The second mode of thinking is directed thinking, which we use when we attempt to solve a problem or formulate an organized response. For example, we might be rehearsing in our mind something we plan to say to someone, or we might be formulating a passage we want to write (in a book on the mind, perhaps). As we think about tasks such as these, we have already broken down each one into a hierarchy of subtasks. Writing a book, for example, involves writing chapters; each chapter has sections; each section has paragraphs; each paragraph contains sentences that express ideas; each idea has its configuration of elements; each element and each relationship between elements is an idea that needs to be articulated; and so on. At the same time, our neocortical structures have learned certain rules that should be followed. If the task is writing, then we should try to avoid unnecessary repetition; we should try to make sure that the reader can follow what is being written; we should try to follow rules about grammar and style; and so on. The writer needs therefore to build a model of the reader in his mind, and that construct is hierarchical as well. In doing directed thinking, we are stepping through lists in our neocortex, each of which expands into extensive hierarchies of sublists, each with its own considerations. Keep in mind that elements in a list in a neocortical pattern can include conditionals, so our subsequent thoughts and actions will depend on assessments made as we go through the process.
Moreover, each such directed thought will trigger hierarchies of undirected thoughts. A continual storm of ruminations attends both our sensory experiences and our attempts at directed thinking. Our actual mental experience is complex and messy, made up of these lightning storms of triggered patterns, which change about a hundred times a second.
Dreams are examples of undirected thoughts. They make a certain amount of sense because the phenomenon of one thought’s triggering another is based on the actual linkages of patterns in our neocortex. To the extent that a dream does not make sense, we attempt to fix it through our ability to confabulate. As I will describe in chapter 9, split-brain patients (whose corpus callosum, which connects the two hemispheres of the brain, is severed or damaged) will confabulate (make up) explanations with their left brain—which controls the speech center—to explain what the right brain just did with input that the left brain did not have access to. We confabulate all the time in explaining the outcome of events. If you want a good example of this, just tune in to the daily commentary on the movement of financial markets. No matter how the markets perform, it’s always possible to come up with a good explanation for why it happened, and such after-the-fact commentary is plentiful. Of course, if these commentators really understood the markets, they wouldn’t have to waste their time doing commentary.
The act of confabulating is of course also done in the neocortex, which is good at coming up with stories and explanations that meet certain constraints. We do that whenever we retell a story. We will fill in details that may not be available or that we may have forgotten so that the story makes more sense. That is why stories change over time as they are told over and over again by new storytellers with perhaps different agendas. As spoken language led to written language, however, we had a technology that could record a definitive version of a story and prevent this sort of drift.
The actual content of a dream, to the extent that we remember it, is again a sequence of patterns. These patterns represent constraints in a story; we then confabulate a story that fits these constraints. The version of the dream that we retell (even if only to ourselves silently) is this confabulation. As we recount a dream we trigger cascades of patterns that fill in the actual dream as we originally experienced it.
There is one key difference between dream thoughts and our thinking while awake. One of the lessons we learn in life is that certain actions, even thoughts, are not permissible in the real world. For example, we learn that we cannot immediately fulfill our desires. There are rules against grabbing the money in the cash register at a store, and constraints on interacting with a person to whom we may be physically attracted. We also learn that certain thoughts are not permissible because they are culturally forbidden. As we learn professional skills, we learn the ways of thinking that are recognized and rewarded in our professions, and thereby avoid patterns of thought that might betray the methods and norms of that profession. Many of these taboos are worthwhile, as they enforce social order and consolidate progress. However, they can also prevent progress by enforcing an unproductive orthodoxy. Such orthodoxy is precisely what Einstein left behind when he tried to ride a light beam with his thought experiments.
Cultural rules are enforced in the neocortex with help from the old brain, especially the amygdala. Every thought we have triggers other thoughts, and some of them will relate to associated dangers. We learn, for example, that breaking a cultural norm even in our private thoughts can lead to ostracism, which the neocortex realizes threatens our well-being. If we entertain such thoughts, the amygdala is triggered, and that generates fear, which generally leads to terminating that thought.
In dreams, however, these taboos are relaxed, and we will often dream about matters that are culturally, sexually, or professionally forbidden. It is as if our brain realizes that we are not an actual actor in the world while dreaming. Freud wrote about this phenomenon but also noted that we will disguise such dangerous thoughts, at least when we attempt to recall them, so that the awake brain continues to be protected from them.
Relaxing professional taboos turns out to be useful for creative problem solving. I use a mental technique each night in which I think about a particular problem before I go to sleep. This triggers sequences of thoughts that will continue into my dreams. Once I am dreaming, I can think— dream —about solutions to the problem without the burden of the professional restraints I carry during the day. I can then access these dream thoughts in the morning while in an in-between state of dreaming and being awake, sometimes referred to as “lucid dreaming.” 5
Freud also famously wrote about the ability to gain insight into a person’s psychology by interpreting dreams. There is of course a vast literature on all aspects of this theory, but the fundamental notion of gaining insight into ourselves through examination of our dreams makes sense. Our dreams are created by our neocortex, and thus their substance can be revealing of the content and connections found there. The relaxation of the constraints on our thinking that exist while we are awake is also useful in revealing neocortical content that we otherwise would be unable to access directly. It is also reasonable to conclude that the patterns that end up in our dreams represent important matters to us and thereby clues in understanding our unresolved desires and fears.
As I mentioned above, I led a team in the 1980s and 1990s that developed the technique of hierarchical hidden Markov models to recognize human speech and understand natural-language statements. This work was the predecessor to today’s widespread commercial systems that recognize and understand what we are trying to tell them (car navigation systems that you can talk to, Siri on the iPhone, Google Voice Search, and many others). The technique we developed had substantially all of the attributes that I describe in the PRTM. It included a hierarchy of patterns with each higher level being conceptually more abstract than the one below it. For example, in speech recognition the levels included basic patterns of sound frequency at the lowest level, then phonemes, then words and phrases (which were often recognized as if they were words). Some of our speech recognition systems could understand the meaning of natural-language commands, so yet higher levels included such structures as noun and verb phrases. Each pattern recognition module could recognize a linear sequence of patterns from a lower conceptual level. Each input had parameters for importance, size, and variability of size. There were “downward” signals indicating that a lower-level pattern was expected. I discuss this research in more detail in chapter 7.
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