The process of mind

[Brief summary of this post]

Let’s say the mind is a kind of computer. As a program, it moves data around and executes instructions. Herein I am going to consider the form of the data and the structure of the program. I have proposed that from the top down the mind is controlled by a process I call the SSSS, for single stream step selector. I have argued that this process uses a single CPU, i.e. one thread or train of thought, but an unlimited number of multitasked processes, though it is only actively pursuing a handful of these at a time. And I have argued that top-level decisions use reason, either inductive of deductive logic, on propositions, which are simplifications or generalizations about the world, guided by desires, which are instinctive preferences understood consciously as preferential propositions. Propositions are represented using concepts framed by models, both of which we keep in our memory.

To decompose this further working from the top down let’s consider how a program works. First, it collects data, aka inputs. Then it does some processing on the data. Third, it produces outputs. And last, it repeats. For a service-oriented program, i.e. one that provides a continuous stream of outputs for a shifting stream of inputs, this endless iteration of the central processing loop, which for minds is heavily driven by outputs feeding back to inputs, forms the outer structure of the program. I call the loop used by the SSSS the RRR loop, for recollection, reasoning, and reaction.

Before I discuss these in some detail, I want to say something about the data and instructions. If I say I’m losing my mind, I’m talking about my memory, not my faculties, which I can take for granted. All of the “interesting” parts are in the data, from our past experiences to our understanding of the present to our future plans. The instructions our brain and body follows are, by comparison, low-level and mostly hard-wired. The detailed plans that let us play the piano or speak a sentence are stored in memory. Built-in instructions support memory retrieval, logical operations, and transmission of instructions to our fingers or mouths, but any higher-level understanding of the mind relates to the contents of memory. Our memory is inconceivably vast. At any one time, we can consciously manage just a handful of data references and an impression of the data to which they refer. But that referenced data itself in turn ultimately refers to all the data in our minds, everything we have ever known, and to some degree everything everyone has ever known. Because “everything” means representations of everything, and since representations are generalizations that lose information, much has been lost. Most, no doubt. But it is still a massive amount of useful information, distilled from our personal experience, our interactions with others, culture, and a genetic heritage of instinctive impressions that develop into memory as we grow. Note that genetically-based “memory” is not yet memory at birth but a predisposition to develop procedural memory (e.g. breastfeeding, walking) or declarative memory (e.g. concepts, language).

One more thing before I go into the phases. We consciously control the SSSS process; making decisions is the part of our existence we identify with most strongly. But the SSSS process is supported by an incalculably large (from a conscious perspective) amount of subconscious thinking. Our subconscious does so much for us we are already very smart before we consciously “lift a finger”. This predigested layer is what makes explaining the way the mind works so impenetrable: how can you explain what just appears by magic? Yes, subjectively it is magic — conscious awareness and attention is a subprocess of the mind that is constrained to see just the outer layers of thought that support the SSSS, without all the distraction of the underlying computations that support it. But objectively we can deduce much about what the subconscious layers must be doing and how they must be doing it, and we now have machine learning algorithms that approximate some of what the subconscious does for the SSSS in a very rudimentary way. So from a computational standpoint, all three phases of the SSSS are almost entirely subconscious. All the conscious layer is doing is providing direction — recall this, reason that, react like so — and the subconscious makes it happen with a vast amount of hidden machinery.

Recollections can be either externally or internally stimulated, which I call recognition-based or association-based recall. Recognition means identifying things in the environment similar to what has been seen before, a process known in psychology as apperception. Sensory perception provides a flood of raw information that can only be put to use by the SSSS to aid in control if it can be distilled into a propositional form, which is done by generalizing the information into concepts. The mind first builds simplified generic object representations that require no understanding about what is being sensed. For example, vision processing converts the visual field into a set of colored 3-D objects adjusted for lighting conditions, without trying to recognize them. These objects must have a discrete internal representation headed by an object pointer and containing the attributes assigned to the object. For example, if we identify a red sphere, then a red sphere object pointer contains the attributes red, sphere, and other salient details we noticed. Such a pointer lets us distinguish a red sphere from a blue cube, i.e. that red goes with the sphere and blue goes with the cube, which is called the segregation problem in cognitive science, or sometimes the binding problem (technically subproblem BP1 of the binding problem). Being able to create distinct mental objects at will for anything we see that we wish to think about discretely is critical to making use of the information. Note that in this simplified example I have called out two idealized attributes, red and sphere, but this processing happens subconsciously, so it would be presumptuous (and wrong) to infer that it identifies the red sphere simply by using those two attributes. More on that below.

The next step of recognition is matching perceived objects to things we have seen before. This presupposes we have memories, so let’s just assume that for now. Memory acts like a dictionary of known objects. The way we associate perceived objects to memories, technically called pattern recognition, is solved by brute force: the object is simultaneously compared to every memory we have, trying to match the attributes of that object against the attributes of every object in memory. Technically, to do this comparison concurrently means doing many comparisons in parallel, which probably means many neural copies of the perceived object are broadcast across the brain looking for a match. Nearly all these subconscious attempts to match will fail, but if a match is found then consciously it will just seem to pop out. We know pattern recognition works this way in principle because it is the only way we could recognize things so quickly. Search engines and voice recognition algorithms use machine learning algorithms that function in a similar way, which is sometimes called associative memory. While we don’t know much yet about brain function, this explanation is consistent with brain studies and what we know about nerve activation.

After a match, our associative memory returns the meaning of the object, which is analogous to a dictionary definition, but while any given dictionary definition uses a fixed set of words, a memory returns a pointer connected to other memories. So the meaning consists of other objects and relationships from the given object to them. So when we recognize our wallet, the pointer for our wallet connects it to many other objects, e.g. to a generic wallet object, to all the items in it, and to its composition. Each of these relationships has a type, like “is a”, “is a part of”, “is a feature of”, “is the composition of”, “contains”, etc. This is the tip of the iceberg because we also have long experience with our wallet, more than we can remember, much of which is stored and can potentially be recalled with the right trigger.

A single recognition event, the moment an object is compared against everything we know to find a match, is itself a simple hit or miss: our subconscious either finds relevant match(es) or it doesn’t. However, what we sense at the conscious level is a complex assembly of many such matches. There are many reasons for this, and I will list a few, but they stem from the fact that consciousness needs more than an isolated recognition event can deliver:
1. The attributes one which we base recognition are themselves often products of recognition. Our experience with substances leads us to evaluate the composition of the object based on texture, color, and pattern. Our experience with letters leads us to evaluate them based on lines, curves, and enclosed areas. Our experience with shapes leads us to evaluate them based on flatness or curviness, protuberances, and proportions. This kind of low-level recognition is based on a very large internal database of attributes comprehensible only to our internal subconscious matching process (beyond just “red” or “sphere”) that is built from a lifetime of experience and not from rational idealizations we concoct consciously. So size, luminosity, depth, tone, context and more trigger many subconscious recognition events from our whole life experience. These subconscious attributes derive from what is called unsupervised learning in machine learning circles, meaning that they result from patterns in the data and not from a qualitative assessment of what “should” be an attribute.
2. Each subset of the object’s attributes represents a potentially matchable object. So red spheres can also match anything red or any sphere. Every added attribute doubles the number of combinations and adds a new subset with all the attributes, so five attributes have 31 combinations and six have 63. A small shiny red sphere with a small white circle having a black “3” in it has six (named) attributes, and we will immediately recognize it as a pool ball, specifically the 3-ball, which is always red. Our subconscious does the 63 combinations for us and finds a match on the combination of all six attributes. Without the white circle with the “3”, the sphere could be a red snooker ball, a Christmas ornament, or a bouncy ball, so these possibilities will occur to us as we study the red sphere. As noted from my comments on machine learning above, the subconscious is not really using these six attributes per se but draws on a much broader and more subtle set of attributes generalized from experience. But it still faces a subset matching problem that requires more recognition events.
3. Reconsideration. We’re never satisfied with our first recognition; we keep doing it and refining it and verifying it, quickly building up a fairly complex network of associations and likelihoods, which our subconsciously distills down for us to the most likely recognized assembly. So a red sphere among numbered pool balls will be seen as the 3-ball even if the “3” is hidden because the larger context is taken into consideration. A red ball on a Christmas tree will be seen as an ornament. So long as objects fit into well-recognized contexts, the subconscious takes care of all the details, though this leaves us somewhat vulnerable to optical illusions.
Although the possible attribute combinations from approach (2) grow exponentially to infinity, our experience-based memory of encountered attributes using approach (1) constrain that growth. So familiar objects like phones and cars, composed of many identifiable sub-objects and attributes seen in countless related variations over the years, are instantly identified and confirmed using approach (3) even if they look slightly different from any seen before.

Our subconscious recognition algorithms are largely innate, e.g. they know how to identify 3-D objects and assemble memories. But some are learned. Linguistic abilities, which enable us to not only remember things but words that go with them and ways to compose them into sentences, are chief among these for humans. Generalization, mechanics (knowledge of motion), math (knowledge of quantity), psychology (knowledge of behavior), and focusing attention on what is important are other examples where innate talents make things easy for us. We can also train our subconscious procedural memory by learning new behaviors. In this case, we consciously work out what to do, practice it, and acquire the ability to perform them subconsciously with little conscious oversight. I allot both innate and learned algorithms to the recollection phase.

Beyond recognition, we recollect using what I call association-based recall. This happens when thoughts about one thing trigger recollection of related things. This is pretty obvious — our memory is stirred either by seeing something and recognizing it or because thinking about one thing leads to another. I already discussed how our subconscious does this to draw memories together through reconsideration, but here I am referring to when we consciously use it to elaborate on a train of thought. We can also conjure up seemingly random memories about topics unrelated to anything we have been thinking about. While subconscious and conscious free association are vital to maintaining our overall broad perspective, it is the conscious recognitions and associations that drive the reasoning process to make decisions. And in humans, our added ability to consciously direct abstract thinking lets us pursue any train of thought as far as we like.

The second phase, reasoning, is the conscious use of deductive and inductive logic. This means applying logical operations like and, or, not, and if…then on the propositions under attention. Deduction produces conclusions that necessarily follow from premises while induction produces conclusions that likely follow from premises based on prior experience. Intuition (which I consider part of the recollection phase) is very much like a subconscious capacity for induction, as it reviews our prior experience to find good inferences. But that review uses subconscious logic hidden to us which we can generally trust because it has been reliable before, but not trust too much because it is localized data analysis that doesn’t take everything into account the way reasoning can. Recollection and reasoning form an inner RR loop that cycles many times before generating a reaction, though if we need a very quick response we may jump straight from intuition to reaction. Although there is only one RRR loop, the mind multitasks, swapping between many trains of thought at once. This comes in handy when planning what to do next as the mind pursues many possible futures simultaneously to find the most beneficial one. Those that seem most likely draw most of our attention while the least likely hover at the periphery of our awareness.

Just as recollection is mostly subconscious but consciously steered, so too does reasoning leverage a lot of subconscious support, much of which itself leverages memory to hold the propositions and models behind all the work it is multitasking. For example, most of our more common deductions don’t need to be explicitly spelled out because habitual use of plans used many times before lets us blend learned behavior with step by step reasoning to spell out only the details that differ from past experience. So intuition basically tells us, “I think you’ve done this kind of thing before, I’ve got this,” and we give it a bit more rope. But the top level, where reasoning occurs, is entirely conscious and the central reason consciousness exists. A subprocess of the brain that pulls all the pieces together and considers the logical implications of all the parts is extremely helpful for handling novel situations. It turns out that nearly every situation has at least some novel aspects, so we are constantly reasoning.

The third phase of the RRR loop is reaction. Reaction has two components, deciding on the reaction and implementing it. The decision itself is the culminating purpose of the mind and especially the conscious mind, which only exists to make such top-level decisions. The mind considers many possible futures before settling on an action that it believes will hopefully precipitate one of them. The decision is simply the selection of the possible future (or, more specifically, one step toward that future) that the SSSS algorithm has ranked as the optimal one to aim for. That ranking process considers all the beliefs and desires the SSSS is monitoring, both from rational inputs and irrational feelings and intuitions. Selecting the right moment to act is one of the factors managed by that consideration process, so it follows logically from the reasoning process. While there is some pressure to reconsider indefinitely to refine the reaction, there is also pressure to seize the opportunity before it slips away or hampers one’s ability to move on to other decisions. Most decisions are routine, so we are fairly comfortable using tried and true methods, but we spend more time with novel circumstances.

While the SSSS decides on, or at least finalizes, the reaction, it delegates the implementation or physical reaction to the subconscious to carry out as this part doesn’t require further decision support. Even the simplest actions require a lot of parallel processing to control the muscles to perform the action, and the conscious mind is just not up to that or even wired for it. So all of our reactions, in the last few milliseconds at least, leverage innate or habituated behavior. As we execute a related chain of reactions, we will continue to provide conscious oversight to some degree, but will largely expect learned behavior to manage the details. This is why studies show that the brain often commits to decisions before we consciously become aware of them, an argument that has been used to suggest we don’t have free will since the body acts “on its own”. All this demonstrates is that we delegated our subconscious minds to execute plans we previously blessed. Of course, if we don’t like the way things are turning out we just consciously override them. In this way, walking, for instance, becomes second nature and doesn’t require continual conscious focus. But while not in focus, all actions within conscious awareness remain under the control of the RRR loop of the SSSS process, as is necessary for overall coordinated action. Some actions not normally within the range of conscious control, like pulse rate and blood pressure, can be consciously managed to a degree using biofeedback. It is reasonable for us to lack conscious control over housekeeping tasks that don’t benefit from reason. This is why the enteric nervous system, or “gut brain”, can function pretty well even if the vagus nerve connecting it to the central nervous system is severed1.

Recollection, essential for all three phases of the RRR process, assumes we have the right kind of knowledge stored in our memory, but I did not say how it got there. Considering that our memory is empty when we begin life, we must be able to add to our store of memory very frequently early in life to develop an understanding of what we are doing. Once mature, the ability to add to our memory lets us keep a record of everything we do and to expand our knowledge to adapt to changes, which have become frequent in our fast-paced world. From a logical perspective, then, we can conclude that the brain would be well served by committing to memory every experience that passes through the RRR loop. However, one can readily calculate that the amount of information passing through our senses would fill any storage mechanism the brain might use in a few hours or days at most. So we can amend the strategy to this: attempt to remember everything, but prioritize remembering the most important things.

This is a pretty broad mandate. Without some knowledge of the brain’s memory storage mechanisms, it will be hard to deduce more details about the process of mind with much confidence. It is certainly not impossible, and I am prepared to go deeper, but now is a good time to introduce what we do know about how the memory works because brain research has produced some important breakthroughs in this area. While the history of this subject is fascinating and mostly concerns a few patients with short and long-term memory loss, I will jump to the most broadly-supported conclusions, which are mostly well-known enough now to be considered common knowledge. In particular, we have short-term and long-term memory, which differ principally in that short-term memory lasts from moments to minutes, while long-term memory lasts indefinitely. We don’t consciously differentiate the two because the smooth operation of the mind benefits from maintaining the illusion of remembering everything. We know gaps can develop in our memory quickly, but we come to accept them because they have a limited impact on our decisions going forward, which is the role of the conscious mind.

We understand long-term memory better. If you picture the brain you see the wrinkled neocortex, most of which is folded up beneath the surface. But long-term memories are not formed in the neocortex. After all, every vertebrate can form long-term memories, but only mammals have a neocortex. Long-term memory comes in two forms stored very differently in the brain. Procedural memory (learned motor skills) are stored outside the cortex in the cerebellum and other structures, and is inaccessible to conscious thought, though we can, of course, employ it. Declarative memory (events, facts, and concepts) is created in the hippocampus, part of the archicortex (called the limbic system in mammals), which is the earliest evolved portion of the cortex. This kind of long-term memory is rehearsed by looping it via the Papez circuit from the hippocampus through to the medial temporal lobe and back again. After some iterations, the memory is consolidated into a form that joins the parts together (solving the binding problem mentioned above) and is stored in the medial temporal lobe using permanent and stable changes in neural connections. Over the course of years the memory is gradually distributed to other locations in the neocortex so that recent memories are mostly in the medial temporal lobe and memories within twelve years have been maximally distributed elsewhere2. For the most part, I will be focusing on declarative memory (aka explicit memory, as opposed to implicit procedural memory) as it is the cornerstone of reasoning, but we can’t forget that the rest of the brain and nervous system contribute useful impressions. For example, the enteric nervous system or “gut brain” (noted above) generates gut feelings. The knowledge conveyed from the gut is now believed to arise from its microbiome. This show of “no digestion without representation” is our gut bacteria chipping in their two cents toward our best interests.

What about short-term memory? It is sometimes called working memory because long-term memory needs to be put into short-term memory to be consciously available for reasoning. In humans, we know it is mostly managed in the prefrontal lobe of the neocortex. Short-term memory persists for about 10 to 20 seconds but can be extended indefinitely by rehearsal, that is, repeating the memory to reinforce it. In this way, it seems short-term memories can be kept for minutes without actually forming long-term memories. The amount of active short-term memory is thought to be about 4 to 5 items, but can be enlarged by chunking, which is grouping larger sets into subsets of three to four. Short-term memory being kept available by rehearsal can extend this, even though only 4 to 5 items are consciously available at once.

While reasoning probably only considers propositions encoded in prefrontal short-term memory, the other data channels flowing into conscious awareness provide other forms of short-term memory. Sensory memory registers provide brief persistence of sensory data. Visible persistence (iconic memory) lasts a fraction of a second, one second at most, aural persistence (echoic memory) up to about four seconds, and touch persistence (haptic memory) for about two seconds. Senses are processed into information such as objects, sounds, or textures, and a short-term memory of this sensory information independent of prefrontal memory seems to exist but has not been extensively studied. Sensory and emotional data channels that provide a fairly constant message (like body sense or hunger) can also be thought of as a form of short-term memory because the information they carry is always available to be moved into prefrontal short-term memory.

Short-term and long-term memory were first proposed in 1968 by Atkinson’s and Shiffrin’s (1968) multi-store model. Baddeley and Hitch introduced a more complex model they called working memory to explain how auditory and visual tasks could be done simultaneously with nearly the same efficiency as if done separately. From a top-down perspective, the brain has great potential to process tasks in parallel but ultimately must reconcile any parallel processing into a single stream of actions. Processing sensory signals, however, are not reactions to those signals, so it makes sense we can process them in parallel and that some short-term memory capacity in each would facilitate that. If the mechanisms the brain uses to maintain short-term memories of sensory signals and pre-frontal working memory involve close loops that rehearse or cycle the memories to give them enough longevity that the mind has time to manipulate them in various ways, then it makes sense that the brain would have just a handful of such closed loops which work closely with pre-frontal working memory to manage all short-term memory needs. Alan Baddeley proposed a central executive process that coordinates the different kinds of working memory, to which he added episodic buffer in 2000. He based the central executive on the idea of the Supervisory Attentional System (SAS) of Norman and Shallice (1980).

Interestingly, we appear to be unable to form new long-term memories during REM sleep, nor do our dreaming thoughts pursue prioritized objectives. However, if we are awakened or disturbed from REM sleep we can recover our long-term storage capacity quickly enough to commit some of our dreams to memory. This suggests some mechanisms of the SSSS are disabled during dreaming while others still operate3.

Having established the basic outer process of the conscious mind as an RRR loop within an SSSS process supported by algorithms and memory that largely operate subconsciously, the next question is how this framework is used to generate the content of the conscious mind, concepts and models.

  1. Function of the Vagus Nerve
  2. Where Are Old Memories Stored in the Brain?, Moheb Costandi, February 10, 2009, Scientific American
  3. Why Do We Forget Dreams? Part II, Krishnagopal Dharani, 2014

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