Emergence of Mind is an introduction to Emergent Cognition, a project exploring ideas related to an emergent systems perspective of cognition:

  • How do simple interactions at one scale effect relatively complex interactions at another scale?
  • Just as matter emerges from different scales of physical interactions, what if mind emerges from different scales of cognitive interactions?
  • How might a theoretical framework inform physical, experiential, mental, and spiritual design for transformative learning in individuals, groups, and society?

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Reimagining the Mind
The story of what it means to be human is fundamentally a story about the search for meaning. But what if our ability to find a sense of meaning arises from our ability to sense the world around us? Just as matter emerges from distinct levels of physical interactions — with atoms giving rise to molecules giving rise to cells — perhaps the mind emerges from distinct levels of cognitive interactions. Informed by Uri Wilensky and Mitchel Resnick’s work on emergent levels; Andrew Ortony, Donald Norman, and William Revelle’s work related to levels of cognitive processing; and Terrence Deacon’s work involving the levels of representation, this perspective of cognition reimagines the mind as a universe of emergent complexity.

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Human beings have a wonderful imagination. Gazing up at the night sky, we can envision ourselves on a planet that’s spinning through a solar system, among billions of other solar systems spinning through a galaxy, among billions of other galaxies spinning through space. We are able to contemplate the complexity of the universe, and we’re aware that there is more out there than humanity may ever discover or even be able to comprehend.

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That complexity also exists within us. As living organisms, we have bodies, and those bodies have cells, and those cells have molecules, and those molecules have atoms, and those atoms have sub-atomic particles. All of which is to say that being alive is no simple matter.

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In the midst of all this complexity, we know that we are more than the sum of our physical parts. But what is that something more? Why are we aware of it? How has it enabled us to move, sense, feel, and think in the world? Can it really be a product of the chemical signals, neural activity, and computational processes of the brain?

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These questions address some of the biggest mysteries in the universe. Even with all the amazing advancements in science and technology, it’s possible we will never get all the answers. However, we do know that whatever answers we find will depend on what questions we choose ask, where we decide to look, which doors we select to open.

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“Mind” is an ambiguous reference to the processes of cognition, awareness, and consciousness. A lot of modern research about the mind focuses on cognition as a function of the brain. The underlying question, though, is how mental awareness emerges from the physical awareness. We already know that our physical bodies are manifestations of complex patterns and levels of interaction among forms of matter. What if cognition involves similar patterns and levels of interaction among forms of mind?

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From living organisms to cells to atoms, more complex forms of matter emerge from less complex forms of matter. What if we reframe the question of cognition by asking how we might understand it in terms of more complex forms of mind emerging from less complex forms of mind? To explore this question, we need a generalizable description of the emergence of complex systems that we can then use as a template for describing an emergent systems perspective of cognition. But before we start exploring, we need to orient ourselves relative to current perspectives of cognition.

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Once Upon a Theory

The stories we tell and how we tell them say a lot about us. In many ways, it is the same with theories. What might our theories of cognition tell us about how we’ve been thinking about thinking?

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These days, cognition is generally used to refer to the activities of the brain and central nervous system which enable us to think, feel, sense, and act in the world. This definition can be modified to include ecological perspectives in which our bodies, relationships, and environments are also considered to be part of cognition. Even as we explore different perspectives, however, the brain remains at the center of most theories about the basic mechanics of the human mind.

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The thing about theories of cognition is that — not unlike the blind men and that poor, manhandled elephant — they all involve different ways of explaining the same phenomena. In this regard, the conflicts among them have more to do with perception and interpretation than objective reality. Even though some are more accurate than others, few of them are completely wrong.

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These differences in perspective also explain some of the problems with trying to describe how various theories relate to each other. It is perhaps more useful to characterize theories by the sorts of questions they are looking into rather than the answers they are finding. For example, many theories of cognition emphasize one of the following questions:

  • What is the role of symbolic systems in cognition?
  • What is the role of social relationships in cognition?
  • What is the role of physical and social environments in cognition?
  • What is the role of the body in cognition?

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All of these perspectives involve big, important questions. But could an integrated perspective help us go beyond these individual points of view to see a bigger picture? It is a different, but no less important inquiry into the study of cognition as well as our understanding of it.

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Many of our most basic ideas about how the world works have been transformed by technological revolutions. The scientific method gave rise to the study of cause and effect; manufacturing gave rise to the study of interacting parts; computers gave rise to the study of network systems. Each of these major advances in tools and techniques embodied a signature perspective that eventually proliferated throughout society and pollinated our collective ways of thinking.

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Whether the topic is cognition or something else, the kinds of answers we find are a function of the types of question we ask; the types of questions we ask reflect the ways we think; the ways we think are informed by the cultures of the social groups in which we live; and the social groups we live in are influenced by the tools and technologies embedded into their everyday lives.

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Here’s a trick question: What do you see when you look at a leaf? When you look at it with just your eyes, you might see it as part of a tree or a forest or a floral arrangement. Or maybe, it’s just a leaf.

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What if we used a microscope to look at the leaf under different levels of magnification? Then we’d be able to look at the leaf and see a whole, then zoom in a level and discover that it is simultaneously composed of interacting parts called cells. If we were able to look at one of those cells and zoom in another level, we would discover that it is also simultaneously composed of its own interacting parts called molecules. And so on and so on. The more we zoom in, the more there is to see.

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Perspective isn’t just about what we look at, it’s also about what we see. Even if seeing isn’t always believing, technology enables us to see things differently and subsequently to conceive of things beyond what we can perceive with our own eyes. As a sort of conceptual technology, theoretical frameworks can help us see in new ways too.

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Simplifying Complexity
It’s been said that “Everything is simpler than you can imagine and more complex than you can comprehend.” As one might guess, emergent complexity is rather complex. Nevertheless, with a little imagination, there are simple ways to organize how we think about it.

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Emergent complexity, or emergence, is a term typically used to describe the way in which relatively simple interactions can have disproportionately complex results. It involves a kind of grassroots, bottom-up organization that helps explain why we find so much order in a universe that lacks any executive, top-down organization. Everything from superconductivity to ant colonies and other everyday phenomenona are considered to be examples of emergence.

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Yet all of these examples of emergence involve very different sorts of interactions. The only way to create a useful framework for describing emergence would require finding a common thread among them. Fortunately, that’s what Wilensky and Resnick (1999) did when they explained the significance of emergent levels to the study of complexity.

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Of course, not all levels are created equally. Emergent levels are informed by specific dynamic, part-whole, and cause and effect relationships. If we organize these relationships into dimensions of patterns and levels of interaction, they provide the basis for an emergent systems framework.

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The Heart of the Matter
Everything we can see, hear, smell, taste, and touch is the result of interactions between our bodies and the physical world. Any relationship we have with other people involves some kind of social interaction with them. History is basically an ongoing story of our collective social interactions. The evolution of every species of life on the planet is the result of long-term, large-scale biological interactions. From grains of sands to galaxies of stars, everything composed of physical matter is the product of emergent interaction. We could even say that everything IS an interaction.

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It’s mind-blowing just trying to think about all that interaction. Fortunately for our minds, our awareness of interactions is limited. The world is full of interactions we don’t perceive because we lack the necessary senses. Even the senses we do have are only sensitive enough to perceive relatively small ranges of interaction. Our direct experiences are poor representations of the wealth of interaction that is always happening all around us.

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We don’t need to get too philosophical about any of this, but we do want to put things in the right context. In a reality that is incomprehensibly interactive, even the things that seem simple are nonetheless infinitely complex. Using simplified terms like patterns and levels and systems requires us to be mindful that these words are deceptively small containers with infinite space inside.

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Part of the Process
Emergence is often related to the idea that the whole is greater than the sum of its parts. This idea is true in many ways, but there are also different ways of understanding what it means for one thing to be part of another. With emergence, it is necessary to change how we generally think about part-whole relationships.

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In our everyday lives, we use the noun, “part,” to refer to a wide range of part-whole relationships. A slice is part of a pie. The filling can be part of a pie as well. Even its ingredients could be considered part of a pie. Usually, though, the best part of a pie is how it tastes.

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To understand emergence, we need to think of parts in a specific way. Normally, when we think of part-whole relationships, we’re imagining some sort of jigsaw puzzle. The parts are like puzzle pieces we put together to form the whole picture. Emergence is a special kind of puzzle in which the pieces aren’t physical shapes but rather forms of interaction.

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Parts can be organized into three patterns of interaction: independent, dependent, and interdependent. What independent interactions are individual parts involved in? What dependent interactions are happening between parts? What interdependent interactions are happening among all of the parts? These patterns are the puzzle pieces from which a picture emerges.

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Patterns help us organize interactions. Just as parts can be integrated into wholes, patterns of interaction can be integrated into more complex patterns of interaction. In case you hadn’t noticed, that’s a lot of interaction, which tends to get messy both literally and figuratively. That’s where levels come in.

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The Cause in the Effect
In emergence, the part-whole relationship is one of cause and effect. Parts are the cause and wholes are their effects. Levels are a way of organizing these cause and effect relationships among interactions.

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Most examples of cause and effect are described in terms of linear or sequentially ordered steps of time. In these examples, cause and effect happen one after the other. To say that A causes B implies that A happened first and then B happened next. The first car suddenly slows down, and the effect is that the second car crashes into the first. It’s a simple and literally straightforward perspective of cause and effect.

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Instead of a strictly linear view of causality, emergence involves a type of cause and effect that happens synchronously but at different levels. These levels differentiate between the scale of the parts and the scale of the whole. Although we may only perceive the resulting changes over time, the causes and their effects aren’t related through time, they’re related through scale / space / size. What happens at the smaller scale of the parts (A) simultaneously causes something to come into being on the bigger scale of the whole (B). As hundreds of individual cars slow down, they collectively cause a traffic jam.

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Linear / sequential cause and effect is like listening to the sound of an individual instrument. We hear the music as one note after another. Multi-scale / synchronous cause and effect is like listening to the simultaneous sounds of multiple instruments. There’s a linear progression, but the music we hear emerges all at once from the interactions of notes. Even though the music would not exist without the individual sounds, it also exhibits qualities or characteristics or a life of its own at a level beyond them.

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PARTING THOUGHTSimg_1112With both the traffic and music examples, it’s important to remember that the focus of emergence is on interaction. In the traffic example, the part and whole relationship isn’t cars and traffic, it’s cars-slowing-down and traffic. Similarly, in the music example, the parts aren’t the instruments, they’re the instruments-making-sounds. Even going back to our pie example, how the ingredients make a pie is not an example of emergence, but the behavior of molecules (from the ingredients) manifesting as a pie is.

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From Little Acorns
For our working definition, emergence is a dynamic, multi-scale process in which interactions-as-parts cause/effect new and qualitatively different wholes that include but transcend the parts themselves. That’s it, in a nutshell.

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Patterns are a way of looking at the independent, dependent, and interdependent interactions which function as the parts. Levels are a way of looking at the various scales of parts and wholes. In trying to conceptualize the framework, it can be helpful — although somewhat misleading — to imagine patterns and levels as horizontal and vertical dimensions of interaction, respectively.

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A NEW FRAME OF MINDimg_1120We now have a theoretical framework for describing emergent systems. Its key features — interaction, patterns, and levels — illustrate the basics of an emergent systems perspective. They are our essential tools for outlining an emergent cognition framework.

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Laying the Groundwork
How do we apply an emergent systems perspective to cognition? As the basis for understanding emergence, levels are the main organizational feature of the emergent systems framework. They’re a way of zooming into phenomena to study patterns and interactions at different scales. With levels, we can start with an overview of cognition and work our way in.

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The idea of levels in models of the brain, emotions, attitudes, etc. is nothing new. Although most of these models do not differentiate between emergent and other kinds of levels, they can still provide a good picture of the territory we are trying to explore.

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Many models in both academic work and popular culture involve three levels of cognition. The most well-known example is probably MacLean’s triune brain, which maps the evolution of various brain structures to certain types of brain functions. Although not considered scientifically valid as an explanation of how the brain actually works, it is a helpful approximation for the organization of cognitive processes and structures.

  • Reptilian Complex: instinctual behaviors, “lizard brain”
  • Limbic System: pro-social behaviors, “mammalian brain”
  • Neocortex: reflective behaviors, “human brain”

Truine Brain | Wikipedia
Rule of Three | Wikipedia

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A similar organization is evident in Ortony, Norman, and Revelle’s model of emotional affect in the context of reactive, routine, and reflective levels of cognition, which is also the basis of Norman’s model of visceral, behavioral, and reflective levels of emotional design. This work, however, doesn’t involve mapping brain structures to brain functions. Instead, the researchers were considering how different levels of cognition represent various aspects of the same information (emotion).

  • Reactive / Visceral: proto-affect; emotional responses based on instinct, physical sensation
  • Routine / Behavioral: affect; emotional responses based on habits, learned behaviors
  • Reflective: emotion; emotional responses based on thought, reasoning

Affect and Proto-Affect in Effective Functioning | Ortony, Normal & Revelle
Three Levels of Processing: Visceral, Behavioral, and Reflective | Norman

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Another useful perspective on levels of cognition involves how we understand reference, or the relationship between what is being communicated (the signifier) and how it is being communicated (the signified). For example, an image of a dog, a paw print, and the letters d-o-g are all signifiers of the idea of dogs. However, the first bears a physical resemblance to a real dog, the second is an intuitive reminder of real dogs, and the third is an abstract form assigned to refer to a dog. In his work on sign theory, Peirce refers to these three types of signs as icons, indices, and symbols.

  • Icon: signifier refers to signified based on physical resemblance (image of a dog and dogs)
  • Index: signifier refers to signified based on co-occurrences (a paw print and dogs)
  • Symbol: signifier refers to signified based on assignment (word “dog” and dogs)

Peirce’s Theory of Signs | Stanford Encyclopedia of Philosophy

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Using sign theory, Deacon models how language evolves from the iconic, indexical, and symbolic reference represented by signs. Rather than looking at various levels of cognitive processing, Deacon focuses on various levels of information (reference) as a function of cognition. Although he doesn’t specifically mention emergent levels, he describes how iconic reference gives rise to indexical reference which gives rise to symbolic reference.

  • Iconic reference: unconscious substitution of signifier (image of a dog) for signified (dogs)
  • Indexical reference: remembered mapping of signifier (paw prints) to signified (dogs)
  • Symbolic reference: learned substitution of signifier (the word “dog”) for signified (dogs) and mapping to other signs (references to / of “dog” and dogs)

The Symbolic Species: Symbols Aren’t Simple | Deacon

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How do these models inform each other? Not only do they focus on different topics, but they also represent different cause and effect relationships, from direct A=B mappings, to linear A-to-B-to-C progressions, to nested (((A) B) C) evolutions. Clearly the models represent specific points of view, but how might they collectively contribute to our overall picture of levels and cognition?

  • Iconic reference: unconscious substitutions based on physical resemblance between signifier and signified
  • Reactive / Visceral: responses based on instinct, physical sensation
  • Reptilian Complex: instinctive behavior, “lizard brain”
  • Indexical reference: remembered mappings based on co-occurrence of signifier and signified
  • Routine / Behavioral: responses based on habits, learned behavior
  • Limbic System: pro-social behavior, “mammalian brain”
  • Symbolic reference: learned networks of substitution and mapping based on assignment of signifier to signified
  • Reflective: responses based on thought, reasoning
  • Neocortex: reflective behavior, “human brain”

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Variations on a Theme

Despite their differences, models involving levels of brain organization, emotion, signs, and reference suggest consistent underlying themes for each level of cognition. As levels of an emergent system, each theme should relate to a type of interaction. Based on the identified themes, we can organize these interactions into sensory, intuitive, and abstract.

Sensory interactions: instinctive, body, iconic

  • Iconic reference: unconscious substitutions based on physical resemblance between signifier and signified
  • Reactive / Visceral: responses based on instinct, physical sensation
  • Reptilian Complex: instinctive behavior, “lizard brain”

Intuitive interactions: habitual, memory, indexical

  • Indexical reference: remembered mappings based on co-occurrence of signifier and signified
  • Routine / Behavioral: responses based on habits, memory, learned behavior
  • Limbic System: pro-social behavior, “mammalian brain”

Abstract interactions: reflective, thought / language, symbolic

  • Symbolic reference: learned networks of substitution and mapping based on assignment of signifier to signified
  • Reflective: responses based on thought, language, reasoning
  • Neocortex: reflective behavior, “human brain”

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Each level of interaction gives rise to a type of representation. These representations are higher-level integrations of the patterns of interactions from which they emerge. They are similar to the traffic emerging from the interactions of cars slowing down, the music emerging from the interactions of sounds from instruments, the pie emerging from the interactions of the molecules of its ingredients. As derivatives of the level they represent, we will refer to these representations as perceptions, associations, and conceptions.

Perception: integrated representation of sensory-level patterns

  • Sensory interactions: instinctive, body, iconic
  • Iconic reference: unconscious substitutions based on physical resemblance between signifier and signified
  • Reactive / Visceral: responses based on instinct, physical sensation
  • Reptilian Complex: instinctive behavior, “lizard brain”

Association: integrated representation of intuitive-level patterns

  • Intuitive interactions: habitual, memory, indexical
  • Indexical reference: remembered mappings based on co-occurrence of signifier and signified
  • Routine / Behavioral: responses based on habits, memory, learned behavior
  • Limbic System: pro-social behavior, “mammalian brain”

Conception: integrated representation of abstract-level patterns

  • Abstract interactions: reflective, thought / language, symbolic
  • Symbolic reference: learned networks of substitution and mapping based on assignment of signifier to signified
  • Reflective: responses based on thought, language, reasoning
  • Neocortex: reflective behavior, “human brain”

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There are all sorts of ways to characterize levels of cognition. Comparing existing models with levels of cognition-related topics gives us an overview of prominent themes. Our description of cognitive levels is a summary of these themes as types of interaction processing.

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The first level of interaction processing is sensory. It involves the interactions of our bodily sensations. Everything we physically experience in the world is processed through this level into perceptions. This is the information we attribute to the body — our ability to see, hear, smell, taste, touch, and move.

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The second level is intuitive. At this level, we process interactions among perceptions over time and intuitively learn how various perceptions are associated with each other. This information is most often attributed to the heart — our pre-verbal ability to understand relationships.

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At the third level, there is the processing of abstract interaction. This processing depends on words to represent associative interactions, giving form to conceptions which we can then use and manipulate in the physical world. We generally attribute this information to the mind — our ability to use words to communicate with each other but also with ourselves via our own verbalized thoughts.

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Photo Credit: jean-louis zimmermann

We can imagine a fourth level as well. However, it is different from the other three in that it does not necessarily give rise to a fully integrated representation. This is a narrative level at which we process the interactions of conceptions into interpretations. It is the information we may attribute to the spirit — our ability to create context and meaning.

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By themselves, emergent cognition’s sensory, intuitive, abstract, and narrative levels simply refer to types of interaction. Beyond the description of individual levels, there is still the question of how the interactions of perceptions give rise to associations, and the interactions of associations give rise to conceptions. To address this question, we’ll need a better understanding of the nature of representation.

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Interpreting the Signs
If cognition is essentially a form of communication, then representations are essentially forms of reference like the signs described by Peirce and Deacon. In his model of signs and reference, Deacon illustrates how one form of reference evolves into another. Using a modified version of that model, we can describe the relationships among types of reference, which can then inform our description of the relationships among types of representation.

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Let’s say you know someone named Eduardo. I can show you a picture that looks like Eduardo, play a recording that sounds like Eduardo, or even give you a whiff of something that smells like Eduardo. Any of these may act as a substitute sensory representation of the real Eduardo. The image, recording, and smell correspond to a visual, auditory, or olfactory embodiment of Eduardo’s physical presence. Even if Eduardo isn’t actually there, his physical presence is being mimicked through one of our senses and tricking us into thinking that he is. That’s iconic reference.

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Then there’s Maria. Let’s pretend Maria is your best friend. If I play Maria’s favorite song, show you Maria’s favorite outfit, or imitate Maria’s signature dance move, this will act as an associative representation of Maria. The song, outfit, and movements act as triggers that remind you of Maria. She could be a thousand miles away, but these triggers are so closely associated with Maria that you’ll practically expect to see her walk through the door at any minute. That’s indexical reference.

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Now let’s imagine that your idol has always been the historical figure, Galileo. Naturally, I feel compelled to tease you about this by repeatedly saying “Galileo”, writing “Galileo” on all your stuff, and even learning to spell “Galileo” in sign language. Your unconscious has learned that these auditory, written, and gestural perceptions are all versions of Galileo’s name — a word his mother decided to use to signify him as a person. So, just like with “apple,” when you hear, read, or see his name, there’s that somewhat confused part of your unconscious which acts like he’s there. Or at least, there in your mind. Nevermind that you haven’t ever actually met him. This index-as-icon transformation is a necessary but not sufficient condition for symbolic reference.

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After your unconscious has learned to directly map any physical perception of the word “Galileo” to your imagined perception of Galileo, it doesn’t stop there. Now, every time you have any audio, visual, or gestural perception of “Galileo,” your unconscious automatically has a “Galileo”-as-imagined-perception-of-Galileo moment. Subsequently, its next trick involves processing the relationships from both word and referent (associations, perceptions, and all) into one integrated representation of “Galileo.” That’s symbolic reference.

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At some point in this imaginary scenario, I decide to stop teasing you by mindlessly repeating his name. Instead, I might use “Galileo” while explaining what a big nerd you are, or in the text I send you (about what a big nerd you are), or perhaps during my interpretative dance performance of Galileo’s life story, which just so happens to feature the song American Rhapsody by Queen (because it takes one to know one). In any of these contexts, you’re interpreting “Galileo” in relationship to everything else I’m saying, writing, or doing. That’s what we’re calling contextualized symbolic reference.

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By exploring types of reference, we begin to get an idea of how iconic reference relates to indexical reference and how both iconic and indexical reference relate to symbolic reference. This, in turn, gives us a starting point for exploring the relationships among forms of representation and the processes by which sensory interactions give rise to intuitive interactions and intuitive interactions give rise to abstract interactions.


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Icons, indexes, and symbols are forms of reference that exist in the physical world. Representations, on the other hand, are forms that only exist within a cognitive system. We could say that perceptions, associations, and conceptions are basically the icons, indexes, and symbols of cognition.

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Perceptions are the icons of cognitive representation. While iconic reference involves substituting and/or confusing the physical presence of Eduardo with something physically similar to him, perception involves substituting the physical world with the iconic representation of our experience of the physical world. The result is a kind of virtual reality that is literally all in your head. See that sunset? Well, you’re not actually seeing the sunset. You’re seeing the perception created by your brain processing sensory interactions between your eyes and the light coming from the sunset. It’s worth repeating: Everything you’re consciously aware of experiencing in the physical world is really just in your head. Sure, the real world exists (probably), but perception isn’t a direct interface with the real world, it is only a replication of it.

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IMG_1715.JPGAssociations are the indexes of cognitive representation. They are derived from the interactions of perceptions. After you see, hear, smell, taste, touch, or otherwise have a perception of one thing, you then intuitively expect to have a perception of something else. Associations will have different strengths depending on your experience. If you’ve only ever perceived red apples, you may more closely associate apples with the color red than, say, a normal person who is familiar with differently colored apples and whose mind isn’t completely blown by trying to imagine that an apple could ever possibly be green.

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Most associations are clearly differentiated. As in not fully integrated. As in your unconscious can tell one thing apart from another, and treats them as different perceptions. But words are special. With words, we learn to fully integrate the perception of the signifier (the word) and the signified (whatever the word refers to). Our unconscious no longer discriminates between the two and begins to treat them as if they are the same perception. So you’ll hear the sound of the word “apple” and part of your brain acts like it’s seeing a real apple. It’s as if “apple” has become an iconic substitution for the perception of apples.

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Conceptions are the symbols of cognitive representation. As a prerequisite, your physical perception of a word must be super-associated with an imagined perception of what the word signifies. Then, whenever you perceive that word, your unconscious integrates the associations and perceptions of both into a single representation or conception of the word. This is a dynamic process, so you may represent the same word differently each time you perceive it. Certainly, your understanding of the word changes, too, as you experience new and different perceptions and as you learn new and different associations. So you probably will not always think of Galileo quite the same way that you do now.

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Interpretations are the contextualized symbols of cognitive representation. This is when we process the interactions of multiple words-as-concepts (like “Galileo”). In addition to processing the words as perceptions and associations, your unconscious maps a constellation among the words-as-concept. Basically, your brain is integrating a network of relationships among all these words-as-perceptions, words-as-associations, and words-as-concepts into a sense of meaning.

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Icons, indexes, and symbols give us a reference point for describing the interaction processing by which sensations gives rise to perceptions, perceptions gives rise to associations, associations gives rise to conceptions, and conceptions gives rise to interpretations. This description also helps us understand how cognition functions as a kind of internal system of communication. This in turn is the basis of an emergent systems perspective of the relationships among body, sensing, sensation, and perception; memory, feeling, intuition, and association; words, thinking, abstraction, and conception; and language, understanding, narration, and interpretation.

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Emergence of Mind
The physical emergence of matter provides a template for imagining the cognitive emergence of mind. The same way that interactions of simple physical forms give rise to more complex physical forms, the interactions of simpler cognitive representations give rise to more complex cognitive representations. As embodied in the emergent systems framework, this type of emergence can be described in terms of patterns and levels of interaction.

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Cognition as an emergent system involves specific types of levels, patterns, and interactions. Instead of levels of matter (particles, atoms, molecules, etc), there are sensory, intuitive, abstract, and narrative levels. Instead of the laws of physics, there are patterns. Rather than focusing on naturally occurring interactions in the world, the focus is on interactions created, connected, and combined within a cognitive system.

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In both physical and cognitive emergence, patterns of interaction processing effect integrated representations. These representations are themselves interactions, but they function as individual forms at a higher level of processing. Emergent cognition involves perceptual, associative, conceptual, and interpretative forms of representation. Unlike physical representations, however, these cognitive representations only exist and interact within the cognitive system.

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Sensing, feeling, thinking, and understanding each involve different kinds of representation which are effected by different levels of processing. Yet all of them are derivatives of the same fundamental interactions. They reflect forms of meaning rooted in and rising out of our physical experiences in the world.

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Herein lie the essentials of an emergent cognition framework. It is a way of imagining how conception emerges from perception, thinking emerges from sensing, the mental emerges from the physical, mind emerges from body. From this perspective, we have a frame of reference for understanding cognition.

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What changes when we look at cognition through a lens that lets us zoom further out and closer in through multiple points of view? There are some interesting implications. Not so much in terms of what we know about cognition, but how we interpret what we know about cognition. At the very least, there is the hope that someday our lack of vision will no longer result in the cruel and unusual punishment of elephants, metaphorical or otherwise.