Question Everything

Talking to Myself - Who is Listening?

Other Parts of the Series:

Part 1: Exploring Consciousness

Part 2: Who is "I"?

Part 3: Talking to Myself - Who is Listening?

Part 4: The Epitome of Consciousness

The Story of Me

We are a chatty lot!

Is there a point to all of this verbiage? Why do we talk to others and to ourselves? We can do something that other animals can't do, or can't do nearly as well as we do. We can generate an infinite variety of utterances from a finite set of auditory elements (e.g., phonemes). But more importantly these utterances convey meaning at multiple levels even when governed by a seemingly limited set of rules — grammar. Random utterances won't do. The rules force a speaker to construct utterances that have structure on multiple levels and it is the large-scale structure, along with the “grounding” of the utterances in a particular level (words or lexicon) that cause the structures at higher levels of organization (sentences and paragraphs) to carry meaning or semantic value. It is this fact that provides an evolutionary explanation for language. The meanings in our utterances increase our fitness as a species. They allow us to interact with the rest of the world successfully.

It goes beyond simple fitness, of course. Other animals are successful to the extent they are fit within their environments. But humans have no single environment (niche). By virtue of their generalized physiology (e.g. the omnivore diet) and their consciousness they are able to colonize essentially any Earthly environment (save Antarctica pre-19th century). They are explorers as well as exploiters. And one of the facilities that made them really good at it is the ability to convey to one another their experiences in exploring. They could share their personal histories with one another by telling stories. These personal histories, or the biographical memories I discussed in the previous post, are about things important to human well-being. Those are the things we tend to fix in memory traces in our brains. And, because of the way the world unfolds as a temporal sequence of parallel events, they are stored in sequences of mental images that also constitute our personal models of how the world works.

The stories of our biographical selves are rich in content and the biological meaning of that content. A typical story I might construct would be something like this:

My Story Today (So Far)

As I got dressed this morning the weather report on the radio said it would be raining and cold so I decided to wear warmer clothes. I remembered that I would not be able to eat lunch until later in the afternoon because I would be traveling from a meeting in Seattle that would not get out before 11:30am and I wouldn't get back to my office (and lunch) until 2:30. I decided to eat a more hearty breakfast than usual, which I did - bacon and eggs with toast. I then cleaned up the kitchen (so I wouldn't get yelled at for leaving a mess!) Got in my car and drove to Seattle. Saw a minor accident on the freeway. It slowed us down but thankfully there were no ambulances at the scene and it didn't look too bad... [goes on and on!]

Notice how my story contains a lot of detail. Notice how it pertains often to my situation and my well being. Notice how it contains elements of how I thought about the future, yet to be experienced. Notice how it contains peripheral conditions that might or might not be relevant to anything at the instant but were similar to past conditions that were. I have a lot to tell. Much of it is of no interest to anyone else because it doesn't pertain to their situations, at least not directly.

Contrast my story with that of my cat. What story can she tell? Here is a sample of her “thoughts.”

My Cat's Story (as told to me!)

I just experienced the availability of food. I just experienced a gratifying feeling of not being hungry anymore. I just experienced my human petting me - felt good. I just experienced my owner throwing me out of the warm place - did not like it. [and other stuff as it happens].

My cat has a story of sorts, in that it contains a sequence of events that are meaningful to her personally. She doesn't think in words of course. But each of those sentences contain particular concepts that she is capable of minding. Notice, however, that she is probably the only being affected by the events and the only one who at all “cares.” Notice how her thoughts are basically in the here and now. She has some memory of the past (being hungry, probably a memory of being thrown out), but doesn't seem to have a way to use that memory to make many predictions about the future, except possibly remembering that I always throw her out of the house after feeding her. She might anticipate future states of her being but probably not future processes or pathways and events that lead to those states^[1].

Where my cat's story is just about herself and is only relevant to herself, my story contains a few hints that other people might actually care about those parts of it that involve interactions with them. We don't just talk to ourselves (or more precisely, mind our narratives to ourselves) we communicate with other people. We care about what is in their minds and they care about what is in ours. We often wish to shape their thinking and behavior based on our desires and they are doing the same to us. Language allows humans to cooperate behaviorally in ways that are not remotely possible in the lower animal kingdom^[2].

The Content of the Story

In the case of language using abstract symbols (words), those symbols have to be grounded in meaning from the real world. There are ‘things’, there are ‘relations’ between things, and there are ‘motions’ of things that change them and their relations. Everything gets a name (a noun) used as a placeholder in mental structures (localized neural networks in premotor cortex that if activated would produce the muscle actions needed to voice the word). Such structures are formed when we first learn a word and connect it to its referent in the environment. We learned the concept of a ‘dog’ by seeing an example of a dog and hearing the word dog used in the context of seeing it. It probably takes many iterations of the co-experience of seeing the form of a dog and hearing the utterance from, say, an adult before we can, upon seeing another dog, correctly use the word. Or before we can hear the word spoken and conjure up a generalized image of a dog.

Relations are covered by most spatial and temporal prepositions (and phrases). “The man sat on the horse” signals a spatial (and by implication a temporal) relation between two objects, a man and a horse. Verbs signal actions that lead to relations. The man had to ‘mount’ the horse in order to be on it. All words are either placeholders (abstractions) for these three aspects, or are used to enhance and put focus on one of the three types.

The various grammars that have evolved in different cultures do seem to be based on a universal template for how to further relate these three aspects. There is a subject (a noun), an action (verb), and an object (another noun, explicit or implicit, as when the subject is also the one affected by the action). Language, then, is a tool to model the dynamical possibilities for things working in the world. It can be used to describe the world because it so well models the way the world works, that is, how the world is a system of subsystems. In this sense I have claimed that humans (and animals too) have a built-in model of systemness which they use to construct memories of actual things that happen in their experiences. Those memories build up the complex that constitutes a biographical self. But in humans there is a secondary set of images coupled with the primary set of sensory-driven images. That set is derived from motor images (voiced sounds) and contains abstract representations of the things, relations, and motions in the primary set. This secondary set is governed by the rules of systems dynamics or, in other words, the universal grammar. And it generates models that are temporally ordered stories of what the observer perceives or what the thinker thinks.

The contents of stories aren't just plain descriptions of the world. Stories are not simply recordings of what happened to be played back for future reference. Every story has semantic value, and that value is based on biology. Every being is mandated by their biology to maintain biomass, grow and replicate more biomass whenever possible. To that end, every thing that happens in the world around the individual and their offspring has significance. Events and states of the world, the things and their dynamics in the world, have potential to thwart or support the biological mandate. Therefore all stories are tagged with meaning relative to those potentials. While it is true that many events and states in the world might seem neutral in any one episode, the fact that relations (causal ones in particular) can change in nonstationary ways means that even supposed benign states of the world could, in the future, turn threatening. Thus we tend to integrate such stories into our store of understanding just in case it does become biologically meaningful in the future. For example the political turmoil in a distant land might seem too far away to be of concern: How could it affect me and my family? But as events like 9/11 have shown us, the capacity for distant turmoil to affect us much more directly cannot be dismissed.

Damasio identified affective semantic tags, calling them “somatic markers”, in which a memory of a story (the narrative) and its integrated form in our larger model of the world is associated with a state of the soma (body) resulting from the progression of events and states observed. His reason for calling it a somatic effect is that our bodies are biophysically changed in response to things we encounter. No one (with normal brains) who witnessed the events of 9/11, even on TV, could not have had a gut wrenching feeling or experienced an emotion of horror. Feelings are associated with every body state even when they do not produce strong emotional reactions. And when memory traces are formed, there are affective connections also encoded in the traces (these arrive in the neocortex from limbic sources). Every sentence in our developing narrative takes on meaning in a hierarchy of abstractions, from the concrete biological needs of the self to how those are met by interactions with the rest of the world, most especially other people. Our social narratives, in fact, are the most compelling of all; William Shakespeare understood that.

Our memories thus have two kinds of content in strong association. The first is the stream of concepts strung together according to the rules of the grammar (dynamics of the systems) forming the story or narrative that is minded. The second is the affective meaning of the stories insofar as how they relate to our personal biology. When we relive a story (recall events and states of the world) we also relive, to some extent, the states of our bodies, our feelings, and emotions that attended the original story as it unfolded.

Conscious Conversations

Some cognitive scientists have suggested (at least in the past) that consciousness depends on language; that consciousness is a result of the language facility. Or, at least, that consciousness and the language facility are co-extensive. But the evidence from studies of self-consciousness in animals like apes, dolphins, and elephants clearly indicate that, at least with respect to self-consciousness, languages of the human sort are unnecessary. The mind of these creatures can still form the images of things, relations, and actions. They can even store memories of stories to be used to generate models of how the world (their world) works and make predictions or anticipations of the near future. It is likely true that language and the advances in consciousness in humans (as compared with our progenitor species) co-evolved. That is, as one became marginally more complex, the other may have been spurred to up the game. For example, one theory holds that nouns were the first verbal utterances made (probably in a species prior to modern sapiens). People were in the business of giving names to objects but did not yet know how to indicate actions (verbs) so needed to “act out” stories involving the named objects not unlike we do with the game of charades. The acting compelled humans to form images of action that acted as a selective force on the developing language complex (now recognized as Wernicke's (listening) and Broca's (voicing) areas in the left hemisphere). We still act out stories even when we have an adequate vocabulary to describe everything. We use hand gestures and body movements to add emphasis to our speech. And, indeed, acting as a form of entertainment persists because it was and is such a powerful way to convey how we think the world works to others.

By this theory descriptions of relations came last as these involve more subtle ways of describing. In any case it is no longer considered that the evolution of language preceded that of consciousness or was the cause of the emergence of consciousness. What the evolution of language permitted is the sharing between individuals of their stories. Body language and facial expressions helped convey the semantic (emotional) content and sentences, etc. conveyed the systemic content. People could learn from one another rather than always rely on direct experience to form new stories (e.g. how to shape an arrow head by description rather than demonstration). Our modern education system is largely based on learning by telling (lectures). Only in those subjects that rely extensively on hands-on experience do we supplement telling with experiential learning (labs).

The co-evolution of language and higher-order consciousness extended to the realm of social interactions and may be the reason that individuals started to construct more expanded narratives of themselves and not just their world. That is, a person did not just have a sense of self, as all animals do, but a story of self, an identity and autobiography. They possess a model of who they are and what they are like. We call this a self-image.

These stories come from how other people react to things we do. Their words and actions tell us something about ourselves that we incorporate into our self stories (it turns out every individual maintains multiple, sometimes conflicting stories about who they are!) Watching how we affect other people is essentially looking at ourselves in a behavioral mirror. Social psychology posits that our self identities are largely defined by our social life. It could even be that if one did not live in a social group, one might not develop a “theory” of who they are.

Our stories of the world are also mostly stories of other people. We construct models of others, in particular what they are thinking, as part of trying to predict how they will respond to our actions in the future. This theory of mind is thought to be based on our own recognition that we, as individuals, have a mind and hypothesize that those who are much like us (our fellow beings) must also have minds. Since we have an autobiographical story available to our minds, we assume others must have their own version of such a story. Since we each have intentions, we assume others do too based on their own stories and thus if we could empathically grasp their stories (by building a model of them within our own minds) we might be able to understand their intentions and, thus, their motives and action choices under various situations.

When I say that people construct models of others and assume they have minds, etc. I do not mean that people do these things consciously. Quite the contrary, most of our propensity to build such models is intrinsic in the way our brains work. It is done subconsciously and the results come into consciousness only in the form of social judgments we make when actually interacting. On rare occassions we might consciously consider what another might be thinking at a moment in order to anticipate their next move. Most of the time our social interactions (and here ‘social’ includes all kinds of interactions at all levels of intimacy with others) are pretty automatic. We don't actually have to think about what we are going to say or do next. The better our subconscious model of the other is, the more fluid our responses and actions will be.

Society depends critically on every member building a model of itself and all the others that have interactions with it. Love, liking, disliking, hatred, etc. are the somatic markers that attach to the intricacies of those models. Suspicion, fear, etc. also can be attached based on internal biases or just plain caution when we do not have a model of a particular individual we come in contact with. One way or another we all have feelings about everyone we come in contact with even if only because they remind us of someone we do know and have stronger feelings about. “That guy reminds me of my uncle Joe. Now there was a worthless lout!”

One thing is certain. The success of social interactions depends on just how veridical our models of self and others are. The more accurate our representations, the more effective our interactions should be. Every human starts out life motivated to cooperate — that motivation is built deeply into us biologically. Competition is fallen back on when warranted, but the ideal of a cooperative society is actually able to produce conditions in which competition need not predominate. There are very many examples of indigenous communities where cooperation (within the community) led to stable and sustainable living for the majority. In fact, one of the prevailing explanations for the evolution of so-called mutual altruism in humans is the theory of group selection in which tribes of cooperators out-competed tribes of individualists for the extant resources, thus giving an evolutionary (fitness) edge to cooperation in social groups.

The Higher Order of Human Consciousness

Language doesn't make us conscious in the way that we are. It does provide us a tool to be used in our consciousness for expressing complex relations and making fine distinctions between similar objects as well as providing a way to manipulate thoughts of things, relations, and motions in an abstract way. Language is crucial to the kind of thinking that we do, but it is not the origin or cause of the kind of consciousness we have.

Chimpanzees are conscious of themselves. They can even learn to associate a small set of signs (symbols, including spoken words and sign language expressions) with things, actions, and to a lesser degree relations. They can reason about their world because they, like us, have a kind of systems grammar that guides the manipulation of images of those things, motions, and relations. They can even back-relate their knowledge of the signs once they have thought through a particular manipulation and express the outcome. For example a chimpanzee that knows sign language can be thinking about a food item, say a banana, and feel hungry. So it would give the sign for eating (action) and banana (thing) indicating it wanted a banana to eat. It probably didn't think, “Gee, I'm feeling peckish. What would taste good right now? What might be in the pantry? I know, a banana fits the bill. I want a banana, please.”

Humans have obviously taken the thought process to a new level. They can think in the abstract and attach words to the thoughts to motivate actions (by someone else?) They can fine tune or shape the way the actions are going to play out by how they construct the sentences. And they can use this facility to actively (that is consciously) think about the state of things sometime into the future. This is typically what we mean when we talk about human level consciousness. It isn't particularly different from that possessed by chimpanzees it is just much more elaborate (in content), more comprehensive (in including both immediate and hidden things), and much longer in time scope (past and future).

However, it turns out that even though human consciousness is more elaborate than our predecessors possessed, our brains still retain the same kind of thinking that underlies all animal thinking. Here the questions might be asked, such as where do thoughts come from in the first place? What causes a chimp to consider specifically a banana for food? What causes you to consider what kind of ethnic food sounds good for dinner? Thoughts seem to come into consciousness from some mysterious, deeper part of the mind and we are not aware of the process that produces them. Once in consciousness we can actively manipulate ideas and talk to ourselves about whatever the subject is about. But why those thoughts in the first place? Where do they come from? How do they get into conscious awareness? These are the kinds of questions I will be exploring in a future posting.

Once thoughts are in consciousness humans take things one step further, aside from expressing thoughts in language. Humans can also be conscious of being conscious of thoughts. That is a person could have, “in the back of their mind” a secondary kind of thought, a thought about the thoughts that had been occupying their consciousness. Everyone has an experience of, for example, thinking about someone out of the blue (maybe in a daydream) and then that thought might lead to a question such as, “Gee I wonder why I just thought about so-and-so?” That is just one kind of thought leading to another in a train of thoughts. But some people will recognize a different kind of situation. The second thought does not follow from the first thought, nor is it quite so explicit in nature. Instead it is felt as a vague sort of question or more likely just an awareness of a puzzlement siting on top of the thought of the person. In other words, both kinds of thoughts happen simultaneously. The latter does not displace the former in explicit consciousness. They are both present concurrently as if there is yet another self in the background observing the foreground self having a thought.

Such experiences are fleeting and usually rare. I suspect there are some people who never quite recognize the phenomenon because the second kind of thought is so faint. Nevertheless, I postulate that there is something very real going on here. Namely, if you look back at figure 3 in the blog of April 19, Who is 'I' the top-most ‘map/model’ is labeled Planning Model and is responsible for the consciousness of one's own agency. I suspect that while much of the functionality of this map is subsumed under the working of Brodmann area 10 (BA10), as explained in that post, I believe that radical expansion of BA10 in our late evolution brought much more to the human mind. There might be yet a higher order map/model that is monitoring (observing) the planning model in that figure. In other words there may yet be an observer of what we had thought of as the top level observer. My coming exploration of thoughts will provide an entrée into this conjecture. I think it has a lot to do with the ancient mysticisms regarding the nature of a non-physical soul or the experience of what is referred to often as “pure consciousness”. The latter is often described as ineffable, something experienced but not really describable. My suspicion is that this is because it is the newest facility to evolve and is related to sapience in a deep way. Ordinary humans have just not quite got a handle on it like we do on conscious thinking with language. But who knows what evolution might yet produce. Is it also possible that this “experience of experience” is strengthened by various meditative practices? That might be an interesting topic!

References

Damasio, Antonio (1994). Descartes' Error: Emotion, Reason, and the Human Brain, HarperCollins Publisher, New York.

Damasio, Antonio (2000). The Feeling of What Happens, Mariner Books, New York.

Damasio, Antonio (2010). Self Comes to Mind: Constructing the Conscious Brain, Random House LLC, New York.

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Footnotes

[1]. Interestingly one of the possible differences between cats and dogs is that the latter do seem to form memories of processes or stories that make predictions of future events. Moreover, dogs seem to have fairly long-lasting working memories. We've all heard stories of the dog who waited by the door patiently for his owner to return home. Experiments on distracting dogs who are waiting for something important to them have shown that after the distraction they are able to go back to what they were doing as if they remembered. One explanation of this more human-like memory and thinking (even if concepts are not voiced) is that dogs and humans evolved very similar lifestyles in terms of running in groups, hunting, etc. Our minds are quite similar because we evolved under similar conditions and in similar niches.

[2]. Ants communicate with one another to affect coordinated behaviors. They do it with chemical excretions called pheromones. These are like odor-producing (vaporizing) chemicals that ants use to send messages to their nest-mates. The pheromones trigger fixed behaviors in the receiving ants thus achieving a form of cooperative response. The pheromones evaporate after being emitted so that the signal is strong initially and then fades over a matter of minutes to hours. This is a kind of communications short-term memory that decays unless reinforced with more pheromone emissions.

Who is “I”

Other parts of the Series:

Part 1: Exploringing Consciousness

Part 2: Who is "I"?

Part 3: Talking to Myself - Who is Listening?

Part 4: The Epitome of Consciousness

The Semantic Trap

It seems nearly impossible for a writer tackling the consciousness problem to avoid a linguistic trap. Ultimately, when we describe consciousness as an act of ‘observing’ ourselves in the act of observing the environment and our physical states^[1] we are faced with a seeming paradox. I am observing myself observing the world, but who is the “I” doing the observing? Is there an “I” observing the world? Is there another “I” observing the first “I”?

Douglas Hofstadter, in his 2007 book, I Am a Strange Loop claimed that these seemingly multiple “Is” were really one and the same observer and that the observer is a self-referential entity that is observing itself observing.

On the other hand, Antonio Damasio, in The Feeling of What Happens has constructed a layered architecture in which a series of “maps”, e.g. cortical and sub-cortical structures that process images act as observers of the layers below (see figure below). That is, information about what is happening in the world and in the body passes upward toward layers that will use this information, along with knowledge encoded in memory and innate dispositions (from lower levels) to decide what actions should be taken. This is basic consciousness, or what Damasio calls “core consciousness.” Much of the functions contributing to core consciousness are performed in the more primitive parts of the lower brain. The five lower maps shown below are formed in various cortical areas in midbrain and paleocortical structures such as the amygdala and hippocampus. The two higher level maps were possible as soon as structures such as the cingulate cortex could encode experiential knowledge and provide comparative analysis between what is happening and what memory predicted would happen.

 

Figure 1. From Figure 3 in prior posting.

 

The evolution of the neocortex in mammals added a spectacular capability in forming much more complex maps as well as greatly expanded monitoring of the biographical self. The neocortex is a massive memory system (c.f. Fuster, 1999) that allows an animal to build a historical record of experiences and how those experiences affected the organism. This memory system is actually a learned model of how the world works and how the organism works in that world. In figure 2 I show what I call a “Super-observer model” that is dependent on neocortex sufficient to integrate experiences into the developing model. The new map/model^[1] is capable of asking more advanced questions regarding how successful the organism has been over its lifetime at dealing with and adapting to the environment it has been interacting within.

The organism now maintains a more explicit sense of the self. The model that is constructed within the neocortex includes a model of the self. Most of the framework of the model comes from the core self, the brain's inherent and generally fixed operational, basic logistics, and basic tactical models (e.g. the amygdala monitors for threats in the sensory fields). But the neocortex-based model allows for incorporation of learned experience into that framework. For example the amygdala might be leery of any snake-like (slithering) thing that it detects. It would initiate a response in the form, usually, of getting away. Evolution “trained” this structure to recognize and respond to snakes because, over the history of the species and its predecessors, snakes have proven to generally be dangerous (circuits in the amygdala that triggered safety responses were selected for, those that didn't got their possessors bitten!) But with a neocortical model, the organism might learn that not all slithering is done by snakes and so even if the amygdala tries to initiate escape, the early prefrontal cortex could check the model and re-check the source of the trigger and decide to not escape if it isn't warranted. This is how dogs and cats can learn to be friends!

The self model in neocortex is far more malleable than the core model. It can override the core model (as just explained) under appropriate conditions and this has tremendous fitness benefits for animals that explore larger and more complex environments for increased opportunities for food and mates. The core model is course-grained. It treats many different objects as threats or opportunities that really aren't in the larger context. If you responded by running away every time your amygdala detected what it thought was a threat you would miss some opportunities that could contribute to your success.

 

Figure 2. The expansion of core consciousness depends on a higher-order map that has access to a biographical memory.

 

Mammals and many birds behave as if they had a sense of self. That is they do not merely react to stimuli in pre-programmed ways all the time (as a reptile generally does). They show the ability to problem-solve in novel situations, such as getting a food morsel out of a bottle^[2].

A sense of self comes from monitoring the impacts that things happening in the environment have on the organism's body. Every action-result pairing has some affective impact, such as when food is successfully obtained the ‘pleasure’ associated with the action to get it has a reinforcing effect on learning that pairing. Rewarding stimuli-action pairs makes those more likely to be chosen in the future. Similarly punished behaviors are made less likely. Damasio (1994) describes what he calls “somatic-markers”, or conditions of the body state concurrent with the mental images being processed, where affective (emotional) states can be associated with newly formed memory traces so that in the future the activation of those traces can be influenced by the emotional content. For example a memory that was formed under negative emotional states may affect a current condition decision if that trace is re-evoked in the present. The possessor will tend to avoid whatever triggered the recall.

The Great Leap Forward

Primates evolved more extensive prefrontal cortical areas that were larger proportionally to the rest of the neocortex (for the size of the brain). The prefrontal cortex sits at the very apex of the behavior decision processing. It has been said to perform the “executive” functions, which includes things like directing attention, calling relevant dormant memories into working memory, even just deciding what needs to be decided. These brain circuits emerged as management specialists to coordinate the rest of the neocortex in their functions. Fuster asserts that they evolved from more primitive motor cortex in the frontal lobe and are, in fact, specialized action (motor) cortex. But the multiple coordinators needed to be coordinated among one another. For example there is a circuit that is responsible for evoking some functions in the cingulate cortex that will make comparisons between items in sensory vs. working memory. Based on the outputs of the cingulate cortex another patch of circuitry decides how to integrate the new sensory information into the exiting model (active in working memory). These circuits need to be coordinated in action and timing in order to produce the proper sequence of processing steps.

The precursors for these circuits already existed in older frontal lobe cortex. The “Super-observer” not only observed what is happening now relative to what has happened in the history of the individual, it also became responsible for considering alternative behavior options in order to add more exploratory possibilities to the repertoire, Rather than be completely dependent on already learned behaviors, mammals evolved increasing ability to try new possibilities. This required a higher order judgment capability than the simpler comparison analysis provided by the older cortices. This too was accomplished in the prefrontal circuits that sat right at the right point of convergence of all the information flows.

The patch of tissue in the prefrontal cortex, right at the very apex, right behind the eyebrows (in human skulls) evolved as the “final” model/map that became responsible for coordinating all of the coordinators (the rest of the prefrontal cortex). To do this the capacity to ask what alternative behaviors might be tried needed to become a more organized and motivated function. It had to coordinate all of the other resources of the brain to formulate plans for future activities. The organism is always driven by biological needs. These are the motivations that drive the organism. The long-range plans (which need not be conscious, ironically) have to support meeting these needs.

Consider, for example, the biological mandate to reproduce. We humans, and presumably all animals, are not consciously aware of a drive to reproduce. Instead there exist subtle and powerful drives to have sex, which provides rewards to the organism (dopamine shots!). But humans construct elaborate models of love and bonding relations that constitute their basic ‘plans’ for ultimately consummating a fertilization event leading to one or more children. All of our conscious thoughts about love and mates, how to choose the ‘right’ one, etc. constitute our plans and whatever they turn out to be (and they can be incredibly variable in content) they will drive us to make choices in daily life that should lead to success in reproduction. That is, if the plans we constructed are realistic. A major problem with the human condition, being subject to the developmental (learning) influences of a complex culture, is that too often, especially in modern life, those plans are essentially unrealistic. An example is the Hollywood version of love and ‘happy ever after.’ Most people (present company not excepted!) have tremendously wrong visions of what marriage will be when they achieve it. This is a major downside to being conscious and non-conscious simultaneously.

 

Figure 3. Part of the prefrontal cortex adds a new kind of map/model that works on planning longer-term courses of action or “strategies.”

 

The sense of having a purpose emerges from the construction of a planning model and the on-going monitoring of the execution and success of the plan produces the sense of agency — the self power to exercise control over the self's situation especially by controlling elements of the environment.

Too often the plan simply isn't viable. It does not represent the real world, or the real self, as they actually are. And this can lead to a major disconnect between expectations (to carry out the contents of the plan) and actual results — that sense of power over the environment is thwarted. The frustration that builds up internally as a result of continuous disappointment, whether consciously experienced or not, leads to mental breakdowns sooner or later. Our modern culture seems to be particularly good at influencing the construction of unrealistic plans and unrealistic beliefs about how the world works and who we are as persons.

The smallish patch (designated as Brodmann area 10, BA10, in brain area maps) isn't a homunculus. It does not accomplish all of these functions and be the seat of the memories of the senses of purpose or agency. It is just a super coordinator whose task is to coordinate all of the rest of the brain components to accomplish these results. This model of the brain and the functions of regions fit the hierarchical cybernetic model of operational, logistical, tactical, and strategic management (see my post: The Science of Systems 7. The control is over the vast memory stores in that hierarchical fashion. BA10 coordinates existing prefrontal areas for long-range plans and monitoring. They, in turn, coordinate multiple other areas in association and pre-motor cortices.

Human consciousness, at its best, involves a brain actively observing its own working, which is primarily the organization of memories on the basis of prior experience and current situations but mediated by memories of the future (plans). But this level of consciousness is not always active. Most of our lives are governed by current perceptions, especially when we are concentrating on accomplishing specific tasks. We only enter this consciousness of consciousness when demands from the external world are not keeping us focused and responding.

Over the last one hundred thousand years (or more) human evolution has seen a tremendous jump in the size and connectivity of BA10. One of the most important effects that may have been a result of this is the great increase in level of judgment, that is judgments over much more complex and longer-time scale issues. Additionally human empathy and altruism have increased in concert with the expansion of BA10 (and judgment). This is what I have called “sapience.”

Consciousness of self and of self being conscious is the new capacity of the human brain, evolved from precursors in mammalia, primates, and hominid genera. Humans are a new kind of animal and are potentially positioned to become a hyper-social being, not like ants or even naked mole rats, but wholly unique in how they can organize their social conditions and their lives. However, it is looking like that will take more evolution and more time than we may have available..

Observing the Observer Observing another Observer

The hierarchical structure of the brain presented here suggests that rather than a recurrent loop (Hofstadter's strange loop) giving rise to the ‘I’ in my mind, that there is something like an ultimate observer that also acts as a very long time-scale coordinator, a strategic planner that is also constructing an extended model of the self which is the basis for the sense of ‘I.’ However I think Hofstadter is also right! In my next attempt to try to understand this phenomenon of consciousness I will explore how language supports the reentrant process of the self talking to the self, narrating the autobiography of self as it develops. That autobiography necessarily includes the narrative of the environment experienced as well as an interpretation of the self and its reaction to the environment (as well as to itself). In this sense I am a strange loop that results from an evolved hierarchy of cybernetic controls.

I am also interested in the way in which we empathize with others by creating strange loops that allow us to vaguely be another person. You are a strange loop that I can kind of understand.

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References

Damasio, Antonio (1994). Descartes' Error: Emotion, Reason, and the Human Brain, HarperCollins Publisher, New York.

Damasio, Antonio (2000). The Feeling of What Happens, Mariner Books, New York.

Fuster, Joaquín (1999). Memory in the Cerebral Cortex, The MIT Press, Cambridge MA.

Hofstadter, Douglas (2007). I Am a Strange Loop, Basic Books, New York.

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Footnotes

[1]. A model is a dynamic map, that is a mapping from inputs to outputs that changes with the incorporation of new knowledge and feedback from experience results.

[2]. Actually a lowly octopus can do this trick even when there is a cork in the bottle. However, the work that the octopus does appears to be largely trial and error efforts rather than reasoned based on prior experience. Octopi have some longer-term memory retention in that if they are presented with the same problem a few hours later, their time to completion goes down. But several days later they are back at trial and error as if they had forgotten the prior lesson. And, they had. Contrast that with a crow who upon discovering a method for getting a food morsel out of a container, will retain the memory for months, if not years.

Convergence

The Multiple Threads of My Interests

The last several months have been really exciting for me. The book project is wrapping up and we should be getting the final manuscript draft to the publisher in early June. But several other areas in which I have been working are beginning to come together, to converge, as it were, in a grand synthesis. I must admit I have been startled by what is happening. I think, in part this is due to my stopping my obsession with how the world is falling apart due to human stupidity and going back to my roots in research in systems science. In any case the multiple threads of my interests are starting to weave together in what is, to me, a profound tapestry. I will try to explain.

Back in Feb. 2009 I wrote a blog post inspired by an e-mail question from a reader. I called it “Subjects of Interest.” The reader was puzzled about my penchant for writing about so many seemingly disparate topics such as energy, brains, and economics. I tried to show that these subjects are actually all interrelated and form a larger scope system; that I had used my understanding of systems science to successfully explore each subject from that perspective.

Over the years that I have been writing Question Everything I have delved into a fair number of subjects that were either explicitly systems oriented, or implicitly so. Here is a list of the topics in which I have done some pretty active exploration.

• Brain Science in general, but especially the functions of the prefrontal cortex in consciousness and sapience
• Information/knowledge theory and hierarchical cybernetics
• Auto-organization, emergence, and evolution (esp. the origin of life problem)
• System dynamics and approaches to modeling systems with a new process-based semantics
• Computation (obviously)
• Artificial Autonomous Agents (robots) using brain-like control systems
• Energy flows (as in auto-organization, etc. above), esp. in biology and economics

What ties these all together is Systems Science (my textbook will show this). Up until just recently, however, I have pursued each somewhat independently from the other even while intuiting that somehow they were all part of a larger whole. Now, it seems, my intuition is starting to take more shape in my mind. A recent insight gotten from working on a research project with the artificial agent brain showed me how these all come together, how they can all be integrated, unified, into a single conceptual framework - a system.

In future blogs I will outline how I see this coming about. Right now I will just provide an overview and mention some of the ways to bring it to fruition.

The Brain is a Universal System Model Building and Simulation Machine

For several years I have been working on the design of a new modeling language meant to upgrade what is known as system dynamics, originally developed by Jay Forrester at MIT (also see Donella Meadows wonderful book, Thinking in Systems). Forrester's language relies on a semantics called “stocks, flows, and controls.” It is true that all dynamic behavior of a system can be simulated by developing a stock and flow model such as in Figure 1 below. The changes in flow rates and stock levels over time constitute the dynamics. These models are discrete time-based and simulated by repetitively computing the state variables at each time tick. Graphs of the output data then show the dynamic behavior of the system as a whole.

 

Figure 1. System dynamics (SD) modeling has been based on the use of stocks, flows, and controls as very abstract concepts. This shows the basic semantics of the SD languages. The way the component pieces hook up is the language syntax.

 

For me this kind of abstraction was useful for many kinds of “simpler” systems. But when I started trying to build more complex system models involving details of energy, matter, and message (information) flows the lack of specificity in flow designation started to become a problem. A flow of energy and a flow of material (not to mention messages) are subject to some different laws. For one, the Second Law of Thermodynamics requires that with every conversion of energy flow there is an unavoidable loss to waste heat of some of the energy, i.e. less work can be accomplished downstream of the conversion. Material flow is more constrained by the conservation principle. It often takes more energy to remove waste materials on top of this. I was unsatisfied with the treatment of messages, only seen in the thin arrows (called “influence arrows,” which represent the flow of information that affects controls (the valves in the figure).

Lastly, and very importantly, I wanted to be able to abstract all of these flows, stocks, and messages into an object called a “process.” What we see in systems are objects that take inputs and processes them into outputs, products and wastes. The products are generally used by some other process which is what gives the output value and becomes the raison d'être for the supplying process. The abstraction (in the sense of hiding all of the details of a system) would allow the modeler to combine multiple processes into meta-systems. In that way one can construct increasingly complex systems from simpler subsystems. I will provide an overview of this in a future blog.

The limitations of system dynamics semantics definitely showed themselves when I attempted to model a neuron and its synapses using it. My first neural/synapse models based on system dynamics were a good exercise and provided many useful insights, but I found the restricted semantics difficult. I ended up developing the model in the ‘old’ way — I wrote it in C. Even so, the experience with DYNAMO and system dynamic left me feeling that with a little more semantic support a language that allowed the creation of complex dynamic models would be a great “project”. I put it on the back burner because my interest in neural systems as a better approach to artificial intelligence had been piqued. For the next many years I concentrated on developing a more deeply biologically inspired model of a neuron with particular focus on the multi-time domain dynamics of synapses and their plasticity, which I had become convinced was the key to a really efficacious method for encoding memory engrams.

Fast forward from the mid-80's to about five years ago. When I had moved from Western Washington University in 2001, where I was making progress on the “Adaptrode” synapse model, using it in neural networks that controlled the behavior of a mobile robot, to the University of Washington Tacoma, where the hoped for support never materialized, my robot experiments came to a screeching halt. As a result I started casting about for something else to do research in. A few false starts later I went back to the system dynamic modeling language and started to coalesce my ideas into some concrete approaches.

As part of my desperate search for a new research arena, and hoping it might have some relation to my previous work, I had “stumbled” into the psychology of wisdom. I had also been studying the growing threats from global warming, population overshoot, etc.; all of the problems that beset mankind and threatened its very existence. In the psychology of wisdom I found a clue. The reason humans were consistently making stupid mistakes and had adopted a completely fallacious ideology (capitalism, profits for their own sake, and growth) is that they lacked the wisdom to make good judgements and hence good decision. Somewhere along the line my interest in brains and behavior along with this insight from psychology led me to a much deeper investigation of brain functions and their evolution to seek explanations for the human condition.

About the same time my curiosity about the state of our energy systems, namely the concept of “peak oil” was starting to drag me into a deeper study of that subject, and what I found made me once and for all realize that humanity was doomed by sheer lack of sapience. All fossil fuels are clearly, unambiguously finite resources that if you extract and use at increasing rates will run out sooner or later. Moreover the supposed substitutes (neoclassical economists insist there are always substitutes when the price gets too high), alternatives such as wind and solar, were highly suspect in terms of their capacities to provide the same level of power that our societies had grown accustomed to. I started using my evolving modeling language to try and model the net energy production of photovoltaic generation given that the energy inputs into the process of producing the cells and installing them seemed to me to be excessive. Net energy is all that counts in system dynamics and my preliminary attempts convinced me that chasing these alternatives to keep society going with business as usual was a fool's errand. I discovered the work of Charles Hall at SUNY-ESF on ‘energy return on energy invested’ (EROI) and given the deep implications for humanity, if my model was giving reasonable answers, I decided to study this phenomenon much more closely. I had a sabbatical leave coming up so I decided to go to SUNY and study EROI with Hall. My objective was to understand the math better, and to see if my new process-based language would be able to produce viable models of energy systems.

Long-time readers know the rest. What I found out in this background research settled matters in my mind once and for all. The world of human societies was doomed to collapse (while at SUNY I met and struck up a friendship with Joe Tainter, who had penned the infamous The Collapse of Complex Societies. Joe had been working on the thesis that collapse of prior civilizations had been greatly influenced by what he described as the declining marginal returns on complexity; that being the result of societies trying to solve problems, the solutions then leading to more problems. With his association with Hall, et. al., Tainter had come to see that the energy flow through the society was related to the complexity issue so he came to recognize that complexity can only increase and succeed if there is adequate energy flow to support it. The Romans, for example, ran out of energy and could no longer support their complex infrastructure (to put it simply).

After returning from SUNY I was inspired to increase my efforts on the modeling language project. I've had several graduate and undergraduate students working on bits and pieces but the whole concept is, itself, rather complex and requires many pieces working together. We've made some progress, but not enough to go ask for money yet.

Meanwhile I had all but forgotten the neuron modeling as I pursued these other lines of interest, The seeming inability of the NN community to understand my models had more or less left me cold for struggling with pursuing the concepts furter. Then, two years ago, roughly, I came across a research paper that signaled something profound. It seems that in the years I had been away from neural network research a fair number of researchers had discovered the problem that I had tried to articulate to the neural network community without much success back in the early '90s and had been working on with my Adaptrode model; that of learning and forgetting non-stationary relations. The Adaptrode works by encoding memory traces in multiple time domains (i.e., real-time, short-, intermediate-, and long-term traces). In a future blog I will provide more, non-technical details about how the Adaptrode model solves some pretty serious problems in memory trace encoding in the real world.

With that kick I realized I needed to get back in that game. I had the solution to the problem and now that the community was paying attention I might actually be able to make some progress. For the past two years I have been steadily pushing my previous work to incorporate a number of new ideas regarding how to actually simulate a brain of greater complexity than that of a ‘moronic snail’, namely, how to construct a neocortex structure to do much more advanced processing than I had accomplished previously. This was greatly accelerated by reading Jeff Hawkins' amazing book, On Intelligence. Hawkins had independently hit on some of the same principles I had developed in my research years before, which gave me confidence that I had been on the right track. I've revived that research agenda and have several graduate students starting to rebuild my simulation software.

The cerebral cortex (neocortex in mammals) is an amazing structure for capturing causal relations at multiple scales of space and time. It literally is a machine for constructing complex models of the systems it encounters and using those models to anticipate the future. Hawkins and many neuroscientists studying the functions of areas of the cortex in behavior and thinking have all come to very similar conclusions. As yet, however, I have not seen an explicit discussion of the role of multiple-time domain encoding in how these models are constructed and validated (i.e. committed to long-term memory).

Realization

Within the last several months realization that I had been working on the exact same concept but under different guises all along dawned on me. Actually I have to confess it came to me during a lucid dream one night! I woke up realizing that my modeling language, my brain model, my attempts at modeling systems energy flows, and my grasp of higher brain functions were actually all one and the same. If I could successfully build a deep model of a brain (especially the neocortex with a human-like architecture) that simulator would do implicitly what I had been trying to do explicitly with a modeling language. I would be able to let such a device ‘learn’ the world — that is, construct a model of the world from experience. It would be able to simulate the world it had learned to project anticipatory scenarios, having the same efficacy as humans. And maybe more so.

It is still unclear to me what value it might have to achieve a breakthrough at this late date. The world of human civilization based on extreme power is coming to an end sooner than we previously thought possible. The latest news on global warming and climate change indicates that the major impacts from this phenomenon are already underway and will accelerate in the years to come. So solving the problem of emulating natural intelligence in machines may simply be coming too late to be very helpful. Even so, my attitude has always been one of curiosity and discovery. As selfish as that may be, I have been motivated by an incredible need to understand things. Some time back I thought that was because I had the conceit to believe if I understood the way the world worked I could do something to correct the mistakes. When I was younger and naive that seemed like a reasonable thing to think. Now that I am older, recognize the foibles of humanity, and my own lackings, I realize that it doesn't matter what I do. My contributions, if any, will not change the course of our fate. Even so, I am still intensely curious. So I will continue to research the subject. I am able to see how systems science, modeling ‘language’, energy flow, evolution, and everything come together in the way the brain works and that will be my focus from here on. I will try to outline these disparate threads in future posts, and show how they all come together in a single consistent understanding.

Wish me luck.

News Release

Scientists Find a 'Hole' in Most Human Brains

I thought I would share this with readers. I have been busy working with some neuroscientists to test a hypothesis regarding the lack of sapience in the majority of human beings. This is a pre-release version, which you should be reading about in the press soon.

Seattle Washington, March 31, 2014.

Two neuroscientists at the University of Washington Medical School and a computer scientist from UW Tacoma have released results from a collaborative study of the brain that should cause quite a stir in brain science. Neuroscientists Drs. Mario Brothers and Gloria Swansong and computer scientist Dr. George Mobus have presented data that shows an anomalous situation in a brain area believed to be associated with higher judgment facilities. This anomaly — actually a seeming absence of critical neural tissue — was found in the vast majority of patients examined using functional magnetic resonance imaging (fMRI). The patients were being treated for other neurological problems not directly involving the region.

Drs. Brothers and Swansong were following up on a theory first proposed by Mobus that could actually explain a large number of puzzling problems with human behavior and thinking. Mobus' theory held that humans had undergone a prodigious evolutionary expansion in the region in question, the fronto-polar patch designated as Brodmann area 10 (BA10) — a small patch of specialized neural tissues right behind the eyebrows — and that the rapid expansion resulted in a loss of critical functions in this patch. He developed computer models that suggested that at the same time that humans had evolved super intelligence they lost their ability to make good decisions regarding long-term issues. The anomaly shows up as a small 'hole' in the center of BA10 where normally one expects to find densely packed neurons.

In 2012, Dr. Brothers had developed a method for measuring the efficacy of judgments made by people and had started mapping the brain regions involved in making such judgments. He started noticing a pattern of remarkably poor judgment in the majority of subjects, results he reported in Human Brain, a prestigious journal covering that subject. At the time, his colleague at the medical school, Dr. Swansong, had also been trying to localize brain regions involved in solving complex problems. She had noted that the fronto-polar region of the prefrontal cortex was explicitly not being engaged in subjects who were nonetheless able to solve complex problems. This was puzzling since it was assumed that higher-order judgments would play a part in intelligence. The two collaborated to develop an explanation for what their separate researches were suggesting. Their integrated methodology has been called the “stupidometer” because of the way it reveals how most humans make really poor decisions. They came across Mobus' theory and immediately began to suspect there might be something to it.

Now the scientists have gathered substantial data to show that the average human being is incapable of making higher-order judgments because of this apparent hole in their brains. Further evidence of humans choosing to solve problems that end up causing even greater negative consequences has been gathered.

“This could explain why we humans decided to develop industrial machines running on fossil fuels to exploit natural resources more rapidly even when the fact that such fuels were finite in scope and the burning of carbon produces the greenhouse gas carbon dioxide,” said Dr. Brothers. “I've often wondered how humans could believe that economic and population growth could go on for infinity when all of the science we know tells us not,” added Dr. Swansong. “Now I think we know,” she added, “Most people seem to have this ‘black hole’ in their brains where good judgments simply disappear through the event horizon.”

Not all people were found to have such holes. Out of two hundred patients tested, one proved to not have such a hole, or it may have been exceedingly small by comparison to the size of BA10. That patient's BA10 was found to be engaged while s/he was working on solving a difficult problem and s/he also scored extremely high on the judgment scale. Both neuroscientists later became curious about their own brains and subjected themselves to testing. Both were relieved to find that their holes were similarly very small or non-existing. No word on Dr. Mobus' condition.

The three researchers' paper has been submitted to Human Brain and is currently under peer review.