c) If a higher-level pattern recognizer is receiving a positive signal from all or most of its constituent patterns except for the one represented by this pattern recognizer, then that higher-level recognizer might send a signal down to this recognizer indicating that its pattern is expected. Such a signal would cause this pattern recognizer to lower its threshold, meaning that it would be more likely to send a signal on its axon (indicating that its pattern is considered to have been recognized) even if some of its inputs are missing or unclear.
d) Inhibitory signals from below would make it less likely that this pattern recognizer will recognize its pattern. This can result from recognition of lower-level patterns that are inconsistent with the pattern associated with this pattern recognizer (for example, recognition of a mustache by a lower-level recognizer would make it less likely that this image is “my wife”).
e) Inhibitory signals from above would also make it less likely that this pattern recognizer will recognize its pattern. This can result from a higher-level context that is inconsistent with the pattern associated with this recognizer.
f) For each input, there are stored parameters for importance, expected size, and expected variability of size. The module computes an overall probability that the pattern is present based on all of these parameters and the current signals indicating which of the inputs are present and their magnitudes. A mathematically optimal way to accomplish this is with a technique called hidden Markov models. When such models are organized in a hierarchy (as they are in the neocortex or in attempts to simulate a neocortex), we call them hierarchical hidden Markov models.
Patterns triggered in the neocortex trigger other patterns. Partially complete patterns send signals down the conceptual hierarchy; completed patterns send signals up the conceptual hierarchy. These neocortical patterns are the language of thought. Just like language, they are hierarchical, but they are not language per se. Our thoughts are not conceived primarily in the elements of language, although since language also exists as hierarchies of patterns in our neocortex, we can have language-based thoughts. But for the most part, thoughts are represented in these neocortical patterns.
As I discussed above, if we were able to detect the pattern activations in someone’s neocortex, we would still have little idea what those pattern activations meant without also having access to the entire hierarchy of patterns above and below each activated pattern. That would pretty much require access to that person’s entire neocortex. It is hard enough for us to understand the content of our own thoughts, but understanding another person’s requires mastering a neocortex different from our own. Of course we don’t yet have access to someone else’s neocortex; we need instead to rely on her attempts to express her thoughts into language (as well as other means such as gestures). People’s incomplete ability to accomplish these communication tasks adds another layer of complexity—it is no wonder that we misunderstand one another as much as we do.
We have two modes of thinking. One is nondirected thinking, in which thoughts trigger one another in a nonlogical way. When we experience a sudden recollection of a memory from years or decades ago while doing something else, such as raking the leaves or walking down the street, the experience is recalled—as all memories are—as a sequence of patterns. We do not immediately visualize the scene unless we can call upon a lot of other memories that enable us to synthesize a more robust recollection. If we do visualize the scene in that way, we are essentially creating it in our mind from hints at the time of recollection; the memory itself is not stored in the form of images or visualizations. As I mentioned earlier, the triggers that led this thought to pop into our mind may or may not be evident. The sequence of relevant thoughts may have been immediately forgotten. Even if we do remember it, it will be a nonlinear and circuitous sequence of associations.
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.
The Language of Dreams
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.