Neurons, aka nerve cells, are the core component of the brain. Our understanding of how neurons process information is very poor. This is my hypothesis on how neurons process information, or in other words, how we think. This is the prologue to “The Fundamental Difference between Men and Women”.
One of the things we know about neurons is the structure:
Notice how the dendrites and axon terminals have hierarchical branching, like tree branches. Another thing we know about neurons is that nerve impulses (i.e. information) only travel in one direction:
Dendrites input information from other neurons to the nucleus. Axon terminals output information from the nucleus to other neurons. When you put together the hierarchical structures of the neuron and its direction of impulse, you arrive at my hypothesis on how information is processed. I hypothesize that convergence of information occurs at the dendrites, and divergence of information occurs at the axon terminals. Here is a simplified neuron depicting this:
If you start at the top and follow the impulse down, you see that multiple branches become just two, and then two become one at the nucleus. And if you keep going down, you see that one splits into two branches, and then two branches split into many more. The world just sees branches, but if you imagine that information is flowing through these branches, and you get two opposite thought processes: convergence and divergence. For many years, I have hypothesized that convergence and divergence are the basis of human/intelligent thought. For many years, however, I was wrong about the scale; I used to think that the brain was one large hierarchy of interconnected information. In reality, not all information is connected, and two hierarchies exist within a single neuron. Thus, every neuron of the cerebrum is capable of convergence and divergence.
In the world of neuroscience, the words “convergence” and “divergence” are foreign. I found it necessary to make these words up to explain my hypothesis. I define convergence as the process of information coming together. More specifically, it is inductive reasoning, connecting thoughts, or finding a similarity. This means the product of convergence is information that has come together: a general thought, a universal thought, or a similarity. I also hypothesize that convergence occurs in an instant. It is information coming together simultaneously—parallel processing.
Looking back at the top half of a typical human neuron, convergence is when pieces of information are simultaneously taken from many different neurons (as denoted by different colors) via the dendrites, and combined into one, general piece of information at the nucleus.
The opposite of convergence is divergence, which I define as the process of information splitting apart. More specifically, it is deductive reasoning, separating thoughts, or finding differences. This means the product of divergence is information that has split apart: numerous specific thoughts, numerous situational thoughts, or differences. Divergence occurs over time. It is information separating sequentially—serial processing.
Looking back at the bottom half of a typical human neuron, divergence is when information of the nucleus (not pictured) sequentially splits apart via the axon terminals. One specific piece of information goes to one neuron (e.g. red), and then another specific piece of information going to another neuron (e.g. yellow), and so on.
A tree structure is a popular way to present information that can be hierarchically organized. It may help to explain convergence and divergence. Convergence is going up the hierarchy; convergence is going from multiple child nodes to one parent node. For example, from golden retriever and German Shepherd to dogs. Divergence is going down the hierarchy; divergence is going from one parent node to multiple child nodes. For example, from dogs to golden retriever and German Shepherd. I can give another example in math. Convergence is looking at the numbers 2, 4, 8, 16, 32 and finding the commonality, which can be summarily written as f(x) = 2x. Divergence is applying numbers to this formula to get 2, 4, 8, 16, 32, etc.
So what’s the big deal? While the world obsesses over how information is stored to memory, I believe convergence and divergence is the key to intelligence and learning. For example, a child eats an apple. He stores this information in a neuron: apple is green, sweet, and sour. Later he eats a red apple, and it tastes different than the green apple. The original “apple” neuron engages in divergence, and separates the information into two more neurons attached to the axon terminals: green apple is sweet and sour; red apple is just sweet. Later he eats an orange that is sweet, sour, and bitter. This information is stored in another neuron. He may reflect on all these thoughts, and find that there is a commonality among them: they’re sweet. In the brain, all the neurons would connect to the dendrites of a single, new neuron with the information: sweet fruits. As you can see, he has gone up and down the metaphorical hierarchy by finding similarities and differences. He has created a neural network to better his understanding of the world. Eventually, as he gets older, the neural network becomes much more complex. It has many neurons connected to the dendrites of just one neuron—strong convergence. It has many neurons connected to the axon terminals of just one neuron—strong divergence.
On the left is a depiction of strong convergence and on the right is a depiction of strong divergence. The color spectrum symbolizes an abundance of neurons/thoughts/pieces of information.
Strong convergence and divergence is what distinguishes human intelligence from other animals. Intelligence lies in the structure of the neurons in the cerebrum, rather than some special region of the brain. My next hypothesis is that as an animal species increases in complexity, so will the number of dendrites and axon terminals on a single neuron. Thus, a neuron in the brain of a simple species, such a snail or spider, would look like this:
It’s a simple neuron with one dendrite and one axon terminal. Information goes in and out; there is no information processing, just reflexes. All thoughts are already “hard-wired”. For example, “Insect entered my web. Go bite it.” A mouse is a more complex animal, thus I expect the neurons in its brain to have a few dendrites and a few axon terminals. At the end of the complexity spectrum is humans, which would have the most dendrites per neuron and the most axon terminals per neuron. This is what makes humans intelligent.
So far I’ve given examples of basic convergence and divergence. Humans operate at an advanced level of convergence and divergence, so here are some human-level examples. Judging facial beauty is strong convergence. Yes, when a man checks out a woman’s face, he is engaged in complex thought. He is looking at each feature of the face and analyzing its shape, proportion, size, and contrast, by comparing it to the facial features of thousands of other faces in his memory. He is figuring out how far each facial feature deviates from the mean. He does this in an instant, and assigns a single, overall value to describe the entire face, usually on a scale of 1 to 10. This is strong convergence because it’s dealing with many variables simultaneously to produce a single thought. In general, computing or recalling averages is convergence because an average is a single value that results from combining many data points. Decision-making can also be strong convergence. For example, when a man buys a TV, he is looking for cost-effectiveness; he is looking for a certain degree of performance for a certain price. To do this, he judges the value of many advertised features of the TV and puts it all together in an overall performance score. This score is then put together with the price, for the overall cost-effectiveness. Finally, he decides to buy or not buy. Consideration of many variables simultaneously for a single thought is strong convergence. It is connecting many distinct neurons to the dendrites of a single neuron.
You may be begging to tell me that you don’t think like this. You don’t judge facial beauty this way and you don’t make decisions this way. This would mean that you are not using convergence but rather divergence. Many people are attracted to a face with an eyebrow piercing, earrings, a “loud” hairstyle, and a full beard. And when buying a TV, some people just want a TV made by a reputable brand. These people aren’t stupid. They just pay attention to different things in life; they have a different perspective. They prefer divergence over convergence; they use more axon terminals than dendrites.
It is probably ideal to use the same number of dendrites as axon terminals. This way, for every time a person puts information together, he or she takes information apart—a perfect balance between convergence and divergence. However, I know that this is not the case for any person in existence. For my last hypothesis, I hypothesize that the ratio of dendrites to axon terminals used is the basis of one’s personality.
Gold denotes use and grey denotes disuse/neglect. I could have also used the color spectrum (i.e. many neurons) to represent heavy use. On the left is a neuron with many dendrites in use, and just one axon terminal in use. Here, the resultant personality is what I call a convergence-favoring person. A divergence-favoring person has neurons like the one on the right: just one dendrite in use, and many axon terminals in use. These are completely opposite personalities. A convergence-favoring person pays attention to general and universal things, and similarities, while neglecting specific and situational things, and differences. A divergence-favoring person is the opposite.
I’ll give one example using the normal distribution, also known as the bell curve. It’s a graph that accurately shows how a measurable variable is distributed in a population. In other words, it shows you just how common or rare your IQ, shoe size, height, sprinting speed, etc. is compared to everyone else. People who favor convergence pay attention to the dark blue area under the curve, which would be the mean and the first two standard deviations. (These are just approximations.) They ignore the rest of the population beyond two standard deviations. They are only concerned with the majority, the mean, the average, or the common man. People who favor divergence pay attention to the light blue area under the curve, which would be the ~5% that are beyond two standard deviations. They ignore the ~95% majority. (These are just approximations.) They are only concerned with the minority, the unique, the rare, the anomaly, the outlier, the special, the superlative, or the individual.
I’m sure you’re familiar with the famous motto, “All for one and one for all.” A convergence-favoring person would abide by the “one for all” part and focus on the community. A divergence-favoring person would abide by the “all for one” part and focus on the individual. Say, hypothetically, one man in a community of 10,000 people is afflicted with cancer that costs $100,000 to remove. Should everyone chip in ten dollars to save his life? In other words, should every single person in the community work an extra hour to save this man? Most people would want more details, but in general, people who favor convergence would say no and people who favor divergence would say yes. As you can extrapolate, whether you favor convergence (i.e. to use dendrites) or divergence (i.e. to use axon terminals) is very much tied to your political view, how you feel tax dollars should be distributed, and how your own time and money should be prioritized—your personality.
© Buism 2013