and expressed globally (i.e., “Good Me” or “Bad Me”.) With the latter opinion they will feel distress; with the former, pleasure. How do they feel about the Other (at this point their caregiver)? If they are comfortable and secure with it, they feel affection. If they don't then they fear it.
These are black and white judgments of Me vs. Other and this polarized judgment of good or bad, is the genesis of all our emotions. We are either attracted to or repulsed by the Other. It is straightforward: attract or repulse (like or dislike.) The baby decides: Good Other or Bad Other and Good Me or Bad Me. With this the child’s first four feelings are experienced (affection, fear, pleasure, and distress) all variations of Attraction and Repulsion, the root of emotional reasoning.
As time progresses and the child develops, these subdivisions of emotion (affection, fear, pleasure and distress) are further divided by the application of good and bad and lead to the further development of emotions. Sad and happy, shame and joy, love and rage are all reflections and modifications of our original judgment of good and bad, like and dislike. We have many names for our emotions, but we have many more feelings than names.
# # #
The Causal Chain from Belief to Action and Back:
We are constantly interacting with our environment (both internal and external). It is like being always engaged in a three-way conversation between our perception of the external environment, our ego, and the repository of past experiences, our memories with which we interpret and judge ourselves and the world. The following graphic represents these conversations.
[In the following, ‘>’ means “leads to”]
. . . Belief or Expectation >
Expectation & Sensation > Perception > Meaning/Understanding > Emotion > Motivation > A Decision to Act > Behavior > Consequence > New Sensation > New Perception > New Meaning > New Interpretation > New Belief > … etc.
Another way of describing this would be by the formula:
[Note: Where B = a behavior, B(n) New Behavior, B(o) Old Behavior, F Mind force or motivation, K constant of individual based on history of resistance and rigidity to change, etc.]
Additionally, as adults, we can feel more than one thing at a time. Since we can localize the expressions of our emotions in a particular area of our body (for example, a raised eyebrow, a crossing of the arms, a slight shoulder lift, or a tightening of a stomach muscle, etc.) This demonstrates that we can express different things at one time. We can say one thing with words and express the opposite with several intelligences other than verbal. Multiple intelligences allow us to communicate complex ideas efficiently.
# # #
The Performance Curve and Human Learning
Human learning and performance are correlated highly with emotional stress and anxiety. If we have a positive relationship with our emotions, then we can use them to maximize our ability to think effectively. The performance curve looks like this:
This dynamic is involved in all human activities. It is true for work and play, for children and adults alike. It is at work in a high-powered business meeting and active in a game of Mario Brothers with the kids. If we have test anxiety or a problem with public speaking, the Performance Curve helps explain and gives us options that can help us smooth things out and control our worries.
On the left of the curve, when there is little to no stress there is mediocre performance. If we just don’t care . . . say . . . about school, then we will probably not do the work required to do well there. We won’t study. We won’t practice or prepare for a test and probably won’t even read the book. We’ll most likely look bored in class or be disruptive. And, consequently, we will not do well on tests, homework, or class participation.
But if doing well in school becomes more important, we will begin to try harder. When we don’t do our work, we’ll probably feel guilty and nervous and maybe study more. If a test is coming soon, we start to feel anxious. This annoying little feeling, this unease, motivates us to get rid of it by preparing for the upcoming test. So then, these little feelings of fear and guilt help us do better.
There is a maximum in how well we can do and a point where guilt and worry no longer motivates but shuts us down. We are finite and limited creatures. So, at some point, the Performance Curve stops going up. It levels off and we enter a state of performance athletes have nicknamed The Zone. Psychologists call it optimal performance and say it’s a peak experience.
This top-of-the-curve state is a highly enjoyable and satisfying condition. Our mood is elated. We feel as if our mind, body, and soul are one, completely in sync. Our perceptions are brilliantly clear, and our decisions are lightening fast and dead-on accurate. Being in The Zone is one of the most motivating mental states we can have. It is intoxicating, even addictive.
But it’s also awfully difficult to stay at the top of the curve. Like a friction-less ball on the top of a smooth hill, our ability to perform tends to roll down either one way or the other. We either fatigue or become over-confident, get bored or worry. So, in one way or the other, we begin to be less successful than when in The Zone.
Remember all stress is not bad and success itself causes an increase in pressure. Most people will attest that a wedding is sometimes nerve-racking but not necessarily a terrible thing. This is as true with a raise or promotion at work, an award, or a victory. All come with added responsibilities and higher expectations for future performance. We call them new challenges, new reasons to try again but they are stressful and taxing.
To be sensitive enough with ourselves to know our current placement on this curve is the mark of high Emotional Intelligence. It allows us to judge and react in a way to push ourselves back toward optimal performance. This self-awareness is a measure and indicator of mental health. Sometimes we must try harder. Sometimes we need to lay-off, walk away or relax. Knowing when to do what is the key to doing our best. AI does not have self-awareness and therefore no emotional intelligence with which to improve its performance.
# # #
The critical area of psycho-social development was studied by Eric Erickson. He developed a stage theory showing how each developmental stage is driven by a conflict which needs to be resolved before moving on to solve the next conflict. He extended development to the full life cycle and not simply the first few years of a life, although here we are concerned with only the first few of his stages. They are as follows:
|
Stage |
Basic Conflict |
Important Events |
Outcome |
|
Infancy (birth to 18 months) |
Trust vs. Mistrust |
Feeding Bonding and communicating with caregivers |
Children develop a sense of trust when caregivers provide reliability, care, and affection. A lack of this will lead to mistrust. |
|
Early Childhood (1.5 to 3 years) |
Autonomy vs. Shame and Doubt |
Toilet Training |
Children need to develop a sense of personal control over physical skills and a sense of independence. Success leads to feelings of autonomy, failure results in feelings of shame and doubt. |
|
Preschool (3 to 5 years) |
Initiative vs. Guilt |
Exploration of abilities |
Children need to begin asserting control and power over the environment. Success in this stage leads to a sense of purpose. Children who try to exert too much power experience disapproval, resulting in a sense of guilt. |
|
School Age (6 to 11 years) |
Industry vs. Inferiority |
Elementary School |
Children need to cope with new social and academic demands. Success leads to a sense of competence, while failure results in feelings of inferiority. |
We rely upon its Emotional Intelligence to maximize our performance. And psycho-social factors have profound impact upon emotional learning and then upon all reasoning. Therefore, the resolution of Erikson’s conflicts influence how well reasoning can operate within the general thinking process.
# # #
3) Brainwaves: Another Factor Over-Looked by Cognitive Researchers
There is a phenomenon associated with and produced by brain activity that has received minimal attention in our research. It is our brain waves, which we can pick-up with electrodes on the outside of a working brain inside a skull.
This is accomplished with an electro-encephala-graph (eeg). We didn’t know much about them except for the little we had learned in school. Except for the one case I had in my practice, a child who suffered with epilepsy, I had never the need more in my career. Generally, we know that their level of activity correlates highly with the elevation in the arousal of consciousness. The behavioral impact of the arousal levels is well known and descriptions of them at various amounts of processing are written in detail.
If brainwaves are inconsequential side-effects of brain activity and represent global arousal and nothing more, we can end the discussion here. But if they have any meaningful role in producing our consciousness and if we dismiss them as unimportant because of this, we do so at our own intellectual peril. Are our brain waves thoughts? Are they meaningful, clearly broadcasted, representative of conscious arousal or simply a noise made by many electric signals, jumbled fragments of signals, meaningless, and partially broadcasted? Why has no one asked this question? Does this thoughtlessness due to some potential prejudice of ours?
Do our brain waves leave our brain? Yes, of course they do or we would not be able to measure their signals with EEG sensors attached to the outside our heads. Are parts of our brain able to detect and to understand them? Can we establish the existence of two-way communication between brain-waves and brains?
It is recently reported that birds navigate thousands of miles efficiently and accurately by way of sensing the earth’s magnetic field using a sensitized protein found mainly in their beaks and eyes. Looking for this protein or a similar substance in human brains, researchers have discovered the existence of magnetite concentrated in four locations in the human brain (reference to Why Is There Magnetite in the Brain? June 11, 2019 By Ross Pomeroy & RCP Staff) or
the cerebellum, brainstem, occipital lobe, and left frontal lobe. These locations suggest the purpose for which the brain is utilizing this magnetic substance, potentially a source of feedback.
The brainstem:
“is associated with various vital functions, such as the sleep-wake cycle, consciousness, and respiratory and cardiovascular control. It also houses the majority of the cranial nerve nuclei and facilitates communication between the cerebrum, spinal cord, and cerebellum by relaying neural tracts.” (https://www.kenhub.com/en/library/anatomy/cerebellum-and-brainstem)
The Cerebellum:
[is the area at the back and bottom of the brain, behind the brainstem. The cerebellum has important functions relating to movement and coordination, including:
- Maintaining balance: The cerebellum has special sensors that detect shifts in balance and movement. It sends signals for the body to adjust and move.
- Coordinating movement: Most body movements require the coordination of multiple muscle groups. The cerebellum times muscle actions so that the body can move smoothly.
- Vision: The cerebellum coordinates eye movements.
- Motor learning: The cerebellum helps the body to learn movements that require practice and fine-tuning. For example, the cerebellum plays a role in learning to ride a bicycle or play a musical instrument.
- Other functions: Researchers believe the cerebellum has some role in thinking, including processing language and mood. However, findings on these functions are yet to receivefull exploration. ] [https://www.medicalnewstoday.com/articles/313265#function]
The Occipital lobe:
is associated with the initial processing of visual stimulus
The Left frontal lobe:
is the part of the brain that helps people to organize, plan, pay attention, and make decisions. Parts of the frontal lobe may mature a few years later in people with ADHD [https://www.aacap.org/AACAP/Families_and_Youth/Facts_for_Families/FFF-Guide/ADHD_and_the_Brain-121.aspx]
Deficits in the frontal lobes are suspected in the development of Attention Deficit Hyperactivity Disorder (ADHD) [Note: Delta waves (Δ - < 4 Hz.) Dominant in infants up to 1 year old – higher Δ means lower awareness of the world – higher Δ means higher ADHD and learning disabilities – drowsy state].
The way we measure/describe brainwaves is with frequency (level of conscious arousal) and globally.
, amplitude (strength), and (Hue or meaning - cool and warm colors). These are the three attributes that emotions can be described by: 1) Object or target, 2) Intensity of the feeling (amplitude), and 3) Wavelength (determining which emotion).
|
|
|
|
|
|
|
|
|
|
Vectors |
= |
Length |
Direction |
Color |
|
|
|
Brainwaves |
=
|
Amplitude |
Frequency - measures arousal which is attention an required when focusing on the target |
Wavelength |
|
|
|
Emotions |
|
Intensity |
Object |
Which Emotion? |
|
|
|
What is being measured? |
|
Strength or Intensity |
Targeting |
What hue on the visible spectrum? |
|
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|
|
|
|
|
|
|
# # #
Many believe that all consciousness remains in the brain but we know that brainwave do not.
Brain waves may be the gestalt we need to allow the training of AI to be affordable and flexible. If the brain can sense and interpret its own activity, then there exists the potential of direct feedback to the brain creating the ability to self-reflect on our current level of mental arousal etc.. This is the start of abstract thinking. Then the mind and a wholistic consciousness can form the possibility of top-down processing, which would increase tremendously the efficiency of learning. Modelling it in our neuro-networks should allow AI the ability to “think more like humans”.
If all this is true, consciousness is rooted in and supported by the bottom-up, digital processing of the brain and/or computer. A feedback loop of brain functioning back to the brain would allow self-reflection and then that ability could lead to higher order thinking.
The patterns of brain waves already have meanings, even though generalized. According to research, brain waves have five speeds categorized as distinct levels of arousal. They are:
Delta (Δ - < 4 Hz.) Dominant in infants up to 1 year old – higher Δ means lower
awareness of the world – higher Δ means higher ADHD and learning disabilities
– drowsy state
Theta (Θ – 4-8 Hz.) Higher creativity – daydreaming – better memories, emotions, and sensations – between wakefulness and sleep – awake child up to 13 years old
Alpha (A – 8-12 Hz.) Dominates frontal and occipital lobes – normal relaxed adults – alter and relaxed – increased A by deep breathing and closed eyes – high A and Θ = abstract thinking and self-control - action state – accomplishing tasks and mental work
Beta (B – 13-30 Hz.) higher anxiety – better analytic problem solving – judgement
Gamma (Γ > 30 Hz.) information rich task processing (bottom-up) – simultaneous processing – multi-tasking – good memory
Brainwaves compose a continuum from unconsciousness of the world to daydreaming or drowsiness to creative and emotional thinking then to relaxed alertness (the Zone?) increased self-control to anxious but alert and ultimately to high data processing. As both the performance curve and the spectrum of brainwaves both measure arousal/stress they both are measuring the same thing and therefore brainwaves can be placed on the performance curve much like this:
“Brainwaves are crucial to all aspects of brain functioning thoughts, emotions, and behaviors.” (From Good Therapy’s website https://www.goodtherapy.org/blog/psychpedia/brain-waves.)
# # #
Earlier in this paper, it was suggested that feelings could be described by a vector mathematically in terms of 1. Length, 2. Direction, and 3. Color. Brainwaves are described mathematically with three descriptors: 1. Amplitude (measures intensity,), 2. Frequency (measures energy or arousal essential for focusing on a target), and 3. Wavelength (identifies color – warm or cool). Therefore, just like the deduction that “If A = B and B = C; Then A must = C”, Brainwaves, like affect can be described with vectors, subject to vector analysis, etc. For instance:
# # #
Starting with the proposition that the mind as well as the brain must be subject to natural law as they ARE natural phenomenon. They are most evident to us on the macro level, so for this article we would like to start a discussion/investigation focused, for now, on the macro level. In the future though, it would be wise to research all levels of reality to see if the processes within both the brain and mind have analogous known natural law. So, we start with looking at Newton’s Laws of motion.
It is important that we have a mathematical language that can be used to communicate the relationships between these variables. I think it might be interesting to pursue what follows:
motivation, a product of Idea x Affect x Personality Constant.
Motivation applied through time equals mental work.
Mental Force = motivation = Cp
As momentum equals mass x acceleration –
Mental Stamina should = K(i) x f(p)dt
These formulas, when first conceived, were meant to begin a conversation and not be the end of one. They are meant to be a way to explore the components of the mind in mathimatical language for a possible way to write their relationships into algorithms. There are probably more. There might be less. They need to be tested, at this point they are speculation based on our understanding of psychology and natural science.
Although we have done no technical research on these ideas so cannot prove their value at this time. But the fact is that when these principles are applied they produce diagnoses and behavioral interventions considered to be supperior to the educational professionsls who used them.
[ADD Thad’s mock-up results here]
# # #
Mental Laws of Motion Physical Laws of Motion
Mental Laws of Motion and Newton’s Laws of Physical Motion are a mirror reflection of each other (like two hands coming together making a near perfect match. Matching random hands like this is an exceptionally low probability event as there are so many sized and shaped hands. Only if the two hands are attached to the same body does this probability increase. This mirroring of the laws of motion suggests that they may have a connection and act like a synapse between mind and body. By them are the laws of physics and meta-physics are possibly connected. If this is true, however, then brainwaves are not an inconsequential side effect of brain activity but are an intended product of the brain. In fact, they may be the main product of the brain much like a radio that produces unseen waves to broadcast and be obtained by a receiver. And if our brainwaves are being received and interpreted by our brains, it is reasonable to suggest that our brains are utilizing self-reflection, a critical skill required in abstract thinking and achieve a gestalt understanding of our brain’s working.
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In conclusion, we believe that there are three significant errors that researchers have made in studying AI and brain functioning. First, it is a mistake to assume that all mental functions exists only within the brain and “do not leave their source” as brain wave obviously do. And second, ignoring the potential for further studying as an essential part of the brain and significantly impacting on our abilities to self-reflect and think abstractly. And thirdly, that homo-sapiens are not primarily thinking beings with some un-wanted side-effects of brain processing such as emotions. The truth is that our feelings are central to who we are and not peripheral. The beginning of thought development goes back to the single cell animal that will move away from a toxin in its environment and towards food in the same. This is the most primitive decision a living being makes. It is a display of thinking, the ability to decide whether to approach or move away from something in the physical environment. Attraction and Repulsion is the first duality involved in reasoning, emotional reasoning. Quantitative reasoning appears when a preschool child first learns to count. Verbal/Linguistic reasoning begins early in development with acquisition of receptive language but doesn’t begin expressive language until their first word is vocalized, most often displayed about a year after birth.
By limiting our investigation to only the brain by believing that consciousness only exists within the brain, we automatically diminish the importance of brainwaves as they clearly travel out from the brain creating a measurable field, already being interpreted in a gross or global manner as a measure of conscious arousal. Unfortunately, we have a priori determined the nature and function of brainwaves thus we may have overlooked a potential explanation of how the digital, bottom-up processing of the brain is elevated and extended by the gestalt workings of the mind.
References Here
Fluid reasoning represents the capacity to think logically and solve problems in novel situations. This construct is central to theories of human intelligence (Carroll, 1997; Cattell, 1987; Gray et al., 2003; Horn, 1988; Horn and Cattell, 1967; McArdle and Woodcock, 1998). M ar 28, 2008
Fluid intelligence involves comprehension, reasoning and problem solving, while crystallized intelligence involves recalling stored knowledge and past experiences.
Fluid intelligence and crystallized intelligence rely on distinct brain systems despite their interrelationship in the performance of many tasks.
[1] THE BIOLOGY OF BELIEF Bruce Lipton etc. pg. 145-6
[2] Tolman, E.C. (1932). Purposive Behavior in Animals and Men. New York: Appleton-Century-Crofts.
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