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117. The Amazing Brain: How it was made.

6 Jul

Most people know, or are at least aware of the idea, that our amazing brains were developed through biological evolution. I am going to try to make a clear explanation of this process. One approach is to make comparisons with easy to understand non-biological processes.

A manufactured product can evolve under the following conditions:
1. Consider a product such as a cell-phone, that has a high volume of sales.
2. This product can and will be improved in a number different ways.
3. After each modification, there is an objective measure of the product’s success.
4. The product is permanently modified if there are indications of its success with the public.

So, the procedure is to make and sell a specific improvement, say, a larger screen. If the larger screen sells more phones, then it will be included in all future versions. If sales are worse, then the improved version will be abandoned. In this way, the cell-phone will “evolve” and customers will enjoy better and better phones.

The key factors in this and other evolution are variation (which is persistent) and feedback related to the new features. And, of course, the feedback must have an effect on the persistence of variations.

In biological evolution, mutation (relatively permanent changes) occurs in a species as new DNA is created for offspring. The feedback is success in survival. If a change, such as a longer neck for a giraffe, helps giraffes to survive, then giraffes may “evolve” longer necks. Note, longer necks allow giraffes to reach more food. Natural selection (survival of the fittest) is the biological process, similar to customer satisfaction for the cell phones.

It is really remarkable that “nature” has created automatically self-improving objects like animals and plants. The improvements can take place without any human intervention. Every animal and plant on earth has developed, in this way, for billions of years.

.                           Amazing time leads to Amazing complexity
Now think about this: the amazing complexity of the human brain is based on an amazing amount of time, billions of years. Brains (and all other organs) have developed to a fantastic degree, because of a fantastic amount of time for this “evolution” process to take place.

I should also mention that in our world, there are many types evolution. Similar to natural biological evolution, is animal breeding. Here, the selection is NOT natural, but by humane intervention. As civilization developed, there have been remarkable changes in species to make them more desirable for human use. The clear effects of breeding are very supportive of the concept of natural evolution.

If you want to develop your understanding of brain evolution, do an Internet search on the words “animal nervous systems” or “animal brains” and look at the images. This will help you to see the progression. After the transition from single-celled to multi-cellular animals, rudimentary nervous systems appeared. These provided simple two-cell reflexes based on an input (sensory neuron) and an output (motor neuron). Eventually, more neurons were added to the processing and finally complex brains appeared. Some of this nervous system development is well
understood, but there is still very much to learn.

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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.