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To leaders and experts, as well as their close associates, their group is significant to their lives. This is much less true for followers and interested non-experts. Both their number and level of interest may wax and wane. In politics, for example, there are many interested non-experts. Just before elections, their numbers increase drastically.

Many groups use the peer review, professional journal combination to promote their growth and influence. These groups are made up of a limited number of credentialed experts, supporting bureaucrats including those who may approve grants and provide other support, and interested non-experts.

In peer review, only other experts are allowed to comment on or criticize the work or research of an expert. The bureaucrats use the comments and criticism to decide funding levels for the experts. It is difficult, and in some cases, impossible, for an informed non-expert to get even an article published in a professional journal. Yet, since everything is connected, the proper expert needs to be exposed to most of my ideas – I want him to read this book.

. . . .

When Victor became President of Austria, the rules changed. Everyone, including Victor, now judged Victor as a winner or loser as President, not as a candidate. The collective thoughts of millions determined reality.

This is a truly wonderful thing. By thinking, we build our own worldview, the most important worldview. Then we can be successful just by thinking we are successful.

. . . .

We want to pursue this, learn how to think effectively, learn how to construct the right worldview, the right reality. We do not want, however, to get confused, to think that understanding this little corner of reality, is our ultimate goal. I do believe that delving deeper into this will help us better understand Never Never Land.

. . . .

What is a Thought? Think about it.

. . . .


I need your help. I have talked about worldviews, how we each have our own, and how our worldview may occasional change. When I think deeply (longer and harder) about a thought, I feel I am glimpsing a little of a thought's true nature. Can you, with your unique Worldview, follow my line of reasoning and also feel that I am right?

I have written about many things - maybe more things and more details than was necessary. I want my writing to support my conclusions. When I psychoanalyze myself (think about my thoughts), I realize my insecurity (You may think I am being ridiculous) may make me give more proof than is necessary.

Before my worldview changed slightly, I wrote about how, if you are a salesman, the internet could help you give a much more productive elevator speech, and thus make more money. I believe what I wrote then is still true, however, things are always changing and it may be a little more difficult today. Also, to me, it just doesn't seem as important.

I have written about branding, describing an alternate universe where everyone wants to be seen as the most wonderful thing in the world, a cute kitten, while, at the same time, branding opponents as the most disgusting thing imaginable, an old cat.

It seems obvious to me that people behave like this on many levels. Based on their worldview, they constantly battle to label themselves the good guy. They imagine a universe where they have succeeded. My worldview suggests they are actively trying to create this universe. My worldview, however, is only one of trillions. You have one vote. Are my musings insane ramblings or brilliant insights? Maybe a little of both?

I want to expand on some of the topics I have already written about - but, in general, I believe a thought is the feeling we get when an individual neuron becomes "excited". This level of "excitement" can vary and the excitement level may be monitored by glial cells. The neuron, on some level, may be branded. The neuron, or a glial cell, is connected to other systems in the body. A "fearful" thought can cause an increase in adrenaline, a rapid heartbeat - our whole body becomes afraid.

We need to know more about neurons and glial cells.

. . . .

What does all of this have to do with the meaning of life? What does all of this have to do with finding God? How does this help us explore Never Never Land?

There are connections, often unseen and unappreciated, between processes. Maybe things we describe here are affected by processes on the other side of the universe. Maybe the processes we describe here are like similar processes on the other side of the universe. Maybe when we describe our universe emerging from Never Never Land, we can glimpse processes in Never Never Land, holding up all of reality. Maybe if we can catch a glimpse of these processes, we can recognize remnants that are still in our universe today.

. . . .

In a neural network, one neuron becomes "excited" and sends electrochemical signals which may excite other neurons. I doubt that the traveling of these signals across the brain are part of the "feeling I am thinking". Instead, the excitement level of the neurons in the particular neural network, along with excitement monitoring by the glial cells, give rise to conscious and unconscious thoughts.

When I speak of a thought, I may be using the wrong word. We all want to think we are rational creatures. If we are, we can look at a problem, find a solution, and then have a better chance to survive. We are in control of our lives. We interpret everything around us to prove we are rational. We feel like we are being rational. We have no problem, however, recognizing that someone else is irrational.

Thoughts are related to neurons, but there is a large emotional part. We think in words, but the words themselves have been branded as good or evil. Can you think of "bloodthirsty" in a good context? It may be more accurate to say "I feel" rather than "I think". I am going to continue to talk about "thoughts", but I may really mean "feelings".

. . . .

Technology has now advanced to the point where scientists can tell when an individual neuron becomes “excited”. I read about an experiment where equipment was used to monitor this activity in the brain of a volunteer.

A neuron is "excited" when it receives input from another neuron and in turn transmits a signal. This signal is electrochemical in nature and is very weak. Electrochemical means the signal takes place in the neuron (actually in a part of the neuron called the axon) and is based on chemical reactions that result in a very weak electrical current. We can now record the strength of this signal.

In this experiment, "scientists" means a group of credentialed researchers standing around a patient or volunteer (for convenience, I'll call him the guinea pig). These scientists have either attached electrodes to the scalp of the guinea pig or inserted probes into his brain. I don't know if these scientists are experts in a soft science like psychology or experts in biology. I don't know how much they know about human neurons or neural networks. They may have studied neural networks, but do not appreciate their power. It may have been years since they last thought about neural networks.

The scientists discovered that, as the guinea pig performed various tasks, different groups of neurons became excited. Each group of neurons is what we are calling a neural network.

What if we imagined a “thought experiment” where our scientists had access to slightly more powerful monitoring equipment? They could record very short intervals of time so that they would not just see a neural network, but which neuron became excited first, second, third, and so on.

The guinea pig is shown a picture of President John Kennedy. What happens in the brain of the guinea pig at the neuron level?

I want to ask some questions that the scientists probably did not ask, or, if they did ask, were probably not able to answer.

When the guinea pig sees the picture of President Kennedy, his optic nerve transmits information from his retina to his brain. Many neurons could receive this information, but only one becomes excited. Only this neuron, out of thousands, seems to be the Kennedy Face neuron. The Kennedy Face neuron, in turn sends a signal throughout the brain. Although an unknown, perhaps vast, number of neurons are exposed to this signal, only a few, as the Kennedy Face neuron did, become excited. These secondary neurons also send signals, resulting in a few more excited neurons. The guinea pig reports that the picture of Kennedy has caused him to think about Kennedy, when he was born, his inauguration speech, his family, his World War II record, his assassination, and other facts.

The neurons that were excited make up one Kennedy neural network.

This little experiment brings up about a million questions. I won't try to address all of them, but let's wade into a few.

When the optic nerve transmits information from the retina to the brain, how is the information coded? This question comes from my computer and data processing background, one area where I could be called a "real expert", rather than just a well informed layman.

If you need to send information from one computer to another, you often have to compress the information first. A small amount of compressed information can be sent more quickly than a large amount of uncompressed information. In this internet age, one computer may be in the United States, and the other computer may be in China. The information will probably go on a long trip where it will pass through at least two communication satellites. To save time, the first computer will compress the information before sending it, and the second computer will receive the compressed information and then decompress it.

When I ask "how is the information coded?", part of what I am asking is, "Is the information compressed?".

Imagine that it takes three seconds for the uncompressed image of a charging cat to reach the brain of a bird, while it only takes a tenth of a second for the compressed image to reach its destination. The question of compressed or not would be very important to that bird.

Some other questions that might be asked are "Why is only the Kennedy Face neuron initially excited?", "How many other neurons are exposed to the optic nerve information and are not excited?", and "Do glial cells have anything to do with this process?".

I don't think we can answer these questions, but thinking about them could lead to valuable speculation, some of which may turn out to be true. Also, I strongly believe that a non-expert with limited knowledge can often ask a question he has no hope of answering, while the true expert, bound by a fixed way of thinking, and obsessed with the minutia of his profession, would never think to ask that question. Once asked, however, the expert would have the knowledge to find answers.

To give a concrete example that applies to this situation. I know what a synapse is. The Wikipedia definition is: In the nervous system, a synapse is a structure that permits a neuron (or nerve cell) to pass an electrical or chemical signal to another neuron. An expert would have much more knowledge about how a synapse operates than I would. It seems possible, or even likely, that the synapse between the optic nerve and the Kennedy Face neuron is acting differently from a synapse between the optic nerve and a neuron that is not being "excited". Maybe the expert can design an experiment that will give us detailed information about processes at the synapse level and we can compare the Kennedy Face neuron synapse and the unexcited neuron synapse.

Let's go back to our latest three questions: "Why is only the Kennedy Face neuron initially excited?", "How many other neurons are exposed to the optic nerve information and are not excited?", and "Do glial cells have anything to do with this process?".

It seems to me that the information being transferred must be more than just compressed. It must contain some key that the Kennedy Face neuron could recognize. Unfortunately, if we think about creating this key, we have to ask "How in the world could the optic nerve know it needs to send the information to the Kennedy Face neuron?". Once it knows that, it can create a key that will be part of the information sent. The optic nerve knowing something about the Kennedy Face neuron is not the main story. The optic nerve would have to know something about many neurons. There would be separate Face neurons for other presidents, a separate neuron for each person the guinea pig knows, even different thing neurons, one for every thing the guinea pig has seen in his life. If you care about science, the earth shattering implication is the optic nerve may have to know something about thousands of neurons.

How much information (regarding other neurons) would the optic nerve have to keep, maintain, and manipulate? I ask this question because, in computer terms, you have to increase your processing power as you increase the amount of information that must be processed.

I can think of one method the optic nerve might use to send information to the face and other neurons that might require less (but still some) knowledge of these other neurons. I don't know if this method would require more or less processing power. I am talking about some kind of cryptographic system.

Let me describe a common cryptographic system that our computer networks use, but in terms of the optic nerve and the face neuron. This cryptographic system uses two keys -- a public key known to all neurons and a private or secret key known only to the face neuron. When the optic nerve wants to send a secure message to the face neuron, the optic nerve uses the Face neuron's public key to encrypt the message. The face neuron then uses its private key to decrypt the message (and becomes "excited" at the same time).

I am sure I am not the first to think of neurons as small computers and neural networks as groups of neurons working together, just like our computers work together on a computer network. If, however, we want to keep our analogy in data processing terms, we can no longer compare our computers to neurons. If optic nerves, and most likely human neurons, bumblebee neurons, and all living cells, have within themselves the processing power to "know something" about four billion other things, we can no longer compare a neuron to a computer. That would be as silly as comparing something with the computing power of the iPhone in your pocket to a child's toy abacus.

When I look at some of the laws, assumptions, and assertions made by quantum physicists, I think they must be talking gibberish. I remember, however, that much of quantum physics has been supported by experiment. You may think I am talking gibberish when I say a neuron in a bumblebee's brain has vastly more computational power than our most powerful computer.

Theoretically, quantum computers have vast processing power. If everything is connected, quantum physics affects neurons, but could neural networks really be quantum computer networks?

What does mankind know about quantum computers? How close are we to actually building such a device? Might this knowledge help us recognize if neurons are, or are not, quantum computers?

. . . .

Human Beings have trouble with large numbers. This is apparent when we study neurons. It is even more apparent when we try to journey to Never Never Land.

I like to think, with my math degree, I have a better appreciation of large numbers than most people. I cannot, however, accurately, without counting, judge the size of a crowd. Fifty people to me is the same as fifty-one.

If you count the people on earth, the number you will get is a few billion. I use the fictitious number gazillion to refer to this number or any other excessively large number. If there were a billion times as many people, I would still refer to this number as a gazillion.

We need to think in terms of gazillions when we study neurons or Never Never Land.

If we add or subtract one from a gazillion, we could never tell the difference – yet our reality might be profoundly changed.

. . . .

I have written about neurons, thinking, and quantum processes. These and other subjects demand thinking about large numbers. I have also began to speculate in a thought experiment about the existence of a “Kennedy Face” neuron that might be one brain's resident expert on all things related to President John Kennedy.

I have not read any further details about real experiment with the guinea pig (human volunteer), or about any other experiments with the guinea pig, or even if more experiments were conducted. I would like to imagine additional experiments I believe should have been conducted and speculate about possible results. We should remember that only a handful of neurons were involved out of 100 billion in the human brain, yet these few neurons apparently caused all of these thoughts about President Kennedy (I am speaking metaphorically - a handful of neurons might well be billions).

I would like to know if the guinea pig has more than one Kennedy Face neuron. As a computer expert, I know that the fewer Kennedy Face neurons (and the associated glial cells) there are, the more powerful, processing-wise, these cells would have to be.

We can imagine a series of experiments where the guinea pig is shown other photos of President Kennedy, some brighter, some darker, some different in minor ways. Is the same Kennedy Face neuron always "excited" first?

We would also be interested in the subsequent neurons that are also excited. Here we have to be both observant and careful.

We believe that learning involves both increasing the number of neurons and strengthening the connections between both the original and the new neurons. If the guinea pig remembers seeing similar photos of Kennedy, the Kennedy connections may grow, a new fact or two may be recalled and assigned to new neurons, and the overall excitement level of the Kennedy Face neural network will change. By being observant, we (or, at least competent scientists) could learn more about the learning process.

We would like to be able to see if the same Kennedy Face neuron is excited no matter which Kennedy Photo is shown. Also, if the level of "excitement” is the same. And also if the same subsequent neurons are excited and to what extent. The problem is, as discussed above, living guinea pigs learn. We need to minimize the effect of how many times a Kennedy Photo has been seen by the guinea pig.

One method we might use is to show the guinea pig a number of photos, including the Kennedy Face photo. Later, maybe the next day (to give the guinea pig time to rest), the guinea pig is shown the photos again, in a random order. Except that a slightly different Kennedy Photo is shown. If the same neuron is excited by two slightly different photos of Kennedy (and, in both cases, this neuron is the first of several excited), this indicates the Kennedy Face neuron has vast capabilities. Would the subsequent neurons excited be the same and would they have the same level of excitement? Another way of asking this is "Is the Kennedy Face neural network unique and stable?

Before we speculate on this question, let us expand the experiment to a third day. We show the guinea pig random photos again, but this time the subjects are younger or older and are posing with family or friends. When the guinea pig sees the Kennedy (no longer just a face) photo, will the first neuron excited be the Kennedy Face neuron, and if so, will the Kennedy Face neural network reappear?

I doubt that the Kennedy Face neural network would be stable. For most people, visual input (like photos) is turned into memories that can be easily recalled. Many would find listing a number of presidents difficult or impossible, but if shown photos of presidents could instantly name them and maybe recite facts about them. This indicates that facts learned long ago are still in the brain, but not easily recalled. Just looking at photos could strengthen the connections between the appropriate neurons, that is, the neural network would be changed.

Another question we could ask is "Is the Kennedy Face neuron part of other neural networks when the initial input is not visual?". For example, if I ask you to tell me about President Kennedy, is it one of the neurons in the Kennedy Face neural network that first becomes excited and does the Kennedy Face neuron become excited when you visualize what President Kennedy looks like. To even imagine experiments that could answer these questions requires a much closer look at neurons and neural networks.

Before we abandon, or at least pause, our discussion of expert neurons, let me tell you about a personal expert neuron of mine – this one specializes in coffee. I believe I have a gazillion other experts to help me with other things.

I have a photo of me as a child, in fact, as me as a baby, still in diapers. I am sitting on my grandfather's knee, drinking from a cup he is holding. A cup of coffee.

In our culture today, giving children, much less babies, coffee is frowned upon. My early, pleasant, exposure to coffee makes me very critical of society's viewpoint on this, and, of course, I can find many studies that support the healthful benefits of coffee. Also, in my very rational, human-like way, I notice the many relatives that lived long lives while consuming multiple cups of coffee per day. I never think of coffee when someone I know dies young.

One drawback to drinking coffee is the splitting headache you endure when you stop. I have heard this headache can last a long time, maybe even two weeks, if you drink several cups a day. I have had one cup of coffee every day since that photo was taken. Headaches have not been a problem – I have never stopped.

The monsters do not serve children coffee in the hospital, but when you have polio, caffeine withdrawal cannot make your headache more intense. When I escaped Isolation Hospital, I quickly returned to my old habits, both good and bad.

I believe I have a “coffee neuron”. Since before I could talk, it monitored the taste and smell of coffee. When I started to think in words, it made these neural networks part of its neural network. Then one morning, groggy and sleepy, I sit down at the breakfast table and took a sip of coffee. My coffee neuron signaled and I thought “Aww – I needed that.”. That simple thought, without even minor variations, has popped into my mind thousands of times – always right after that first sip in the morning.

Strong evidence to me of my coffee neuron. Do you have expert neurons?

. . ..

To understand the level of complexity we encounter when we try to study thought and to understand why it seems life must use quantum processes to handle thinking, let me quote one paragraph from a blog entitled "Searching for the Mind with Jon Lief, M.D.":

One of many brain projects attempts to map the mouse brain, which has a mere 70 million brain cells with 14 million in the cortex. The maximum number of connections for one mouse neuron seems to be 45,000. Mapping this much smaller number of neurons is currently an impossible, monumental project. If all of the existing supercomputers were used for a small region of the human brain, it would take thousands of years to calculate all of the possible connections.

It has been estimated that each of the one hundred billion neurons in the human brain has on average 7,000 synaptic connections to other neurons. It has also been estimated that the brain of a three-year-old child has about 1 quadrillion synapses. It takes about a millisecond (one one-thousandth of a second) for a neuron to select a synaptic connection and send a signal to another neuron.

What we are saying a neuron is doing is receiving signals from one or more other neurons (out of 7,000 possible neurons), from these signals creating a new signal, then deciding to which of 7,000 neurons it wants to send the new signal, and then finally sending the new signal to the correct neuron. The neuron goes through this process 1,000 times per second. It seems likely that this could only be possible if the neuron was using quantum computing processes to make the almost infinite number of calculations needed.

It is beyond our current technology to duplicate the calculating that seems to be going on inside neurons. To do this, we would have to develop quality quantum computers.

It is also beyond our current technology to monitor the results, that is, to track the signals as they leave the neuron one thousand times a second and to record the neurons that become excited by the signals. This recording of signals, when played back in slow motion, would show groups of excited neurons - each group of excited neurons would be a neural network.

Each neural network, in this case, would be a response to an outside stimulus (seeing a Kennedy photo) or the response to another stimulus (for example, thinking about the Kennedy photo you have just seen). For tracking technology to work, the electrodes, probes, or other brain monitoring equipment would have to be under computer control.

As we said, even tracking neural activity is beyond our current technology. The major difference is we can master this technology without quantum computers. Tracking technology could be powered by one or more standard silicon based computers or supercomputers.

It would be productive to imagine experiments involving this tracking technology.

If we imagine our guinea pig attached to an advanced tracking system, we can and will address some questions we have asked. First, however, we should talk about some concepts that, if not invented, were at least popularized by the famous Austrian psychiatrist Sigmund Freud.

An iceberg floats in the ocean with only 10% visible, the part above the surface. The other 90% is below the surface, invisible. Freud said our conscious mind, like the visible iceberg, was only 10% of the total. Most of the rest, almost 90% of our mind, was well below the surface. This was our subconscious mind. Our conscious mind know nothing of our subconscious, but can be affected by it. Finally, there is the preconscious mind. In our iceberg analogy, it is the part of the mind just below the surface. Most of the time, the conscious mind is not aware of the preconscious, but the preconscious mind holds information that can be easily recalled when needed.

Can Freud's iceberg view be related to neurons and neural networks? Could we use our advanced tracking system to find the guinea pig's conscious mind?

We have speculated that the functioning of the neuron (or neuron glial cell combo) is affected by emotion, that at least some neurons are emotionally branded. Life has discovered that a creature that remembers a fearful experience, like almost being eaten by a lion, has a better chance of survival.

A neuron could be branded by more than one emotion, or alternatively, one neuron in a neural network could be branded by one emotion while another neuron in the same neural network could be branded by another emotion. We have discussed fear, but shame is also an emotion. For social creatures, shame is a very powerful emotion.

Shame is an emotional tool that life uses to encourage individuals to conform to the values of the group, usually making the group more competitive and better able to survive.

If you believe in neural networks branded by emotions, it is easy to see how conflicts within these networks could lead individuals to unhappiness and possible death, while helping the group survive. These conflicts play out in the minds of future soldiers, where networks branded with patriotism and the imagined shame of being labeled unpatriotic overcome networks that might lead to safety. The result is war, either justified and unjustified.

Freud felt that the subconscious was made of repressed memories, often based on shameful sexual experiences. I agree that memories can be repressed. Let me speculate on how a (non-sexual) repressed memory might be built in neural network terms.

Coulrophobia is the fear of Clowns. An unknown number of people have this phobia, but it would seem to be more than you would think. It is hard to tell because many adults and older children are ashamed to admit they suffer from this phobia. They have no idea why they fear clowns, but when you put fear, shame, and neural networks together, the answer may be simple.

When I was nine, the monster came again. He said I had polio. Today, I know he was just a friendly dragon. I do not feel he was a friendly dragon.

Let me describe again that long ago time.

I was as sick as I had ever been in my life. For six months, the monster held me captive and tortured me, for “my own good”. I remember it well. When I finally escaped, I knew it was perfectly rational to flee in panic, to avoid even thinking about the monster. I vowed to never let the monster or his friends near again. Yet, today, I must periodically visit ominous offices full of white coated monsters. I must beg a monster for slips of paper, embossed with his magical RX seal.

Some people fear clowns. I should be so lucky. I have researched how people develop Coulrophobia. The progressive changes in brain cells and neural networks during this time is complex. The parallels between this phobia and my fear of doctors seem undeniable.

Suppose a three year old boy meets a clown, at a party or the circus. A big, strange looking guy with a painted face is not funny. In fact, he looks extremely dangerous. The three year old's reaction is very similar to an older boy being attacked by a lion. He can't think, he only wants to escape, scream for help, run. A neural network is formed, but at his age, fear cannot do as good a job of cementing the memory. The fear, however, is there.

When a six year old boy meets a clown for the first time, his reaction is drastically different. The boy is bigger, so the clown isn't quite as imposing. The main difference, however, is the boy now sees himself as a rational being. He can learn quickly. He can figure things out and solve problems. He is mature. He doesn't get upset unless he is truly wronged – like having to go to bed when he doesn't want to. This boy will ask "Who is this guy?" and will later see the humor in asking "Who is this Clown?". This boy will begin building a pro clown neural network.

The three year old boy has a clown neural network. Three years later, when he is six and he meets another clown, he already has a clown neural network - and it is not a good clown neural network.

This six year old also sees himself as rational, but now he is facing extreme danger, a clown. No time to think. He must run, scream, get to his mother for protection.

Suddenly, at this time of greatest danger, something happens that is almost as bad as being grabbed by the clown. His mother is not protecting him, she is laughing and telling him clowns are fun. He knows he can usually trust his mother to tell the truth. There are also older children. They are laughing at the six year old and calling him a baby. He is still scared. He is still crying. Now, however, he is also embarrassed, full of shame.

The clown neural network of this fearful, ashamed six year old cannot be deleted, but it can be modified and new neurons added. A year later, when the boy, now seven, goes to a circus and runs into the ubiquitous clown, we can envision his new clown neural network in action.

We can define the seven year old's conscious mind as the neural network that currently has his attention. We may have to think more about this, but it is a good working framework. In fact, just in writing this, I think longer and harder. Our neurons are sending out a thousand signals a second. Many of these could be thoughts, maybe even affecting our moods. Our conscious mind neural network would have a neuron to slow down thoughts, much like the playback feature on our advanced tracking system. This would change a millisecond long thought like "I love my cat" to a conversational "--- I --- LOVE --- MY --- CAT ---". Anyway, back to our fearful seven year old.

When the seven year old sees a clown, the visual information is transmitted by the optic nerve to what we can call the Clown Face Neuron which is still branded by the emotions of the original, fearful encounter. The Clown Face Neuron still has its connections to other neurons and to systems outside the brain. Adrenaline is produced. The desire to run is there. The feeling of fear is still there.

The connections between the Clown Face neuron and the conscious mind have, however, changed. There are new neurons. Perhaps one is a new Clown Face neuron without the fear branding. The conscious mind could be aware of this neuron and would use it to recognize a clown when he saw one. There could also be new shame neural networks, contemplating, when excited by the original Clown Face neuron, how much they regretted the behavior of the three and six year old boy. These neural networks would repress shameful thoughts and memories and keep them away from the conscious mind.

An advanced tracking system would allow the observation of neural networks in great detail. Carefully designed experiments where, for example, outside influences are controlled, could tease out how mental processing really works. A few questions that could be addressed: What is sleep and what is its purpose? How do neural networks grow? How many different neural networks can an individual neuron belong to? What is consciousness? What is the difference between a conscious and subconscious thought? I could go on, but let's also investigate how advanced tracking could be changed to modify neural networks.

You could integrate powerful lasers with the probes or electrodes of the advanced tracking system. You could then selectively kill individual neurons. Imagine killing the bad clown neuron in a victim of coulrophobia. Would the victim be cured? After treatment, the first time a clown is seen, there is no longer a bad clown neuron to be excited. The signal from the optic nerve would go where? The former victim would know what a clown is. A new, benign clown face neuron could be built, or, the signal could go straight to the newer clown face neuron, the one that had not been branded by fear. In either case, the former victim would be cured. Unless you think longer and harder.

When a new, benign face neuron is built, it has to be connected to the newer clown face neuron (which was created to control the phobia) or else the signal from the optic nerve has to go directly to the newer clown face neuron. In both cases, the newer clown face neuron is involved. It is not branded by fear. Unfortunately, it is branded by regret and shame. Could this cause a problem?

Maybe we should kill two neurons, zapping both the old, fearful one, and the newer, benign one? Now the former victim would have no memory of clowns and would have to build a new clown face neuron from scratch. For the former victim, who is now older, the fear, regret, and shame would no longer be present. He would be cured.

Unless those thoughts of fear, regret, and shame, still buried deep in our coulrophobic's subconscious, somehow made their presence felt.

Potentially, an advanced tracking system with the ability to kill individual neurons could be a great treatment tool for all kinds of mental disorders. First, however, we'd have to perform many experiments on volunteers. These experiments could be described collectively as "zap, kill, and see what happens".

It is easy to see how a machine that can selectively kill neurons could be fodder for science fiction (a better term may be speculative fiction). The hero (to the reader) has wonderful cute kitten values. The owners of the machine want to catch the hero and zap his cute kitten neurons and turn him into a "normal" old cat.

Any stories along these lines would really be based on the unspoken question "what is a mental disorder?". Unfortunately, the answer to that question depends on your worldview.

Sigmund Freud also used the iceberg analogy to describe his psychoanalytic personality theory. Freud believed there were three parts of the human personality: the Id, the Ego, and the Superego. The constantly changing relationships involving these three parts produces the complex behavior we see in people. The Id is concerned with meeting basic needs. The Ego is concerned with dealing with reality. The Superego is concerned with morals.

The following is from The id is the most basic part of the personality, and wants instant gratification for our wants and needs. If these needs or wants are not met, a person becomes tense or anxious; The ego deals with reality, trying to meet the desires of the id in a way that is socially acceptable in the world. This may mean delaying gratification, and helping to get rid of the tension the id feels if a desire is not met right away. The ego recognizes that other people have needs and wants too, and that being selfish is not always good for us in the long run; The superego develops last, and is based on morals and judgments about right and wrong. Even though the superego and the ego may reach the same decision about something, the superego’s reason for that decision is more based on moral values, while the ego’s decision is based more on what others will think or what the consequences of an action could be.

The Id develops first. A baby is only concerned about himself and what he wants. His consciousness (the upper 10 percent of the iceberg) is dominated by the Id. The Ego develops next and as it does, the Id drops into the preconscious, and finally subconscious. Finally, the Superego develops. Now the ego can float in all three levels.

Freud believed that the three personality traits had to be balanced for good mental health. If your Id was too strong, you would not be conscious of it, but your actions would display self-absorption and selfishness. If your Ego was too strong, you would come across as very rational and efficient, but also distant, boring, and cold. If your Superego was too strong, you might feel guilty all of the time, or you could come across as too saintly, someone who thinks they are better than everyone else.

I believe Freud was right, but, on a more basic level, what he was saying could also be attributed to numerous neural networks fighting for control.

What can we say about neural networks relative to Freud's personality traits - thoughts that may suggest experiments for our imaginary advanced tracking system - just in case someday it becomes real?

Before the Id of a growing boy descends into the subconscious, there must be a number of neural networks already there. I would call these quiet, monitoring neural networks. These networks are probably a lot more numerous than you would think. Although they will always remain in the subconscious, they can grow as the boy matures.

We can imagine how one of these might react when the three year old boy first meets the fearful clown. This neural network monitors visual input. The network includes a neuron that controls eye movement, allowing continuous, subconscious monitoring of the room. There is a table with a doll on it. This neural network is not yet connected to any neurons with knowledge of words like table or doll - these are just familiar images, but the doll image is tied to feelings of security and fun. There is also a blue cup near the door, an image tied to food and drink, happy thoughts. Each of these images are reviewed, subconsciously. Each review takes about a thousandth of a second. Then the clown appears in the doorway and the boy's attention moves from the blue cup to the clown.

The visual network is not the only neural network in action. One of the boy's neural networks is monitoring outside temperature. His arms are slightly cold, but he is sitting on his mother's lap and she is holding him. Her warmth feel good and another neural network is excited, producing feelings of security and satisfaction. His audio neural network listens to his mother's voice and other sounds. None are disturbing, some even increase and extend the feelings of security and satisfaction. Other neural networks monitor other parts of the body. One tells the boy he is slightly hungry.

If the boy had been younger, he would have been crying. If he did, his mother might cover his arms with a warm blanket. Surely she would recognize he was hungry and fix that. Now he was smarter. He knew his mother might stop holding him and look for his sippy cup, give him to someone else while she looked for his sweater, or, horrors, make him take a nap. He wasn't that hungry. He wasn't that cold. He would keep silent and enjoy the moment.

The boy didn't realize that his thoughts, although not yet based on words, were a sign that an Ego was already growing within his Id. He just knew that right now everything was nice. Except that one of his neural networks seemed to be getting more and more excited about some kind of clown face.

When the boy's visual neural network scans the blue cup near the doorway, in one one thousandth of a second, it is categorized as familiar and benign. A new scan is started on the clown. Is it familiar? No. Rescan. Is it big? Yes. Rescan. Is it dangerous? Only if it sees me. Rescan. It is looking at me. Send signals to excite emergency neural networks. Rescan. It is approaching fast. Send more signals to excite emergency neural networks into panic mode. Dump clown face image into short term memory.

At this point, the visual neural network is shut down or is put under the control of emergency neural networks until the danger has passed.

. . . .

If we had an advanced tracking system, we might learn much about neural networks.

The status of all neural networks which are altered by the clown could be analyzed carefully. The strength of signals from and to the visual neural network during the milliseconds after the clown's appearance would be informative. When the clown face neuron appears would also be of interest. Is an existing monitoring neuron converted within milliseconds, or is a new neuron built milliseconds, hours, or days later? What can we determine about strength of signals or even their meanings as they cross each synapse?

The question of when the clown face neuron is created actually is related to how memory works.

Wikipedia defines short-term memory as: Short-term memory (or "primary" or "active memory") is the capacity for holding, but not manipulating, a small amount of information in mind in an active, readily available state for a short period of time.

As I have said before, the specialist or expert (or the science writer who is translating the expert's words) are very verbose. In fact, they can write entire books about their area of expertise. An expert in a related field will also be verbose, but in a completely different way. For example, a psychologist writing about short term memory does not write in the same way that a microbiologist specializing in neurons would.

Since I want to discuss concepts from both worlds in order to ask some unique questions, let us expand to a bigger picture and consider long-term memory.

Wikipedia defines long-term memory as: Long-term memory (LTM) is the final stage of the dual memory model proposed in the Atkinson-Shiffrin memory model, in which information can be stored for long periods of time. While short-term and working memory persist for only about 18 to 30 seconds, information can remain in long-term memory indefinitely. Long-term memory is commonly broken down into explicit (declarative), which includes episodic memory, semantic memory, and autobiographical memory, and implicit memory (procedural memory).

After reading the above definition, I had to look up or google a lot of other terms. You can do the same if you like. I did gain a lot of valuable insights, but I was also bored, fighting off sleep as I read about sleep. I won't subject you to needless, long winded definitions, but just bring things up as they are needed.

Both the definition of short-term memory and long-term memory are written by people from the "soft" sciences, for example, psychologists and psychiatrists. As we drill down and contemplate the meaning of some of the specialized terms, we are introduced to the thoughts of biologists and other "hard" scientists who discuss how these terms may relate to neurons and neural networks.

Soft science experiments sometime reveal surprising results and suggest how mental processes, in this case, memory, may really work. We can then look more closely to see if and how hard science proposes explanations based on neurons and neural networks.

I read about the tachistoscope, a device invented in 1859 and used in physiological research until replaced by computers. With this device and the subsequent computers, researchers (soft scientists) could control how long an image was displayed and could be seen (on a movie screen or computer monitor). With this device and the subsequent computers, researchers proved that quick views of images could have an effect. Not too surprising until we are told that a quick view means so fast that the conscious mind doesn't even see the image.

That a quick view of an image can have an effect is not quite as surprising when we remember that a visual neural network is scanning visual input one thousand times every second. We want to know, however, what hard scientists are saying is happening at the neural network level. We want to know if we can have a memory of an image we do not know we ever saw. If we had an advanced tracking system, could we devise experiments to help us understand this process better?

My research has recently taught me that one of the conditions that may affect short-term memory is Post Traumatic stress disorder. From Wikipedia: Post Traumatic stress disorder (PTSD) is associated with altered processing of emotional material with a strong attentional bias toward trauma-related information and interferes with cognitive processing. Aside from trauma processing specificities, a wide range of cognitive impairments have been related to PTSD state with predominant attention and verbal memory deficits.

I need to tell you what the above definition of PTSD means, why I was interested, and why it probably doesn't matter.

My definition of PTSD is as follows and is hopefully somewhat close to reality. People with PTSD think about emotional branded material differently. They obsess over trauma-related memories. Verbal memory is a catchall phase referring to memory for words and verbal items. It is believed that, for most people, verbal memory is on the left side of the brain. Other areas of the brain are recognized as supporting certain functions, for example, the prefrontal cortex is believed to be involved in planning and evaluating outcomes. People with PTSD don't think like other people. One example is they may not do as well as others on tests requiring the accessing of verbal memory.

How do we know all this? One way is to test groups of people, some with PTSD and others without (the controls). The researchers use Magnetic Resonance Imaging (MRI) technology to measure brain activity. One branch of this technology is called functional magnetic resonance imaging (fMRI). A common form of fMRI measures what is called the blood-oxygen-level dependent (BOLD) contrast. BOLD is based on the fact that blood flows to the part of the brain that is active, that is, the neurons are excited. Using fMRI technology, neural maps can be created for both PTSD and non PTSD subjects - these maps being created while the subjects are being tested. These maps show the PTSD subjects are not thinking "normally".

Why was I interested in PTSD? On a cursory level, PTSD seemed related to clown phobia. What if the clown had not been benign? What if the clown had had an ax in his hand and murder in his heart? What if he had left behind a scene of mayhem and a single surviving baby boy. Would the boy have Clown PTSD for the rest of his life?

After further review, however, I doubt that a three year old's encounter with a murderous clown would be the same kind of situation a future PTSD victim would face. A short episode of extreme fear is not the same as weeks of almost continuous fear punctuated by moments of mayhem and horror.

We always want to think we are smart, but we also want to think reality is simple - we want to believe that if one thing happens and then another thing happens, the two events are related. We want to believe that the first event caused the second, and if we see the first event again, the second event will soon follow. This is sometime true and creatures that believe this will, on average, live longer and produce more offspring. In the case of PTSD, however, the victim may have decided that any loud noise, not just an explosion or gunshot, is a precursor of death and horror.

We may want to think that reality is simple, but it is not. Life is simple relative to reality, but it is not simple either. Life, working under evolutionary pressures, has had 1500 million years to make things complex. You can see this when you examine the clown face neuron in the adult brain of a coulrophobic (clown fearing person). This neuron is not just one of 100 billion neurons, it is one out of 10,000 different, specific kinds of neurons in the brain.

Researchers have shown that emotions affect mental processes including memory. If we try to tie several facts together, maybe we can come up with some new thoughts. Let's list a few facts that have a good chance of being true.

        (1) A neuron in combination with one or more glial cells (often, when we speak of a neuron, we may also mean glial cells) has tremendous power, both in terms of how fast it can process information and how much information it can store.

        (2) A neuron can affect how we feel by processing emotions and taking various actions. These actions could be in response to both negative and positive emotions - for example, we could get a feeling of satisfaction when we complete a task. Exploring this area could give insights into how we form good and bad habits.

        (3) Much (I hate to say all) of this action starts when a neuron processes an incoming signal. If communication to other neurons is required, a glial cell will interact with one or more of the 7000 synapses available.

        (4) There are many kinds of different emotions and a neuron can be subjected to different levels of these emotions and for different durations of time.

        (5) Sleep may be necessary for a neuron to complete tasks it cannot complete while handling normal incoming signals. One task, for example, might be to decide what to do with all the information received during a busy day. A neuron may have the capacity to store a day of information (a tremendous, but not infinite amount of data). A neuron may not be able to contain a month of data. There are other hypothesis for why sleep is needed. More than one explanation may be true.

When I think about these five facts, some of the thoughts I expressed only a few pages ago seem either wrong or in need of clarification to more accurately describe what really may be going on.

If you remember, when describing the visual neural network of the three year old at the moment he first noticed the fearful clown, I stated that right after more signals were sent to excite emergency neural networks, the clown face image was dumped into short term memory and then the visual neural network was shut down until the emergency had past. All of this was happening in a few milliseconds.

When I spoke of dumping the clown face image into short-term memory, I was probably letting my computer expertise bias my thinking. In a computer, memory, which consists of bits with values of either "1" or "0", are available to the central processing unit (cpu). The cpu performs calculations on these bits which yield new values (bits). Bits can also be written to or read from external storage devices like disk drives. When a disk drive is read, bits are copied into memory. If you are a computer person, it is important to know that, although it can be done in the blink of an eye, it still takes much longer to read from or write to an external storage device than it takes for a cpu to access memory and perform calculations on bits.

To a computer expert, what we are calling memory in the last paragraph is really short-term memory, and what we are calling short-term memory is really long-term memory (the information has to be read from or written to a disk). What we are saying is we are taking the thousands of bits of information that describe the clown face (which is already in the clown face neuron) and are writing (dumping) these bits somewhere else. Where is "somewhere else", how do we dump, and why does this not make sense?

The "somewhere else" would have to be another neuron. The idea is the clown face data is very important because the clown has been determined to be a threat. This important information needs to be immediately transferred to another neuron for safe keeping. Maybe this is a neuron devoted to keeping dangerous images.

When we back off and think about the job of what we are calling the clown face neuron and we also think about how powerful this neuron is, we can begin to build a better picture.

The job of this neuron is to evaluate visual data coming from the optic nerve. As the eye moves from image to image, this neuron evaluates, and probably records, each image. It may evaluate and record up to one thousand images per second.

When the clown face image is evaluated, this neuron sends signals to one or more other neurons. We say the neuron has become "excited". The signal could be, but probably isn't, as simple as "big, unknown, dangerous looking, ugly man approaching". Also, within the body of this neuron, or perhaps within certain synapses, out of thousands of possible molecules, one or more new molecules may be created. These could give us a feeling of slightly increased interest or apprehension. At this point, the neuron, which we are now calling the clown face neuron, will return to its regular job, evaluating visual input from the optic nerve. Even when the eye is closed, the clown face neuron evaluates blackness until the eye reopens. The clown face image doesn't have to be dumped anywhere - it remains in the original neuron.

Neurons have the ability to move or be moved. In fetal development, they move long distances to reach the brain. Later, they can move within the brain. We have to ask the question “why do neurons need to move?”. One answer may be that glial cells or other neurons have decided that the observations of a neuron are important or not. If, for example, a three year old has been frightened by a clown, it may be decided that his clown face neuron should remain close to the optic nerve to look for future clowns. This neuron already has lots of information about clowns. The older child, on the other hand, on seeing a clown for the first time, will gather the same information about clowns, but without the fear. It may then be decided that this clown face neuron can be safely moved away from the optic nerve, becoming, over time, part of normal memory.

It may well be that the fifth "fact" above, which were observations about sleep, can tie together and explain a lot of what we observe in the world. It is, however, premature to go there yet. Instead, let me remind you that there is an estimated 10,000 different kinds of neurons in the human brain.

If we consider the auditory system, we start with the auditory nerve, which is also called the cochlear nerve. The auditory nerve monitors the movement (caused by sound) of hair cells in the inner ear and transfers information to an evaluating neuron deep in the brain (to an area near the brain stem). This is, of course, a very simplified version of what is happening. In this simplified version, I would like to compare the audio evaluating neuron to the visual evaluating neuron and say they are similar, but different. They are different because Life has had at least 300 million years to tailor these neurons to their specific tasks while, at the same time, trying to make sure the particular creature (in this case, human) survives.

I may have some of the details wrong. For example, there is more than one kind of sound. Words, thunder, and music are all different sounds. Maybe there is, in the audio neural network, a word evaluating neuron, a loud noise evaluating neuron, and a music evaluating neuron. A few people hate music. Maybe music is being processed by their loud noise evaluating neuron.

An expert may know the answers and be able to accurately describe these neural networks. Or we may be able to use current or future technology to "fill in the blanks". These kinds of details, however, do not affect our overall arguments.

These two, as well as numerous other neural networks, are actively monitoring our environment and responding to it. We can, however, do more that just monitor our environment. Let us look at neural networks that are trying to improve us and create a better, happier future reality.

On a typical weekday, an eight year old boy comes home from his third grade class. He has about an hour of free time available. What will he do?

The boy picks up his basketball and, as he has been doing on most weekdays for the last year and a half, heads for the goal in his backyard.

A simple decision - but a vast array of neural networks support and oppose this simple action.

When the boy glances at the clock, neural networks evaluate the image, interpret its meaning, and cause the first conscious thought (time for basketball practice).

Immediately, other neural networks produce images and thoughts of his new Batman comic book, desires to read it now, and feelings of sadness (there is a molecule for that) that he has to practice basketball. But why does he have to practice?

The answer, of course, is other neural networks. These networks make thoughts and feelings that easily overwhelm "bad" thoughts like "Batman", "I'm too tired", and "It's too hot". Amazingly, the boy may be consciously aware of the bad thoughts and feelings, but not of the good. He may actually dread practice, but do it anyway. Why?

The answer probably could be found at some point a couple of years ago when the boy was six and was playing for his church's team (for five to seven year-olds). You could say he received positive reinforcement at that time, but it was really that plus some happy accidents. His mother and father had always encouraged him - saying he was a great basketball player, a great t-ball player, a great soccer player, even a great tennis player. He trusted his mother and father, but still.

On the other hand, he did notice that he was as fast and coordinated as the other kids. He even seemed as good as the kids that were a year older. And then, as if to emphasize he really was good, in their first game (which they won 8 - 4), he threw the ball up and it went in the basket! The crowd cheered, his parents cheered, his team-mates cheered, and the coach was excited. His coach even exclaimed that if he practiced hard, he could be a superstar. The boy wasn't even sure what a superstar was, but it sounded great. Maybe basketball was his game.

During that season, his father encouraged him to practice at home - and the more he practiced, the better he could shoot. And, of course, the better he shot, the happier the game time experiences were. He was now a boy who recognized the value of being dedicated to practicing. We still haven't, however, given a reasonable explanation of how the boy became obsessed with basketball practice (the average 8 year old doesn't usually practice almost every day for a year and a half).

We can call the boy obsessed or abnormal, but in this case it is an obsession we generally admire and celebrate. We say he is dedicated. This obsession is the very basis of exceptional success.

Random events can drastically change our behavior and our worldview. A few months before our six year old started his successful basketball career, he started his first soccer game. He was immediately run over by a seven year old. The boy felt like he had been hit by a truck. He promptly landed on his nose. They stopped the blood and the tears, but fear ran with him from then on. Fear was with him every game and his play suffered, Soccer was not his game.

After the last basketball game that year, there was the usual excitement and celebrations. Not much was made of next year - a year to young kids is forever. The next afternoon, the boy and his father were shooting a few baskets. His father said it was important to keep sharp for next year. They paused when a neighbor stopped by. The boy went into the house for a glass of water.

The boy's mother was in another room, talking to several of her friends. Women, it seemed to the boy, had more fun when they talked together than did men. They would cover more subjects faster, sometime even talking at the same time. The boy didn't know the other women, except for one, the mother of one of his friends. He was sure none of them even knew he was in the house.

Just as he was about to go back outside, the boy heard his mother say "I sure am proud of my boy. He loves basketball and practices everyday. I didn't know a kid so young could be so dedicated.".

Several of the boy's neural networks evaluated the word "dedicated". He had heard it before, but didn't know its exact meaning. It was tentatively labeled "good". This label was strengthened. Probably one, maybe more, evaluated his mother's whole statement and categorized it as a compliment - definitely a sincere compliment. This neuron built molecules that made the boy feel good, proud. These feelings lasted, for a while. And these feelings could reappear whenever the boy remembered this episode. And even when he did not.

Speaking of not remembering, the boy did not remember his first friend who moved away before either boy had their third birthday. He did not remember his friend's older brother. He did not remember his friend's thin sandy hair and round face, even more babyish than most others his age. He did not remember that he saw his first baseball at his friend's house. He did not remember the small, red, hard, wooden bat.

The first thing the eight year old boy does when he starts to practice is to imagine a cheering crowd welcoming him to the court. Somewhere in his mind, a neuron makes him feel good. That neuron, or another, also realizes the boy has overcome the bad neural networks that were trying to keeping him from practicing. The good feeling increases.

Now down to business. The boy imagines an opponent, hands raised, between him and the goal. The boy fakes one way, dribbles the other, leaps, and launches a shoot. These simple actions are supported by and are the results of numerous neural networks. Dribbling the basketball requires the right signals to the right neural networks and to the right nerves and muscles at the right time. These actions have long ago retreated from the boy's conscious mind, but they can still be improved.

When the ball is shot, again it is important that the right signals are sent to the right neural networks and to the right nerves and muscles at the right time. In this case, the hands and arms and the feel of the ball is more important and boy is more aware of this consciously. Now, at least one neuron, with input from many senses, tracks the results.

With each shot, the boy feels a short, temporary emotional response - a response probably caused by one neuron labeling a shot with one of a possible ten thousand molecules. After many shots, the boy thinks to himself "I didn't shoot very well today", "I'll do better tomorrow", "I just need to practice more" and, subconsciously, "I am proud I am so dedicated". As the boy heads into the house, these thoughts are also labeled.

When the boy's first friend hit him with the little red bat, it was an accident - probably. No child his friend's age could be evil. Some kids can have a more prominent ID, a less developed Ego. They can be more accident prone. The boy doesn't remember his mother holding him tightly, a cloth to his bleeding head, comforting him, saying "Mommy's here, we're OK. We need to watch out for those bad baseball bats". The boy had forgotten all this. He had also forgotten, before he even knew the words to express it,that he felt that his first friend, Little Stevie, had hit him on purpose. Anyway, he never saw his friend again.

Two years before we first met our dedicated eight year old, he played his last T-Ball game. He was an average player. When the ball was placed on the T, he could sometimes hit it, sometimes not. When the ball was thrown in the air, he would try to catch it, but he was always a little afraid.

The next year, a week after his successful basketball season, his church had their first baseball game. The boy was one of the younger, smaller players on the team.

The boy didn't bat the first inning. He played the outfield, but only one hit came his way, weakly, on the ground. He managed to stop the ball and throw it back to the infield.

The next inning it was the boy's turn to hit. He carefully selected a hard protective helmet. He looked for a bat. They were all red. The boy entered the batter's box. The pitcher was a big kid. The boy had noticed that he threw hard and kind of wild. The pitcher took off his cap and wiped his forehead. He had thin, sandy hair and a round, babyish face. Somewhere in the boy's mind, a neuron remembered and the boy felt fear. The boy struck out. Each swing missed the baseball by so much that it was embarrassing.

"Man", the boy thought, "this is worst than soccer".

When he got home that afternoon, his mother ask him how was baseball.

"Fine", the boy said. Then he went into the backyard to practice basketball.

A few hours later, the boy ended his day with his usual prayer:


I pray the Lord my soul to keep,

If I should die before I wake,

I pray the Lord my soul to take.

. . . .

We have no plans for any further discussions of “soul keeping” or “soul taking”, but at some point we will think longer and harder about sleep. It may have extensive and unexpected influences on mental processes such as a boy learning to play basketball. For now, let us just quote from Wikipedia: Sleep is a naturally recurring state of mind and body characterized by altered consciousness, relatively inhibited sensory activity, inhibition of nearly all voluntary muscles, and reduced interactions with surroundings . For now, however, let us return to neurons, neural networks, and quantum computers. Maybe, we will ask an irrational question or two – like, “Do quantum computers need to sleep?”.

. . . .

Suppose, by hook or crook, I have persuaded a member of the lgtbq (lesbian, gay, transgender, bisexual, questioning) community to read this book.

My neural networks are different than those of the members of this group – but there are many similarities. All neural networks, from man to bumblebee, are alike in many ways.

What if there is an expert who is renowned in his professional group? Perhaps he is a clinical psychologist - a clinical psychologist is a person who has undergone extensive education and on-the-job training to enable them to help in the diagnosis and treatment of the mental illnesses and disorders that are prevalent throughout society (from Or, she is a psychiatrist – a psychiatrist is a physician who specializes in psychiatry, the branch of medicine devoted to the diagnosis, prevention, study, and treatment of mental disorders (from wikipedia).

What if the expert I need is a member of the lqtbq group, but not as an expert? He or she is only an interested non-expert in this group, but is an influential, practicing expert in a professional group of psychologists or psychiatrists.

What if this person of interest is friends with the member who has read this book?

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