Why you shouldn’t compare your brain to a computer

The debate about the relationship between the mind, consciousness, intelligence, and technology has been one of the most persistent topics of contemporary philosophy. Despite the fact that modern science is still not able to fully resolve these questions, many philosophers believe that some of the characteristics of our brain can be explained by computational models. This opinion has been widely shared among neuroscientists who have long argued that the brain operates just like a computer, processing information much the same way. But for almost a century, psychologists, linguists, neuroscientists and other experts in human behavior have disagreed, insisting that the human brain functions differently, with different parts processing different tasks using specialized circuits. So why should you compare your brain to that computer? Let us look at the reasons why these arguments are so flawed. First, we will consider how our brains process information and make decisions, as well as their limitations. Second, we will take into account the peculiarities of different regions in the brains, which differ from one person to another, for example by sex or race. Third, we will look at why it is difficult to understand the functioning of different parts of the brain. And finally, we will consider the relevance of such comparisons from a biological point of view.

First, let us consider how our brains process information and make decisions. Our brains are designed to interpret visual stimuli and make decisions about what these signals mean. They use specific neurons called “simple cells” to receive information from different areas in the visual field (the retina) and decide whether it is worthwhile to pursue further processing. These simple cells are thought to be located in three layers: rods, cones and macula. At the top of each layer are photoreceptors (more precisely retinal ganglion cells). Then two lower layers are responsible for processing visual information and making decisions about where we start processing the incoming signal (the fovea). Finally, the brain processes the resulting image or sound with an additional cell in the middle, which is responsible for encoding visual information into electrical signals and controlling motor actions (for example, vision and hearing). From a statistical point of view, however, there is no evidence that our brain uses only one type of cell but in fact we have several cell types with different locations in the visual system. We can classify them according to their role in processing visual information and make decisions. Thus, we have one large pool of rod cells in the innermost layers of the retina called thalamocortical ganglion cells and a smaller pool of cone cells located in the outermost layers of the retina called the ciliary epithelium. Each of these cells receives light and transmits its information through dendrites at the back of the cell membrane. Next up we have the cone cells, which are responsible for processing images and other sensory inputs received from the retina. They are located on the surface of the retina, in the center of the central retinal ganglion with the iris. On average, they form four layers, in which we have five types: mesopsic, stellate, trichomes and apical . Lastly, there is a very important fourth category of cells known as rods of similar size but with different dendrites. Rods contain two types of dendrite-like structures, called presynaptic terminals. Their function is to allow the nerve impulse to pass through the axon to the next neuron. However, it also allows impulses to cross the synapse to reach higher levels of processing and become processed by the brain. The main difference between these two categories is that for example rod cells contain many dendrites compared to cone cells which have fewer dendrites and therefore do not have a huge number of dendrites. Therefore, we have five types of rods in the visual system.

Now let us take a closer look at the differences between these types of cells. There are two primary differences between rod cells and cone cells. Firstly, while rod cells have an extended dendrite and thus larger numbers of dendrites, cone cells have shorter dendrites. Secondly, while rod cells are better suited to receiving visual information from the retina, cone cells receive it from other places that are less visible. An area known as the lateral geniculate nucleus (LGN) is located in the posterior part of the visual field, in the left visual tract. It contains mainly rods but also small numbers of cones. Here the main similarity lies in the fact that both types contain large amounts of LGN cells. When visual information travels down the optic tract, it first passes from the thalamus to the visual cortex. Here, however, it enters the visual system through the medial layers, then through the ventral visual system where it reaches the posterior layers of the temporal lobe. Cone cells receive information from the anterior visual system, where they are located in the lateral geniculate nucleus (LGMN). In contrast, rod cells receive information from the frontal visual system, where they are located in the central visual tracts, in the right visual tract, the lateral geniculate nucleus (RGMN) and the lateral ventricles. Moreover, while the lateral ventricles are responsible for processing visual sensory input, they receive it from two visual centers in the brain, namely the inferior colliculi and the superior colliculi, respectively. Overall, cone cells have more neurons compared to rods, have thinner dendrites and do not have so many dendrites like rod cells, which means that they cannot receive visual signals like rod cells can. Hence, a large percentage of visual processing occurs in the lateral geniculate nucleus (LGN). Rod cells, on the other hand, receive visual information from the visual system, which includes the eyesight centers in the LGMN, which receive visual information in the lateral ventricles. As an illustration, see figure 3.

As we can see, there are striking differences in the structure and organization of different parts of the brain. Since the brain is such a complex organ, the question arises whether we can draw conclusions about it based purely on individual differences. If we think that human brains operate just like computers, it would make sense if we could build simulations of these brains that could be used to predict the results of various tests. With the advent of digital technologies, however, we have come to realize that we can’t simulate reality – in any meaningful way. What we can do, therefore, is to collect information about how the human brain functions and compare it to other simulations of the brain in order to get a good understanding of how well we understand how our brains work. This is why we can’t use digital tools to simulate our brains because we don’t know how exactly their structure and functional organization work. This makes it hard to compare the neural network models of the mind to real computers because we lack knowledge about their internal workings.

In conclusion, the debate over the relationship between the mind, consciousness, intelligence, and technology is far from settled. While some argue that our brains operate just like computers, others insist that these differences are due to the unique properties of our respective types of cells and structures.