However, a significant part of human cognition is different from deliberate reasoning (Polanyi, 1966): We have little awareness of where our actions and thoughts "come from"; they emerge spontaneously in response to a situation or in the course of acting, speaking, writing; we do not always plan in advance what to say; we just speak; sometimes we even surprise ourselves with what we say, write, or do. Sometimes we plan what to do, but such plans are not as neatly laid out and thoroughly controlling of what we do as plans in descriptive cognitive models. Often we do not know how we accomplished something until we reflect afterwards on what we did.

Some everyday examples of our conceptual coordination are quite striking: We can imitate an accent without describing it theoretically; we can visually project events in our imagination (such as whether a spilled cup of coffee will reach the end of the table); and we find in many physical activities, as in dance, sports, and music, that words often get in the way. All of this points to cognitive structures and processes that are implicit, tacit, and organized on different sensory and temporal dimensions. Apparently such "steps" and actions are generated, generalized, and coordinated along different dimensions in the course of acting. When we consider the cognition of children and animals, who patently do not act by first describing their world and alternative behaviors, this point appears even stronger.

The view of knowledge as tacit and generative, rather than explicit and programmatically applied, implies that we need to seek alternative notions of representation—symbol structures and processes with different characteristics than those employed in descriptive cognitive models. Inspiration can be found in the neural network models of Edelman (1992) and Freeman (1991), related work in contextualist (Hoffman and Nead, 1983) and ecological psychology (Gibson, 1966), and in anthropology (Suchman, 1987; Lave, 1988). The right explanation is unlikely to be identical to today's best models, and some researchers do not offer alternatives to the descriptive approach, but in general these efforts point in the right direction.

Within the emerging understanding, often called "situated cognition" (Clancey, in press), there is room for abstraction. Indeed, it makes sense that tacit knowledge structures are abstract; this is part of their generative power. Hence, there is no contradiction between searching for new mechanisms that lie outside the realm of the descriptive models explored hitherto and the goal of explaining the higher-order intellectual accomplishments of human beings. On the contrary, one goal of situated cognition is to explain higher-order cognitive accomplishments, "abstract thought" and the like, in terms of tacit and implicit but generative processes.

In this paper, I argue that a confusion has developed in the scientific community because all kinds of concepts have been equated with descriptions, including equations, heuristic rules, semantic nets, and diagrams. "Symbolic reasoning" has been viewed as the foundation of all cognition, such that any sensory input can be mapped to descriptions by some form of encoding (Bickhard and Terveen, 1995), and all intelligent action requires and only depends on manipulation of descriptions of the world and behavior. Often other modalities of conceptualization (rhythm, accent, imagery, and gestures) are viewed as merely the input or output of such manipulations. I argue that the nature of conceptual coordination has been misconstrued by viewing verbal conceptualization as the landing place and controller of all thought. Hence "abstract thinking" has been misconstrued as being fundamentally verbal, and other modalities of abstraction, on which verbal thinking often depends, are inadequately understood.

In subsequent sections I provide an overview of distinctions I am making and ways they are sometimes misconceived. To illustrate the nature of conceptual coordination, I analyze two examples of neurological dysfunctions. I distinguish between conceptualization and descriptions, and suggest a neural perspective for understanding the distinction. Finally, I show how these ideas can help resolve debates about the rule-like nature of knowledge.

It is sufficient to think of symbols as strings of characters and of symbol structures as a type of data structure... The following are examples of symbols: Apple, Transistor-13, Running, Five, 3.14159. And the following are examples of symbol structures: (On Block1 Block2) (Plus 5 X) (Same-as (Father-of Pete) (Father-of (Brother-of Pete))). (Hayes-Roth et al., 1983, p. 61)

In particular, in improving and building on the descriptive cognitive modeling approach, situated cognition researchers are:
 

• not attempting to abolish the idea of abstraction, e.g., suggesting that it is a kind of illusion;

• not claiming that "transfer" of knowledge across situations is not possible or important (cf. Anderson et al., 1996);

• not claiming that parts of cognition are "non-representational" or "non-symbolic" (in a broad sense) (cf. Vera and Simon, 1993);

• Trying to highlight differences between what existing computer models capture and naturally-occurring cognition. For example, what is rejected is the transfer metaphor for explaining:

• ‡ how memory works (i.e., categorizations are generalized and recoordinated in use (Bransford et al., 1977; Iran-Nejad, 1987; Jenkins, 1974; Rosenfield, 1988; Schön, 1979) and

• ‡ how descriptive generalizations are applied (i.e., everyday design and policy interpretation typically requires reconceptualization, not using written rules as if they were recipes (Suchman, 1987; Wynn, 1991)).

• Focusing on non-linguistic aspects of human coordination, e.g., visualization, social relations, and rhythm. By hypothesis, symbolic reasoning and language depends on these (Edelman, 1992).

• Emphasizing the importance to psychology of understanding how the brain actually works, to the point of having an engineering specification that would enable replicating its functions for the broad range of human intelligence (Effken and Shaw, 1991; Freeman, 1991). For example, not all "symbol structures" in an animal's brain are entities for referring to the external world (Maturana and Varela, 1987).

The clarifications I provide here are important because what some researchers take for granted others might never have believed. For example, one cognitive psychologist wrote to me, "ëStorage' is only a metaphor; nobody in the symbolic cognition tradition thinks of it as actually storing something in a space, whatever that would mean." But one can easily find the opposing view throughout the AI literature. For example, Pylyshyn provided the following commentary at the 22nd Carnegie Symposium on Cognition:
 

The choice of both notation and architecture are central empirical issues in cognitive science, and for reasons that go right to the heart of the computational view of mind. It's true that in the physical sciences, theoretical notation is not an empirical issue. But in cognitive science our choice of notation is critical precisely because the theories claim that representations are written in the mind in the postulated notation: that at least some of the knowledge is explicitly represented and encoded in the notation proposed by the theory. The architecture is likewise important because the claim is that these are literally the operations that are applied to the representations.... In cognitive science, theories claim that the mind works the way the model does, complete with notation and architecture. What is sometimes not appreciated is that computational models are models of what literally goes on in the mind. (Pylyshyn, 1991, p. 221)

The theory posits a set of processes or mechanisms that produce the behavior of the thinking human. Thus the theory is reductionistic; it does not simply provide a set of relations or laws about behavior from which one can often conclude what behavior must be. (The elementary processes and their organization, of course, are not explained: reduction is always relative.) Thus, the theory purports to explain behavior—and not just to describe it, however parsimoniously. (We are aware that some would dispute such a distinction, viewing all causal explanations as simply descriptions.) (Newell and Simon, 1972, p. 9)

Consider for example Rebecca, whom Sacks characterizes as having two modes of being. The first, a mode of thought measured by formal testing, requiring pattern-seeing and problem solving, revealed her as defective, lacking basic human capability:
 

A poor thing...a multitude of apraxias and agnosias, a mass of sensorimotor impairments and breakdowns, limitations of intellectual schemata and concepts.... a mere mosaic of higher cortical functions...

She had done appallingly in the testing—which, in a sense, was designed, like all neurological and psychological testing, not merely to uncover, to bring out deficits, but to decompose her into functions and deficits. She had come apart, horribly, in formal testing... (Sacks, 1987, pp. 180-1)

Rebecca apparently experiences ways of seeing directly (without narrating her experience), and she can pattern herself after an ongoing concrete form in the environment in which she embeds her activity. She says, "I'm sort of like a living carpet. I need a pattern, a design, like you have on that carpet. I come apart, I unravel, unless there's a design."(pp. 184-5) She needs to be supplied a narrative structure, some pattern-rhythm to interact with directly in the environment. She can't compose scenes of her own conception, but she could be "composed by a natural scene," which presents itself to her as a dramatic unity, with aesthetic sense. Attempting to achieve coordinated action by her own spatial-temporal constructions, she becomes lost, appearing moronic and spastic. Top-down, internally driven organizers of verbal sequencing and ordering of scenes into imagined plans appear to be impaired.

The "abstract vs. concrete" dichotomy takes on new meaning when we consider conceptual coordination as involving different sensory modalities, as illustrated by an example of a contrasting dysfunction. Dr. P is the famous "man who mistook his wife for a hat." Dr. P lives in the opposite of the autistic world: Dr. P lives in the world of abstract conceptions, which he cannot appropriately relate to concrete things in the scene around him (pp. 7, 20, 229):
 

Not only did Dr. P increasingly fail to see faces, but he saw faces when there were no faces to see... in the street he might pat the heads of water hydrants and parking meters, taking these to be the heads of children; he would amiably address carved knobs on furniture and be astounded when they did not reply. (p. 8)

There was something radically wrong with the whole way he proceeded. For he approaches these faces—even of those near and dear—as if they were abstract puzzles or tests. He did not relate to them, he did not behold. (p. 13)

He took it like a botanist or morphologist given a specimen, not like a person given a flower. ëAbout six inches in length,' he commented. ëA convoluted red form with a linear green attachment.... It lacks the simple symmetry of the Platonic solids, although it may have a higher symmetry of its own...' (pp. 13-14)

The impairments in knowledge explored by Oliver Sacks are not scientific misconceptions or the kind of failures in high school physics tests. Rather, he explores the abstract nature of conceptual coordination, where the "abstracting" process is not only verbal, but includes other kinds of organizers in time: visual, rhythmic, manipulospatial.

Teasing apart the lessons from neuropsychological dysfunctions is complicated because the patients illustrate, even in their dysfunctions, what computer models cannot do. For instance, Dr. P can only coordinate his eating and dressing by continuing to hear a song in his mind (p. 17)! On the one hand, these patients illustrate the reality (Dr. P) and necessity (Rebecca) of abstraction by descriptive modeling in everyday life. However, their experiences suggest that more might be going on, which is also integral to human cognition. To sort out these organizers, I contrast the mechanisms of symbolic reasoning (descriptive modeling), with sequential and simultaneous relating in human coordination (Table 1). Of the two patients, Dr. P is more like a computer program operating on descriptive models. But taken together, the examples illustrate that abstraction via description manipulation is insufficient—descriptive cognitive models do not adequately capture or replicate everything that people can do.
 
 

Abstract Cognitive Processes	Symbolic Reasoning	Ability to compose sequential relations	Ability to simultaneously relate image and sound in coordinated action
Example	manipulating descriptive model of world, e.g., deductive inference	physically aligning objects, grammatical speech, projecting ordered events, e.g., hearing a song in one’s head	dancing, speaking metaphorically
Rebecca
Dr. P
Descriptive Cognitive Model		()

To elaborate a bit more, "concrete" in Rebecca's understanding means especially a direct coupling between perceptual patterns and action. She lacks a kind of non-verbal abstraction required for hand-eye coordination or constructing an imaged plan of motion over time, as required in walking around the block. She compensates by embedding her action in a narrative conceived over her visual-auditory space. But her metaphoric understanding, a form of abstraction, cannot be explained by descriptive cognitive models, which postulate that metaphor is a process of matching feature descriptions (Schön, 1987; Hofstadter, 1995)—which she cannot do at all.

"Concrete" in Dr. P's understanding means describing and relating properties of objects. He lacks a kind of visual abstraction required for relating details within a simultaneously-perceived configuration. He compensates by manipulating descriptions, like an expert system. But his visual problems cannot be explained by descriptive cognitive models, which postulate that visual abstraction is a process of matching feature descriptions—which he can do very well indeed.

On the surface, the conventional formal definition of abstract thought appears reasonable: "...thinking that goes beyond immediate experience, regulated by knowledge structures called abstract schemas."(Ohlsson, 1993) Conventionally, such abstract schemas are taken to be descriptions of objects, properties, and events, as in explanations of Dr. P's reasoning. But the following forms of conceptual organization also go beyond immediate experience: hearing a tune in one's head, visualizing a planting border around a lawn, placing an arm in a sleeve. Such behaviors are conceptually coordinated and don't all involve verbal descriptions in their form or regulation. Indeed, most studies of abstract thought focus on scientific theories, not how to find one's way around the block. If we take thinking to involve any organizing performed by the brain in relating and ordering of actions in time, then a more general notion of abstracting might be called conceptual coordination.

From this broader perspective of conceptualization we can begin to place the concrete and the abstract in a different relation—not just an ordering of descriptions from specific to general or implicit to explicit. For example, Varela (1995, p. 11-12) says that "the proper units of knowledge are primarily concrete, embodied, lived...The concrete is not a step toward anything: It is how we arrive and where we stay."
 

In a nutshell, the enactive approach [to cognition] consists of two key points: (a) that perception consists of perceptually guided action; and (b) that cognitive structures emerge from the recurrent sensorimotor patterns that enable action to be perceptually guided. (p. 16)

The coupling relation between perceptual and motor systems, even involving conceptual organizers, was emphasized by Dewey (1896) in his famous critique of early stimulus-response theory. The relation of sensation, perception, and motor processes is dynamic, as part of a circuit, such that the momentary interactions within the system are sustained and directed as one developing ensemble, each momentary organization leading to the next, and (in Bartlett's terms) each organization is literally built out of the components that have worked together in the past. Again, this includes conceptual processes, as in Rebecca's conception of narratives and metaphors—there are other ways to form and relate concepts than by inferential chaining of descriptions. Understanding musical intelligence, spatial reasoning, visual recognition, and their relations to symbolic reasoning (Gardner, 1985a) is enhanced by this shift to a multimodal, coordination view of cognition.
 
 

• Descriptive representations: Linguistic expressions (e.g., texts and diagrams), including numeric models and computer datastructures called "symbolic representations."

• Conceptualization—representing in brain: Modalities for coordinating experience and action, includes verbal and non-verbal, the simultaneous and the sequential.

• Reasoning: Categorizing, ordering, and comparing conceptualizations to construct a "mental model" or "action plan"; includes inner speech; never strictly formal because always involves conceptualization.

• Calculation: Formal manipulation of descriptions, as in mathematics, expert systems, and other descriptive cognitive models (e.g., Soar (Newell, 1990)).

By the "situated view" there is a fundamental difference in kind between descriptions/calculation, and conceptions/reasoning. But the descriptive modeling view equates conceptualization with descriptive representation and reasoning with calculation. This misses the point that abstract schemas described by Bartlett (what I call conceptualizations) are not descriptions, but neural categorizations coordinating different modalities. The exclusively descriptive models of natural language processing omit the non-verbal aspects of comprehension, and suppose instead a mechanism built entirely out of words (above the phonemic level). In contrast, conceptualizations are processes of representing. Unlike texts and diagrams, they exist only in the time of use. They do not encode and are not stored or perceived as things. Conceptualizations involve aspects of perceiving and—by virtue of how the categorizing mechanism works—are inherently integrated with physical activity.

For example, Sacks emphasizes that Dr. P's problem is not just a loss of an isolated function, of visual processing. Perhaps more important, to lose the visual capability to conceive scenes, that is to identify objects as wholes, is to lose an aspect of human subjectivity. The holistic, conceptual grasp of a face as being a face and personal judgment are related. Without a holistic visual grasp, a means of experiencing feeling, of relating personally to the world is lost. When Dr. P did manage to infer the name of the person or thing, he could experience an emotional attachment. Otherwise, things that other people found significant (like his wife sitting on the chair to his side) just went past him.

More generally, being "socially situated" means appropriately choreographing activities—"ways of being," roles, ways of spending time, "things we do when." Examples of activities are: Reading the Sunday paper, going to the movies, working at IRL, being the clinic physician-in-charge, being on a business trip, attending a workshop, staying in a hotel, living in California, taking a vacation, writing a book. Activities are always temporally extended "things we do," often restricted to a certain time and place, with conventions for when we do them, what we wear, how we talk, and what value we place on events. Activities are always socially constructed, in the sense that they are negotiated (by action and feedback) within a community.

Activities are abstractions, like all conceptualizations. But we must beware not to identify activities with their descriptions. It would be easy to slide into calling every activity a task and specifying a goal description and rules or procedures for carrying them out. This is how the exclusively task-oriented view of work leaves out people's conceptions of who they are, how they allocate their time, their allegiances, their career trajectories, etc. Activities are known by human behaviors; they are what we do (Frake, 1977; Rommetveit, 1987; Wynn, 1991. As conceptions they constitute part of the context in which goals become defined and tasks are assigned and carried out. The real world is part of this context too, but it is the mental conceptualization of role, community, practice, etc.—the choreography of action—that shapes how we think of something to do and how we think about how to do it.

From this perspective, knowledge does not consist of theories and models per se, but comprises our conceptualizations and our perceptual categorizations that coordinate what we see and do. Activity conceptualizations are adaptively activated in different physical and social contexts. In this sense, they are general: I may go to a restaurant in a different country and understand what is happening around me and how to behave, even though the menu and money may be incomprehensible.

Activity conceptualizations were described by Schank's formalization called "scripts." However, in practice human knowledge doesn't consist of a single "restaurant script" per se, but a different conceptualization for each actor: the chef, the owner, the waiter, the patron, the guest, etc. Instead of universal descriptions that are shared, conceptualizations involve an inherently subjective point of view. Conceptualizations are alike not just because of the language we use during the activity. More importantly, as categorical relations between roles, stuff in the world, and conventional actions, conceptualizations develop within and sustain a coordinated practice of behavioral interactions. The "similarity," what is shared, lies in interactive compatibility, not isomorphism of stored descriptions. For example, in the restaurant, different players hand-off their work and interpret materials in compatible ways.

In summary, there are different kinds of generalization in practiced motor skills, conceptualizations, and descriptive models. All are "abstracted," but in different ways. There is no one-one correspondence between them; in particular, we cannot exhaustively describe the "definition" or "meaning" of everyday conceptualizations and can't functionally replace the neural conceptualization process with an engine that manipulates and controls behavior on the basis of descriptions alone. The evidence for this is provided by neurological dysfunctions: Dr. P resembles an inferential engine, unable to see the forest for the trees. On the other hand, a fully "poetic" coordination process, like Rebecca's, lacking a "symbolic" organizer, reveals an inability to deliberately relate categorizations in space and time—but she can dance.

1) A comparison of descriptions, in which classes with features serve as variables to generalize a description (e.g., "give aspirin to a patient with an fever" is more abstract than "give aspirin to Mary").

2) Temporal activation and configuration of sensorimotor processes, including the phenomena of perceptual categorizing, the practice effect (categorizing sequences, conceiving chunks), and multimodal coordination (singing while dressing).

The first is the domain of an observer's descriptions in text, speech, and diagrams. The second is the domain of sensorimotor coupling (what Maturana and Varela call embodied action). The historical relation of abstract and concrete are different in these two domains, though both emphasize a causal relation: the relatively abstract is constructed from the concrete. But in the purely descriptive domain of computer models, abstract descriptions are created by examining concrete descriptions (e.g., cases or input examples) and generalizing them, a process of finding patterns and stating rules with variables (e.g., see Buchanan et al., 1969). In the domain of embodied action, there are at least three kinds of abstraction relations:
 

• Perceptual categorization from sensory signals

• All categorizations are biased by (built from) previously formed categorizations

• Categorizations may compose: Verbal chunks are categorizations of sequences of categories forming in time and a visual chunk involves a concurrence of categorizations (what Luria, 1988, calls "simultaneity").

Categorizations are neural structures that activate and hence constitute structures that are forming at the time of experience itself. This is to be contrasted with a stored memory. Neural memory is "content-addressable," but without retrieval as independently existing things. Associations are in some sense direct, involving what Edelman calls "classification couples" and "reentry" (mutual excitation) between levels of categorization. By this view, the "seven plus or minus two" size of short-term memory is a limit on how many processes we can sequentially chain together and hold active at one time. That is, we construct an activation sequence by which one global neural map feeds forward into the next and do this for 7±2 maps. It is not a constraint on space (a buffer size) but on time (with respect to sustaining activations).

Other key properties of this emerging understanding of neural processes of representing include:
 

• Neural categorizations are not immutable forms (unlike tokens in descriptive models) (Merzenich, et. al., 1983).

• Neural categorizations are stable relations between processes (Rosenfield, 1988).

• Neural categorizations may be non-verbal, as in imagery and music (Gardner, 1985a).

• Categorizing sequences of categorizations over time may correspond to the inferential chunking mechanism of descriptive cognitive models (as in Soar; Newell, 1990).

The point is that words probably correspond to recurrent neural categorizations, but there are more abstract, subsuming conceptualizations organizing the person's experience (activity conceptualizations), as well as more concrete, subsumed conceptualizations of perceptual-motor experience (Lakoff, 1987). Speaking and interpretation of descriptions occurs within this conceptual activity and perceptual-motor context. The higher-order understanding affects how we move and where we look as we interact in the world—what perceptual categorizations are of interest to us and how our interpretations are biased. In some activities, such as computer programming or mathematics, our actions are strongly conventional and regulated; in others, such as spending an afternoon sailing or spending an evening on the town, our actions are still conventional, but there is more room for improvisation.

In short, the idea that conceptualization should be contrasted with descriptions is quite complex, involving not only how words relate to neural processes ("where are the symbols in the brain?"), but how activity is coordinated over time, including how we regulate our choice of words and schedule the tasks of the day, and in the large, how our sense of identity is constructed as social actors. By contrast, descriptive cognitive models are relatively flat, construing all the nodes in Figure 3 as words or networks of encodings, and viewing all the constructive relationships as processes of indexing, retrieving, matching, and instantiating. An alternative view claims that mechanisms we do not yet understand are involved, accounting for such phenomena as rapid figure-ground shifts, musical and rhythmic memory, visualization, silent speech, and projection of imagined movements in space.

1) Learned neural coordinations, which are generalized into conceptualizations resembling grammars (e.g., subject-verb order in English).

2) Descriptions of recurrent neural processes, such as formal grammars, expert system rules, and other cognitive models.

3) The "operating principles" of the hardware, that is, how new categorizations and sequences are constructed from previous coordinations, especially how reconstructing and holding active multiple categorizations allows us to categorize relations of identity, negation, causality, correspondence, etc.

Once we include this perspective in our inquiry, we find many examples in our experience of such non-descriptive conceptualization. For example, understanding irony or a pun involves apprehending an relation that is not in itself verbal, and may only with hesitation be expressed (with a sense of frustration at making the ineffable a thing, stating it in words). Another example is the imitation of an accent. Americans may conceive the patterning of British English, and mimic it. We do so by apprehending the relations of pronunciation and stressed sequences in a coordinated "coupling" of perceptual-motor categorizations; we conceive the accent as a way of performing, without having to first describe the accent formally and carry it out instructively as a procedure.

In contrast, creating and using descriptions involves modeling a situation in some language or notation and inferential steps to derive valid implications and new questions—performed either in our head by inferential conceptualizations or by a symbolic calculus, as in an expert system. Nisbett's report (1993) about teaching statistical reasoning studies such descriptive modeling at work. But the problems he encountered highlight the different kinds of regulators. Of special interest are the logical patterns of thought close to the limits of the neural processor. For example, it is difficult for some people to juggle the equivalence of "if p then q" and "if not-q then not-p" in their heads. Instead, a conceptualization such as "the semantic notion of obligation" allows holding the details of a problem active (as neural processes) and ordering them appropriately. These "pragmatic reasoning schemas" may exist without the person's articulation of the relations in formal terms (as stated in p's and q's) or even without an ability to execute on paper a logic proof requiring modus tolens. Instead, the person engages in a form of concrete thinking, arranging the elements of the situation in a mental model, according to a conceptual scheme (Wu, 1995).

Furthermore, concrete thinking of this form can be taught by describing the conceptual schema and providing examples of how to use it. In this respect, the rule description is a sign post, which may (or may not) be discarded in practice. "The rules can be made more accessible by teaching examples of their use, and especially by teaching people how to decode the world in ways that make it more accessible to the rule system" (Nisbett, 1993, p. 11). Nisbett's terminology must be used advisedly here—"decoding" must be viewed as moving from a description to a situation conceptualization.

Nisbett's conclusion that "it is a mistake to try to found a theory of mental life on mere associations or connections between concretely-defined elements" (p. 12) can be viewed with Rebecca's experience in mind as affirming the idea of conceptual coordination. But it might be turned the other way: It is a mistake to try to found a theory of mental life on mere associations or connections between verbally-defined elements. For then we would all be like Dr. P and expert systems. Indeed, the descriptive modeling approach has attempted to embrace all aspects of cognition within discrete, sequential, and often exclusively-verbal conceptualization. This view has dominated how cognitive science itself is pursued, constraining what constitutes data, what kinds of mechanisms are considered, and what kinds of partial understandings are recognized as reportable and professional. In teasing apart the map (our descriptions) from the territory (our conceptualizing), and asking what remains to be done, we are challenged to recognize that we know more than we can describe, and models based on encodings will always be impoverished relative to neurological processes we seek to replicate. Abstract descriptions may be the epitome of scholarly thought, but they are mere shadows of our concrete understanding.

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