Complex mesh with white void lying at its center

Essay in Progress, Part 1 – How Knowledge Is Represented in the Brain

Last summer I started writing an essay about consciousness as a physical phenomenon. I had a premise that consciousness was an emergent phenomenon and that emergent phenomena, such as bird flocks or schools of fish, were essentially conscious. To substantiate my argument I delved into scientific literature. Soon I discovered a remarkable paper, called Integrated Information Theory, which argued against my initial premise and gave me many new insights about the nature of consciousness.

I continued my intellectual journey and kept adjusting my line of thought with every book and paper that I read. Along the way I learned that it is quite difficult to build up my argument, as the subject at hand was so far-reaching, and when I stopped writing, due to a lack of time, I was left with 50 pages of non-chronological thoughts and insights, full of jumps and regressions. I had made large strides towards a better understanding of how consciousness connected to neurology, evolutionary biology, psychology and phenomenology, but the continuity of my story payed the price.

Now I want to pick-up the threat where I had left it and use blogposts as a structure for my essay. Of course all feedback is welcome!

“This essay attempts to combine insights from various scientific fields and merge them into an overall understanding of the most taken for granted mental processes such as: thinking, remembering, perceiving, imagining and dreaming”

To kick it off I will formulate an argumentation based on simple neurological facts, which will lay the groundwork for the rest of the essay. These neurological facts will sometimes seem too obvious to mention, but that’s the whole point; they should form a fundament that can hardly be disputed. Next to that, I look at consciousness and the operations of our brain as physical phenomena and not some kind of spiritual qualities. It is, therefore, better to first dissect the brain into its building blocks and go bottom-up from there. It needs to be noted that this essay is not a scientific work in itself as I don’t have the right qualifications for that. This essay attempts to combine insights from various scientific fields and merge them into an overall understanding of the most taken for granted mental processes such as: thinking, remembering, perceiving, imagining and dreaming.

What is knowledge?

First of all the brain is the most complex organ of the human body. It is probably the best example of how, over time, dumb mutations can lead to extremely sophisticated constructions of living matter. It is an obvious but very important fact to keep in mind that the body and the brain are the products of natural selection, which implies that every significant feature is the way it is because it has an advantage over other possible features.

“How is it possible that infants, who have the same amount of neurons as an adult and 50% more synapses, cannot even play a simple melody on the piano?”

The brain consists primarily of three types of cells: neurons, synapses and glial cells. The latter provides more of a supportive role for the former two and will therefore be left out from the rest of the argumentation. The exact structure of a neuron or a synapse will also not be explained. What, then, is a neuron or a synapse? Neurons are electrically excitable cells that transmit electro-chemical pulses to other neurons and glands in the body. Synapses are the connections between neurons. They allow an action potential to travel from one neuron to the other. There are about 86 billion neurons in the average human brain. Each of these neurons connects to roughly 7.000 other neurons, which amounts to about 500 trillion synaptic connections in a matured brain. At birth all the neurons a person will ever have are already present in the brain, as opposed to synapses of which there are actually 50% more at birth than in adulthood, which immediately brings forth an interesting question: how is it possible that infants, who have the same amount of neurons as an adult and 50% more synapses, cannot even play a simple melody on the piano? Seriously, though, how is it possible that an infant, with ‘more complex’ neural networks than an adult, seems to lack all the knowledge that the ‘lesser’ brain of an adult does have? The answer might be an important one, namely that knowledge is not stored in neurons or their connections, but that knowledge, or information about oneself and the world, resides in the relative differentiation of elementary and higher-order neural networks.

“The brain is not a computer – far from it”

This is quite a mouthful of course, so  let’s break it down into smaller bits. Previously we said that neurons are “electrically excitable cells”. This means that they have the potential to ‘fire’ an electrical pulse down the line; they are not turned on as a switch, but rather fire a signal lasting for about a millisecond. Neurons are therefore radically different in function than the semiconductors used for computing, which can store information declaratively, like a switch that can be called upon. Information is not stored in neurons; neurons are not bits of information that become megabytes in networks of neurons containing memories and thoughts. The brain is not a computer – far from it.

“It are the signals traveling through the connections in one’s brain that are the units of knowledge”

If a newborn has all the neurons and synapses of an adult and they are not empty slots ready to be filled with memories, how does he accumulate knowledge then? By differentiating the connections between neural networks. When an infant is born he has all the right cellular machinery at his disposal, but they are yet undefined. His brain is a relatively uniform distribution of neurons and synapses. Some necessary reflexes are already built-in; he will hold his breath under water, he will cry when he is hungry and he will quickly recognise the voice of his mother. But real knowledge comes with experience, because experience rewires the brain, some connection become stronger while others weaken. Now it seems the emphasis lies on the connections between neurons, but it are the signals traveling through the connections that are the units of knowledge. The more qualitatively different neural pathways a signal can potentially travel through the more knowledge is ‘stored’ in that brain.

To visualise the difference between the neural networks of an infant and those of an adult they can be compared to a roadmap. The neural roadmap of an infant is like a grid, such as Manhattan in New york or Eixample in Barcelona, the roads are of equal length and size and cross each other in a regular fashion, but the neural roadmap of an adult is like the hierarchy of roads in the countryside, where some roads are highways, shortcuts between nodes of activity, and others small dirt roads barely visible on the map, yet every highway was once a dirt road. This type of knowledge, that is inherent in the wiring of neural networks or other types of networks, is called procedural knowledge. How a computer knows how to add and subtract, which is the basis for all its operations, is also a type of procedural knowledge that is inherent to the computer’s architecture.

To be continued…




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