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197. Brain and Computers Compared (Revised)

28 Dec

Brain-Vs-Computer-Pic2This essay is an addendum to my previous blog-193 “Brain uploading ideas are nonsense.”  It also provides my understanding of what is known about human brain functioning.

Those interested in downloading a human brain into a computer, and have it function, such as answering questions, should consider this. Although the human brain can be called a computer, it is profoundly different from a man-made computer. THE FIGURE above illustrates the fixed regularity of a computer (upper box) with every component specified and with definite location. The Brain below shows a changing and branching structure, where the actual array of components is the “program.”  Every human experience makes at least a slight structural change. Converting from an entire brain configuration with quadrillions of control points,  to an equivalent computer representation, I assert is impossible. (More explanation below.)

BRAIN AND MAN-MADE COMPUTERS ARE VERY DIFFERENT

Man-made computers have a FIXED structure of electronic components. Modern microchips have thousands of transistors and other components in a well-defined, set pattern. Computer programs, cause the chips to function. When a computer is activated by a program, it makes use of many of the components, such as microscopic transistors, so that something meaningful can go to output devices like printers or screens. In a word, the electronics are fixed and the program varies. Note: a “computer program” is a set of instructions that can be written down or typed into a file that can be “read” by a computer. It tells the computer how to utilize its well-defined components in performing certain tasks. There can be many programs to provide for a wide variety of computer functions.

The human brain is nothing like this. A live brain in a body, is constantly changing. Instead of using an external set of programming statements to control the action, the control components themselves (such as transistors) quickly vary to produce a certain output. These variations include additional nerve cells, additional connections, and each connection (a synapse or gap junction) can undergo substantial change. A synapse, based upon its chemistry and inter-connections, can be more excitable, blocked, or anything in between. The nerve cells, axons, and dendrites form branching structures that provide many paths for its operation.

THE BRAIN FUNCTIONS BY CHANGING ITS STRUCTURE

If you look at a magnified computer microchip you will see regular rows of components. The components will vary in different places, but within each part, there is exact duplication.

But in a brain, you will see great variation in size, shape, and connectivity. The “program” is built into the “brain electronics” and varies as the individual is exposed to many different environmental factors, such as learning, imitation, memorization, food supply, social features, etc.

THE BRAIN IS LIKE A CITY, WITH MANY ROADS AND PATHS

Here is a helpful analogy. Think of the brain as a city with millions of roads and pathways. The sensory systems, like vision, hearing, and touch are roads leading into the city — and there are roads going outbound causing the movement of muscles, activating vocal cords, affecting glands, etc. Between the inputs and outputs are millions of pathways with wide streets and narrow paths, free-flowing and constricted in various ways, all to provide something meaningful. At millions of junctions (synapses, etc.) there are traffic cops that speed things up or block the passage. If someone pinches your arm, action potentials flow down wide roads (axons) leading to the brain and spinal cord. Within these structures there is a maze (inter-neurons) that quickly processes the input information and activates outbound pathways, or simply stores info. (This maze is where complex thinking takes place.) The outbound paths (motor nerves) lead to many muscles that can move your arm, body, and make you say “ouch.” If you are pinched over and over again, the relevant pathways tend to widen, causing increased flow and a more efficient reflex. In our city (brain) there are also archive centers that store memories, and other mechanisms that enhance the whole process.

The ability of a brain to function in this way developed over several billions of years. It is a marvelous structure and its exact functioning at the nerve cell level is still unknown. But we can make good educated guesses as to how much of it may work. We don’t know exactly how words and ideas are stored. And we don’t know exactly how millions of memories are accessed during a wide range of operations, and how a brain creates an essay or scientific theory. Yet, the fact that there are many trillions of “control points” (like transistors) suggests that amazing things can result.

A DEAD ISOLATED BRAIN CANNOT PERFORM IN ANY WAY

I might add that a disembodied dead brain can never function like it did live in a body even if fully preserved. Cutting out a brain removes inputs, outputs, the spinal cord, and feedback loops that are critical to functioning. And would involve damage to the brain itself. A removed brain can never be the same as a live intact brain so any hope of living-on in a computer representation is impossible.  Any sectioning of a brain would destroy many interconnections.

Consider this fantasy. You transfer a brain into a computer, and it can talk. Most likely it would scream, “I can’t see, I can’t feel my legs or arms, I can’t hear, I can’t touch  anything,  where am I, HELP!” How could you talk to this isolated brain that has no ears. So you would really have to save a whole head and even the spinal cord. As you contemplate all of these difficulties, it is clear that trying to save a human brain, which can function, is nonsense. Also, for all the reasons outlined above, it is not possible to “read out” specific thoughts or ideas, by any brain recording method.  (Note: recording sub-threshold “thoughts” from vocal cords is not a brain recording.) 

I might add that although uploading a useful brain, or reading specific thoughts, is not possible, what is remotely possible is a good understanding as to how a brain functions at all levels. This could take decades or even centuries, but it is worth discussing and exploring.

 

193. Brain Uploading Ideas are Nonsense

26 Nov

Several writers have suggested that “someday” technology will advance to the point where a brain can be “uploaded” to a man-made computer, where it will be able to function and communicate with us. In some cases, these writers seem desperate to live on after death, by transferring themselves into a computer where they will continue their life. Here are the names of some brain-computer “speculators:” Ray Kurzweil (newsletter), Michael S.A. Graziano (TED talk Oct 2019), Greg Gage (TED talk June 2018) and several others. Most of the “speculators” are brilliant people, who are simply overly optimistic. But a company called Nectome will preserve your brain (“backup your mind”) so that it can be scanned hundreds (?) of years from now (deposit is $10,000). See MIT Tech Rev, Mar 13, 2018.

I am writing on this subject not only to challenge extreme speculation, but because this discussion serves to illustrate the complex nature of our brains and certain technology limitations.

My position is that this thinking belongs to science fiction because there are insurmountable obstacles for this endeavor. It is true that we can explore smaller and smaller biological objects. And computer memories continue to increase in miniaturization and capacity. But there actually are limitations because “matter” has certain limiting features. For example, our units for computer memory are close to the molecular level in size and will soon reach a limit. The speed of computers is limited to the speed of light. Even if we can ultimately reach these limits, it is likely that reliability will decrease. Certain “cosmic rays” and other factors will play a role. I maintain that the laws of physics and chemistry make real limits to tech advancement, that can never be overcome.

I think writers should not bother us with extremely unlikely speculation unless they actually can propose some ways to overcome obvious limits. I could say that someday we will travel to and explore, the inside of “black holes,” or travel to the center of the earth. But there is no value to idle speculation and it only creates confusion for the general public. Companies like Nectome (see above) will collect your $10,000 for something not possible.

Below are some relevant details.

We start with the dificulties in brain scanning. For helpful information on brain control points, see Mark Mayford et al, Cold Spring Harbor Perspectives in Biology, “Synapses and Memory Storage”, June 2012. For a simpler explanation, see Deborah Halber, Brain Facts.Org, Storing Memories in your synapses, Oct 11, 2018. Also very helpful and fascinating are Google images. Search under neurons, gap junctions, synapses, etc. and add the word “type” like “neuron types” to see more variation. As I was writing this, I looked at “gap junction types” and was amazed by the recent advances in this area.

Here are a few brief definitions:
Control point: either a synapse or gap-junction. It is like a transistor in a computer.
Synapse: a connection between two nerve cells, using chemical transmitters, which cross a tiny gap.
Gap-Junction: a connection between two nerve cells, where the cells actually touch.
Action potential: an all-or-none digital signal that transmits info up to a distance of several feet.
Axon: a long extension of a nerve cell (neuron) that carries forward info in the form of an action potential. The axon is like the wire connecting two telephones.
Dendrites: a short extension of a neuron that receives an action potential from an axon.
Nerve cell body: The cell body is supportive and provides nutrients for the whole cell. It may or may not directly contribute to info passage. The cell body has projections called axons and dendrites, which carry info in the form of action potentials.

The first question is whether you would be working with a living or dead brain. Let us start with a dead brain. In order to extract the brain itself, you would need to cut numerous inputs and outputs. The most important structure removed would be the spinal cord, which is considered a part of the central nervous system. Everything cut away from the brain destroys important feedback systems because the brain is highly interactive with the rest of the body. It is possible that even advanced thinking involves feedback loops with the eyes, nose, vocal cords, major muscles, skin receptors, etc. A cutaway dead brain might say nothing but “ouch.” Any type of brain cutting or sectioning would destroy important connections. Any type of deeply penetrating electrodes or laser beams would be partially destructive and location would be likely impossible. Many systems such as circulation and nutrition would not function and could not be fully studied. The brain emits hormones and is affected by chemicals in its blood supply. Most of these chemicals function with feedback loops and could be vital for  understanding. Scanning a dead brain might be possible, but much of the vital biochemical info would be unavailable. Even if all the nerve cells were available for some type of non-destructive scanning, the extremely tiny control points (like transistors), such as synapses would only be superficially informative. To summarize, a dead brain makes unavailable much vital info regarding its functioning and would be useless to transition to something functional.

A live brain would have all the relevant chemicals and structures, but presents another set of impossible difficulties. Who would sit still for months with millions of holes in his scull for electrodes. Or sit still for laser scanning for months to get all the connections and their efficacy, if this were even  possible. Any deeply penetrating laser beam would cause some damage or produce limited results. How would a laser beam record the efficacy of synapses or gap junctions. Also extremely important is the dynamic nature of the brain. Synapses are constantly changing in efficacy and number, and there is internal movement caused by the circulatory and nutritional systems. There will never be a way to reliably record from this impossible dynamic system with extremely tiny and numerous structures. And even if you could do some good recording from a limited area, covering the whole brain and spinal cord could take hundreds of years.

Here is a summary of the complications of brain scanning:

1. There is a very large number of components, ultimately hundreds of trillions, and sufficient information from all the components would require perhaps a thousand bits of info. The final count for all the info necessary for understanding a brain would be well into the quadrillions.
2. In addition, there are numerous  analog aspects, which trigger action potentials (digital). A synapse will only produce an action potential if it reaches a certain (analog) voltage value.
3. The living brain is a dynamic system in which the control points are constantly changing, due to use and disuse, nutritive and other factors.
4. One would have to work with tiny structures, close to the molecular level. Any prolonged scanning could and would often fail because of spurious movement. A bus driving by, or minor earthquakes, or a scientists steps could disrupt scanning. Blood flow could also disrupt.
5. If you are recording analog info at a synapse, for example, you might need to record for several minutes or longer to understand its action. Even a one-second recording for a trillion synapses would take centuries.
6. Scanning with glass or metal electrodes would cause damage to the brain cells. You might try some kind of laser system, but to go deep into the brain would require a powerful beam and  would cause damage.

For each of, say, 500 trillion control points, you would need the following data to fully understand how it functions.
1. Its exact 3-D location relative to some reference point, like 4.4342343 inches left, 3.4544546 inches right, and 3.66767667 inches deep.
2. A complete description of all its connections to other control points. Could be a thousand of such connections and the nature of each connection must be described, including its location, synapse or gap junction, neurotransmitter and any modifications to synapse efficacy.
3. Each synapse has a pre-synaptic and post-synaptic (receptor area) characteristic, which would take a 1000 or more bits to describe.
4. Gap junctions must be described by their exact location along axons and the efficacy of their connection, which would depend on the area in contact, and other factors.
5. Making sense of all the interconnections, we are definitely looking at many quadrillions (a quadrillion is 1 with 15 zeros) of data bits, probably several hundred quadrillions. It would take centuries to record all of the information.
6. The amount of data would require, probably hundreds of hard drives. How could this mass of data ever be organized and converted into a functioning “computer brain.”

.     THE HUMAN BRAIN IS A VERY UNIQUE TYPE OF COMPUTER

But, let us say that after several centuries you are able to overcome all of these problems (not likely) and you complete a scan of the brain, spinal cord (part of the CNS) and have info on inputs and outputs; all stored on a thousand (or more) giant external drives. How in the world would you be able to turn this into something useful. The human brain is a computer, but it is profoundly different from man-made computers, which are entirely digital and have a fixed structure. The human brain is a complex combination of digital, analog, and chemical operations, which is constantly changing whether sleeping or waking. It has a unique branching (tree-like) structure unlike anything man-made.

You might ask, could we someday construct a computer with the same electronic characteristics as the brain to make transfers easier. I think it is possible to someday build such a computer, but uploading info from a living brain to this computer would not be possible, because connections in this type of computer are developed through experiences (a huge variety of data inputs). For example, in a younger person, every time you learn something, there can be new nerve cells, new axons, and a variety of changes to many synapses. In an older person there may be a few new nerve cells, but there are many changes in synapses and probably other structures.

At this point, you might say, so what; after a thousand centuries, we will be able to overcome all of these problems. Which brings us to another point: Does it make sense to make theories about things that we will never be able to prove. P. W. Bridgman (Nobel Prize winner in physics) says don’t waste your time. Maybe we should leave “uploading a human brain” to the science fiction writers, particularly if you have no special facts or methods to make radical ideas more acceptable.

One more point, on a related issue. Although I assert that complete scanning or uploading a brain is likely not possible, a fairly complete understanding of how the brain works (at the level of synapses) may be possible someday. 

 

 

 

131. Tech Advances Needed for Survival

8 Dec

I read a wide variety of publications and often find that great technological advances are met with fear and inappropriate limitations. Our planet is rapidly changing by increasing populations and by ignoring important factors like climate change. People are afraid of GMOs, automation, robots, vaccines, DNA innovations, and even medical pills. All of us on Earth are facing very serious problems, and we must rely on reputable science to provide solutions. Below is a brief discussion of three out of the many major issues, which I hope will serve as a stimulus for further research.

GMOs.  I provided detailed info on GMOs in a previous blog (number 87). The simple fact is that nature (without warning us) is constantly changing plant and animal DNA. Evolution selects for survival, not for the human health of a food source. On the other hand, when scientists develop a GMO, we know about it, and it can be tested for health factors. Lets promote GMO evaluation and research, and not abolish them.

CLIMATE CHANGE TECH.  Failure to deal with man-made global warming (see my blogs number 34 and 126) can lead to changes in ocean currents and wind. The consequence will be new patterns of flooding and some normal areas will become deserts. These changes will cause serious hunger problems and horrible mass migrations, unless we deal with these issues in advance. There is research on technology that could reduce the greenhouse gases in the atmosphere, and there are other tech innovations that can help  us. Let’s encourage and financially support tech and scientific research in this area.

ROBOTS AND AUTOMATION.  Many people (particularly workers) are fearful of advances in this area. Consider this: robots and AI are now used extensively in many industries (e.g. auto manufacture), and unemployment in the USA is way down, and there are no other problems of note. Like any other  tech, robots must be programmed and used carefully. In the future, robots could help shorten working times and improve worker safety. 

CONCLUSION: TWO PATHS.  We have serious choices to make. We can put money and effort into new tech and science, or take the negative path. It is very interesting that some in our current gov do not trust experts in climate changes, but do trust experts in military details and weapons development.  Could it be that climate solutions negatively affect greedy rich manufacturers, while the rich and powerful enjoy better weapons to preserve their enterprises.  

Here is what I think! Any tech innovation has some element of risk, which can be minimized by hiring top experts for evaluations. On the other hand, I think discouraging innovation can be much more dangerous.  Worldwide current thinking, if not corrected, can lead to major wars, starvation, worse mass migrations, and horrible increased poverty. Encouraging science/tech education and support is crucial.

 

 

116. Brain Complexity

5 Jul

In my Blog-114, I provide some information on brain micro-structure:
“Our nervous system is composed of billions of nerves with around 150 trillion interconnections called synapses, and other connection variations. Further, each synapse (which functions like a transistor) has a complicated and variable structure. The nerve cells, their branching structures, and connections, provide all of our simple and complex behaviors.”

In my study of neuron science, I often see proposals and conjectures
regarding total brain simulations, and even the transfer of stored brain info
to a gigantic computer as a way of prolonging life. One speculator proposes that a person’s intellect could continue after death.

My study of all these conjectures suggests that the writers do not
appreciate the size and levels of brain complexity. My assessment is that
our current and future knowledge will not be capable of producing any
such copying or sizable transfer. Perhaps in 400 or 500 years different viewpoints will be more acceptable.

What follows is a further description and clarification of brain complexity.

A computer has transistors, diodes, resistors, conducting wires and other electronic components that function in concert to provide logic, control,
computation, sensory systems, memory, and information transfer over a
distance.

Analogous systems in the brain are various types of connections between
nerve cells, and elongated cell structures (axons) that are like transmission
wires. The electrical pulse that is mostly used for communication over a distance
is the “action potential.”

I could include, here, a few relevant pictures, but to really see most of
the known variations just use your browser to search “nerve cells” and also
“gap junctions.” (click “images” at top of page). Many of the pictures are
very current and show an amazing variety of structures.

There are two types of connection: chemical (synapses) and electrical (gap-junctions). The terminology can be a little inconsistent but the principles are clear. Neurons have (separate) sending and receiving points. For cells A and B to communicate, a sending point (terminal) of cell A must be in very close proximity to a receiving point (receptor site) for cell B. If the connection is a chemical synapse then the sending point of cell A sends transmitter chemicals across the gap to neuron B receptor. Sending is triggered by an electrical signal (action potential) that causes the release of a chemical (transmitter). The receiving point (or receptor) generates a transmittable signal when enough transmitter is received. Transmission can be excitatory (producing action potentials) or inhibitory (preventing action potentials). Some examples of common neuro-transmitters are acetylcholine, epinephrine, GABA, ATP, and Serotonin. There are about 25 different known transmitters.

Electrical connections between nerve cells operate similarly, except that the
excitation is more direct and transmitter chemicals are not used. Gap junctions
mediate electrical excitation by opening gates that allow the passage of ions.
Ions are tiny charged particles (atoms or molecules) that function in transmission. There can also be transferred electrical excitation without specific gap-junction structures, if parts of cells are making actual contact.

Further functioning (and more complexity) is related to the number of sending points that simultaneously contact a single receptor. A single nerve cell (neuron) could have hundreds of sending and receiving contacts and direct ommunication with many other cells.

Another layer of complexity is that there are many transmitter chemicals and countless substances that can affect the transmitters and the transmission process. Some of these excitatory or inhibitory substances in the brain are there naturally, and can depend on what you eat and your activities. There are also a multitude of drugs that can affect transmission in a multitude of ways.

All animal brains have specific structures and a very sophisticated organization.
Synaptic receptor sites (the receiving points) can have a variety of properties
depending on DNA coding and also actual usage. The extent of excitation by
sending points (pre-synaptic terminals) can be relatively fixed or variable.
In some situations, receiving points (postsynaptic sites) can produce a stream
of action potentials, or just one or two. If a synapse is used repeatedly,
transmission could be enhanced or inhibited, depending on a number of
temporal and chemical factors. Depending on usage, a receptor site could
store information that alters its performance — a “memory” function.

From the discussion above, you can see that there are numerous devices in
the brain that function as “logic.” The brain has common “and-gates”,
“or-gates”, “nor-gates” and many other types of gating to use in programming all of the fantastic abilities we enjoy. Much of the logic used by our brains is similar to that used in our computers. But brain logic has a far greater variation and is
really a combination of digital and analog systems. Information in a computer
is generally a universal pulse of a fixed voltage. In brains, information takes many forms including pulses, graded potentials, ion movements, and the presence or absence of a great number of chemicals. In computers, memory is achieved by manipulating magnetic and electrical properties of tiny bits of matter. In brains, some methods of storage are known and others are the subject of reasearch. It is likely that much of memory has to do with long-term facilitation (or inhibition) in synaptic transfer. There is much research on molecular structures that are altered to provide long-term information storage.

Imagine trying to construct something like a biological synapse with all
the properties described above. Your constructed synapse could have a hundred excitatory and inhibitory inputs, with several different transmitter chemicals. The receptor site should be able to produce a variety of action potential rates and be capable of changes related to memory. Even the construction of one
complete synapse would be very difficult. Imagine trying to create a human
brain with 150 trillion synapses with a variety of properties, AND with an
extremely complicated and as yet unknown organization.

Scientific brain research is valuable and should be continued. But productive
lines of inquiry should be promoted while most unrealistic speculation should be
ignored or presented as science fiction.

How did this extremely complicated biological computer system called a brain
develop? In a future blog I will deal with this question.

114. Brain, AI, and Behavior (3rd Revision)

13 Mar

This blog was stimulated by a Ray Kurzweil newsletter topic:
               Will artificial intelligence [AI] become conscious?
It reminded me that I have been wanting to explain this and related topics more thoroughly. Before continuing, I must describe my qualifications related to the conclusions that I will draw. I have had considerable formal training and professional experience in the following areas:
1. Behavioral Science
2. Neuro-science
3. Computers and control systems
4. Advanced computer programming

All of these topics are related and the relationships are illuminating. I have divided my ideas into several topics:

1. “Consciousness” is a layman’s term but is also used by scientists outside the field of behavioral science. It is most often used in a vague way without clear definition. And when defined, the definition is often made with vague statements. Many years ago, P.W. Bridgman (The Logic of Modern Physics, 1959) advocated “operational definitions.” One should use terms that can be defined in terms of specific procedures. For example, “hunger” could be defined as 24 hours of food deprivation. Another, “meter” is the length of the path traveled by light in vacuum during a very small, specified time interval: 1 over 299,792,458 sec.

Instead of the vague “consciousness” we should use terms like:
“Aware:” meaning there are measurable responses to specific type of stimuli.
Asleep:” defined by measurable patterns of EEG, and breathing patterns.
“Coma:” lack of responsiveness, but not asleep or under drug influence.
There are many similar terms that can have precise definitions. One can find numerous discussions of “consciousness” that go nowhere because the terminology used is not precise or “operational.”

So, here is my answer to the above question: Will AI become conscious?
My answer is that there will be amazing developments and uses for AI, but it will never exactly duplicate the capabilities of the human brain. Our brains developed over millions of years of evolution and have abilities that are not likely to be completely imitated. Throughout his lifetime and responding to all his experiences, a person’s brain develops by adding new structures, new neurons, and billions of new interconnections. Could this changing, adaptive system, with many trillions of connections and chemical operations, ever be duplicated by humans. (See below for details.)

2. How does the Brain work? Using all the knowledge areas mentioned above (behavior, neurophysiology, computers, etc) I will make the following description. First, the processing ability of the person primarily depends on the brain, but also includes other parts of the nervous system, and other systems, such as hormonal, sensory, and muscular.
The overall system is much like an ordinary computer, with keyboard and scanner inputs, a central processor, memory, and outputs such as a screen, printer, and speakers. In humans, a wide variety of sensory cells (receptors), such as cells in the retina, provide inputs, the nervous system (mostly brain) provides processing and memory, and outputs are complex behaviors, reflexes, hormone production, vocalizations, etc. An interesting fact is that even spurious factors like viruses work in the body and computers, in very much the same way. In both cases, they use the normal processing features to reproduce themselves and to cause damage.

Manufactured processing systems are pretty familiar. Most interactions are based on wires that carry electrical charges (+ and -). In humans, the wires are nerves that transmit over distances using the motions of ions in a wave process, much like a fuse. Ions are tiny charged (+ or -) particles composed of elements such as sodium, chlorine, calcium, potassium, etc. The ions move sideways to the direction of information flow, much like a tsunami moves in a wave without transferring the water itself. The moving wave that transmits info is called an action potential.

Our nervous system is composed of billions of nerves with around 150 trillion interconnections called synapses, and other connection variations. Further, each synapse (which functions like a transistor)  has a complicated and variable structure.  The nerve cells, their branching structures, and connections, provide all of our simple and complex behaviors. Frequently used connections associated with “learning” often expand and acquire new protein components. Functioning of these cells can also be modulated by various hormones, chemicals and drugs. So, our brains are a gigantic system with a number of control points so large as to be incomprehensible, that evolved in several billion years (also incomprehensible) to a structure that can create abstractions like, Einstein’s Relativity, and can ask where did I come from? It is also important to note that although the brain is complex almost beyond comprehension, it is still composed of chemicals and processes governed by the man-made laws of physics and chemistry. It is very unlikely that these totally “deterministic” components can produce any “free will.” In support of this conclusion, we know that computers (unquestionably deterministic) can produce amazing “behaviors” and can be programmed to imitate something like the assumed human “free will.”

We understand and know how the brain and spine produce simple reflexes using the input, output and processing systems described above. Not yet described here are more complex functions like memory retrieval; logic and reasoning; “creative” actions; and “emotions” like love and anger. It is clear that our brains can do a wide variety of things and has specially evolved to implement those most related to survival and the achievement of reproduction.
We know, for example, that special parts of the brain are devoted to facial recognition, to strong emotions, sex, visual memories, and the fight/flight response. We know that the brain can group together a series of actions or things and can rapidly produce a whole learned series without separately retrieving the components. There are experiments in “learning to learn” where if one learning process is similar to another, there is a facilitation. Really good brains can produce valuable associations and retrieve deeply “buried” little used, but relevant info. Brains have a remarkable ability to search, summarize, and draw conclusions. We do have some idea how these remarkable processes can take place, but much of this is purely speculative. Yet, the fact that computers can be programmed to do much of this abstract work, supports the idea the even the most amazing actions are “deterministic” and ultimately predictable. Also supporting determinism is that the huge number of anatomical and functional studies of the brain have never disclosed any super-natural “free-will” elements. The argument that free-will could “emerge” from deterministic elements, seems unlikely to me, but in the end, determinism forces us towards certain conclusions. Personally, when I really examine my life, I see that all my current behaviors are the result of a life-time of experiences.  I must ask free-will advocates: if your current behavior does not come from your DNA and past experiences (learned, imitated, stored, etc), where does it come from?

3. Thinking
There is one more topic that should be mentioned: “thought.” What is thought? Is it a behavior? Does it precede all overt behaviors? Is it “neuronal” like other actions? What is its function? Etc. Based upon some behavioral science studies and my own intuition, I propose the following.

First of all, most behavior just occurs without any thinking or planning. Second, thoughts can be words, pictures, or even “feelings.” Thoughts are studied scientifically by using a subject’s verbal responses, which ARE observable.
Thought is a covert brain output that does not reach the status of observable. An interesting facet of this idea is that some people “think out-loud” and what should be covert isn’t. I have known several people who do this. The most likely and useful aspect of thinking, is to produce a sub-threshold behavior to test its effect before causing the thinker any problems. For example, you ask your boss for a raise in your head, with different wordings, to find the best version. Or, you imagine yourself climbing a mountain and you note the fear that it generates. Thinking allows you to try things out before you actually do them, and serves as a safeguard.

Under the heading of thinking, one could imagine advanced retrieval processes that would be important for developing a theory or concept. A thought could be stimulated by an event in the environment. You see a stranger that looks like a past friend and a thought about the friend emerges. Clearly, there are environmental events that elicit related thoughts, but maybe there is also a thought generator, based upon the relative importance of stored info. Do we have some sort of scanner that finds important or otherwise significant items to think about?

Final thought: Even though our brains are extremely complicated and likely can never be duplicated, downloaded, or fully understood, brain research can still be productive. Studies of brain inputs and outputs, small systems of nerves, and comparisons with computers and other control systems,  have yielded valuable insights as to how higher functioning is accomplished.