The Retrieval

 3. Retrieval

There are common misconceptions when it comes to how the brain’s thought process works. Many of us believe that everything, such as creativity, imagination, and portrayals, occurs entirely inside the brain. This is not entirely accurate. Let me elaborate on that. Our brain processes information in two ways:

The Scene – Activating the same neurons to produce the same activity. This happens outside the intellectual mind.

Behind The Scenes – Cognitive and non-cognitive processes, such as thinking and reasoning, occur inside the intellectual mind.

These two aspects need to work in coexistence. As you read through this chapter about these two types, you will realize that they should not be separated but instead combined into one single entity – The Brain/Mind.

One more thing –

SE (Same-Effect): In Same-Effect, the output impulse will activate the same frontline input neuron that was once activated.

DE (Different-Effect): In Different-Effect, the output impulse will activate different frontline input neurons than the ones that were previously activated.

Both SE and DE represent how stored information can become known to you, which is why I named it as ‘scene.’ To be more precise, how do you think you know that you are thinking? The only way to do that is by stimulating the exact same frontline input neurons that tend to be activated when there is a presence of certain stimuli from the actual environment. Do not worry; I will explain it in detail below. Additionally, SE takes place during the normal retrieval process when the ring just needs to be formed, while DE occurs when the retrieval process involves the blending of rings (where the ring needs to be formed and mixed with other rings, as explained below).” Behind the scene” is where cognitive and non-cognitive activities take place. This is the place where the constant blending of rings occurs. In general, this is where our guesswork, computation, figuring out things, and many other processes that require the activation of multiple rings take place.

Blending of rings –

Beyond storing and retrieving information, the brain primarily manipulates the stored information to generate new knowledge. Theoretically, our brain blends one idea(ring) with another(ring), creating a new concept or information.

Randomness –

Randomness is akin to leftover inputs performing their function. If these remaining inputs are substantial enough to create a dynamic system, that system will initiate a self-sustaining chain reaction. Additionally, external environmental stimuli play a role in the newly established dynamic system. In essence, your thoughts initially begin randomly and adapt to your environment's stimuli.

A fully matured brain appears to generate randomness. It might seem as though we are in control of our thoughts, deliberately choosing one thing over another throughout the day. However, this continuous decision-making can create the illusion that we are the ones guiding our brain’s thought processes. Neither our brain nor we are in control of our thoughts; it is randomness that governs everyone is thought processes.

Common information –

As the name implies, 'common information' refers to the energies of information that are shared/common among two or more different rings of varied information. Common information is useful for computing and blending two or more identical or slightly non-identical pieces of information into something new. It is an input-dependent variable.

In the illustration, seeing the home (visual energy information) induces the primary ring, and due to brain plasticity, the auditory energy information is also activated. Therefore, whenever you receive auditory energy, it will also activate the visual energy information of that auditory input. This is due to plasticity, which involves the accumulation of neurons in a certain way, rather than synapses getting stronger, as mentioned earlier in Chapter 2(The storage). 

The play –

The common information, randomness, and the ring all work in conjunction to blend the rings and produce new information.

The picture below clearly conveys the idea. Also, one should not forget that the final output, which is the newly blended rings’ energy information, travels back to the frontline input neurons to provide us with the visualization, in this case, a fire camp with a black background and a white frame.

During the blending of the rings, almost all the senses’ reduced energy information will turn into visual energy information. There may be other sensory information contributing to our consciousness, but it is not particularly noteworthy. This is because we receive an enormous amount of energy information from the visual system alone, and the visual system is active most of the time (e.g., during imagination and dreaming). In contrast, the olfactory and auditory systems contribute to consciousness but to a lesser extent when compared to the visual system. Visual system act as a superconductor.

Additionally, we cannot visualize the computational work because it is often a quick process (e.g., 2 + 2 = 4). People often refer to computational work as “connecting the dots.” However, when the computational work is challenging, we can visualize the process more clearly (e.g., 5 × 6 = (5 × 5) + 5 = 30). We can visualize the intermediate steps here because it is not too fast to escape our visual awareness. By “escape,” I mean that the energy information from the computational work does not reach the frontline input neurons. If the process is quick, the intermediate steps of computational work never reach the frontline input neurons, and we only see the final answer.

In the case of difficult computational work, the intermediate energy information tends to reach the frontline input neurons, so we understand both the process and the answer or output. This is since impulses (or signals) in neurons never cease moving along the ring (plasticity). When the computational work is challenging and time-consuming, the energized intermediate information consistently travels at a constant speed and eventually reaches the frontline input neuron with slightly modified information. The energized information does not wait for the entire work to be completed. All of this relates to the difficulty level of the work.

Linearity of thoughts –

We never say 1->4->2->5->8->...n. Instead, we always tend to say in order 1->2->3->4->5...n. How is that possible, given that we know all the numbers, but our brains remember everything in order? Where and how is this ordering of things performed in our brains? Thoughts are stored in order too; new incoming thoughts are stacked upon existing thoughts, creating an organized structure. Let us explore how the brain can perform this ordering or sorting process. You receive a lot of inputs from the environment, even if you are not consciously aware of them. These inputs play a crucial role in storing and retrieving information. They also aid in the ordering of thoughts when storing and retrieving.

As you can see, I have depicted blue arrows that illustrate the numbers in order, such as 1->2->3. The process is more complex and challenging to explain using plain English and diagrams. So, I will stick with simpler models. Let us assume that the inputs from the actual environment were sufficient to activate the dot (1). It is important to note that larger dots (1, 2, 3) can, when activated, return to the frontline input neurons, allowing a person to visualize the numbers in the appropriate order. Please note that this is a retrieval process; I will discuss the storing process later. Now, after activating dot (1), it sends impulses to all the other connections linked to it, which are 1’, 1’’, 2, and 3. As shown in the diagram, the activation of 1’ and 1’’ leads to impulses being sent to dot (2) alone. This activation causes the larger dot (2) to activate, and upon this activation, 2’, 2’’, 1, and 3 dots are also activated since they are connected to dot (2). The activation of 2’ and 2’’ sends impulses to 3, leading to the activation of the bigger dot (3). The linearity of this process can extend, depending on the information. Just for the sake of completeness, I have included an arrow pointing back to dot (1) to close the cycle. The cycle may not always complete. The letter ‘C’ is used to represent the background processes, which are activated by inputs from the actual environment, but you may not be aware of them. The constant ‘C’ is introduced to reduce noise in the diagram. In simpler terms, these triangles (comprising small and larger ones) are what perform the ordering of thoughts in our brains. After the activation of the larger dots, as new energized information, and this energy flow back to the frontline input neurons, we can visualize the numbers or thoughts in order. Recall the unit cell we discussed in the storage chapter. To fit this theory, imagine these triangles as the circles we saw in the unit cell diagram. Now, envision the pyramid of unit cells from the consciousness chapter. Combine all these elements (triangles as circles and the pyramid of cells), and you have a simplified working mechanism of the brain.

The storage and retrieval processes are somewhat similar. Remember that storage involves nothing more than information stacked upon other information through plasticity, often aided by repetition. Repetition leads to the creation of a greater number of similar inputs, such as C-constant, 1'-1'', 2'-2'', 3'-3''. These secondary dots are the similar inputs that activate the primary dots with assistance from sub-secondary inputs like constants ('C'). Sub-secondary inputs also fall under the category of similar inputs. Increasing the number of similar inputs enhances the probability of selectively activating the primary dots, thus promoting linearity. When looking at the secondary inputs in the diagram, you can begin to grasp that sub-secondary inputs are necessary to activate the secondary inputs. These sub-secondary inputs can also be activated by environmental inputs and indirectly by the primary dot's activation (indicated by an asterisk), setting off a chain reaction.

In the brain, these sub-secondary inputs are present in large numbers and aid in retrieving thoughts in the correct order. Think of these processes as a dynamic system. In other words, when the right amount of input from the environment is provided, a specific dynamic system forms, which then retrieves information in the proper order. If you are finding it challenging to grasp, I would recommend learning about dynamic systems.

Now, if you are wondering how all this works together to activate major primary dots, let me explain. When the correct amount of sub-secondary inputs is activated, the primary dots will eventually be activated. Initially, inputs from the actual environment activate the sub-secondary inputs, which are essential for initiating the formation of dynamic systems. Later, the system can run autonomously. After the dynamic system is formed, it can automatically activate the required sub-secondary inputs to further create and maintain the dynamic system. Meanwhile, environmental input continues to enter the brain, sustaining the ongoing process of the retrieval dynamic system.

In the previous chapters, I depicted inputs as high-intensity, energized information, but when discussing the linearity of thoughts, I referred to inputs as similar-like inputs. In both representations, the underlying concept remains the same. The only distinction is that when we think of inputs in the context of impulses, we can consider them as energized information, whereas when we think of inputs in the context of neurons, we can view them as similar-like inputs (such as 1’, 1”, 2’,.. C). It is just a different way of perceiving how inputs are processed in the brain. I differentiated the representation for the sake of making the concept easier to understand. Regardless of the representation, these inputs ultimately create a kind of dynamic system, activating the primary nodes, and the resulting energized information returns to the frontline input neurons, enabling visualization.

Inputs uniqueness create regularized path of neurons. These paths help in problem solving via forming a linearity in thoughts.

 

And this linearity in forming an output was affected by what kind of neurons are nearby when activating a ring that could get into the frontline input neuron. This nearby type of neurons was influenced by specific regions in the brain that produce surplus of neuro chemicals when triggered, I will be calling them reference point. And their reference point act as attractors when the ring was forming like a dynamic system. As we grow, the ring systems are formed along the path of reference point. As these reference point gives more neuro chemicals when activated they have ability to attract more neurons towards them and make ring to be formed along the way of reference points presence.

Think of like river flowing in a direction frequently corrected by other river flow stream which was influenced by the rocks or sands present nearby the river flow.

The brain is not designed to permanently store knowledge?

The memories like concept's, facts are stored and retrieved successfully only if those memories are linked to many other knowledge. Interconnectedness of any knowledge inside the brain will prevent the forgetting that knowledge by representational shift property of neurons.

Since we all exposed to emotionally filled knowledge/information all the time (as emotions has more reference point inside the brain). It is easier for emotionally linked knowledge to get interconnected with other knowledge than the knowledge that is partially linked with emotions. 

The reference point gives surplus of neuro chemicals which eventually change the ring to their desired shape. That is the ring will travel in the reference point way more frequently, not always with all reference point only the reference point that has been activated by the senses.

Successful storing needs -> frequent usage of that knowledge -> usage is derived from "need" or cause for that knowledge -> and there are multiple factors that may be reason for that cause or need of that knowledge, and these factors are not in human’s control.

They are always activating as rings are formed along their path and that is why information that we receive most of the time connects to emotions and emotionally related information was always available.

"In short, the storing of any knowledge is not in our control"

Let me say a little bit about dendritic computation. 

That is, neurons have dendrites that are said to be doing a complex computation, they are of course involved in computation by storing the pathway or reducing information (why? Reduced information to further meets the demand of the other clusters in the connectome) but they are not doing some complex things. Because since dendrites can grow more by numbers as well as length they are presumed to be / manifested to be doing a complex job. So, i would like to say dendritic computation like selective direction, integral summation, spatial and temporal summation are there that is the result of having more dendrites but that is not doing the mind work.

And one more thing, neurons dual activity of acting like computing and leading the impulses direction to travel to the frontline input neuron.

Neurons are involved in both computation and direction. Computation – storing the connection and direction – reconnecting those stored connection to give right output. Dendritic computation was the byproduct of plasticity in cluster of neurons.

Dendritic computation is result of plasticity driven strong connective neurons impulse.

Dendrites speeds up the process of propagation of impulse along the way. Plasticity driven strong connection processing can influence the type of computation that the dendrites are going to perform.

The wiggle connection

The brain follows a simple mechanism that efficiently solves problems. Let me state the mechanism: impulses from the external environment enter the brain, and as these impulses cycle inside the brain, inevitable connections form between input impulse and output impulse neuron clusters. This allows the answer to appear quickly to the observer, making shortcuts to the answer by bypassing full computation and directly connecting to the output after undergoing full computation. This process is followed for all inputs consistently.

Karl popper on probability of a theory to be true:

In the view of many social scientists, the more probable a theory is, the better it is, and if we have to choose between two theories which differ only in that one is probable and the other is improbable, then we should choose the former. Popper rejects this. Science values theories with a high informative content, because they possess a high predictive power and are consequently highly testable. For that reason, the more improbable a theory is the better it is scientifically, because the probability and informative content of a theory vary inversely—the higher the informative content of a theory the lower will be its probability. Thus, the statements which are of special interest to science are those with a high informative content and (consequentially) a low probability, which nevertheless come close to the truth. Informative content, which is in inverse proportion to probability, is in direct proportion to testability. As a result, the severity of the test to which a theory can be subjected, and by means of which it is falsified or corroborated, is of fundamental importance.

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If you are reading this, it is my hope that you find my theory interesting and plausible. I believe that eventually someone will contact me to discuss this theory. I also have an experimental idea to test my theory, but I need assistance because I lack a solid background in neuroscience. I acknowledge that my theory may not be entirely correct, but I hope it will inspire others to ponder the problem and spark curiosity in those genuinely interested in unravelling the mysteries of the brain. That is all; I have provided my contact details below. Please do not hesitate to reach out if you have any questions, want to make changes, are willing to help, or wish to provide constructive criticism.

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