• Self-organization;
  • Synergy;
  • Ultrafast cognition;
  • Context sensitivity;
  • 1/f noise


  1. Top of page
  2. Abstract
  3. 1. Three paradoxes of cognition
  4. 2. Ultrafast action
  5. 3. Exquisite context sensitivity
  6. 4. Scale-free variation
  7. 5. The road taken and the road ahead
  8. Acknowledgment
  9. References

In some areas of cognitive science we are confronted with ultrafast cognition, exquisite context sensitivity, and scale-free variation in measured cognitive activities. To move forward, we suggest a need to embrace this complexity, equipping cognitive science with tools and concepts used in the study of complex dynamical systems. The science of movement coordination has benefited already from this change, successfully circumventing analogous paradoxes by treating human activities as phenomena of self-organization. Therein, action and cognition are seen to be emergent in ultrafast symmetry breaking across the brain and body; exquisitely constituted of the otherwise trivial details of history, context, and environment; and exhibiting the characteristic scale-free signature of self-organization.

Blink (Gladwell, 2005) tells a story of experts who spotted at first glance a forged statue previously vetted and purchased by a museum. Ultrafast perception is an example of ultrafast cognition, and the anecdote has counterparts in scientific studies demonstrating ultrafast cognition. We contend that ultrafast cognition is one of three general inconsistencies between fact and theory of cognition, and we recommend solutions that have circumvented similar paradoxes in motor coordination of the body.

1. Three paradoxes of cognition

  1. Top of page
  2. Abstract
  3. 1. Three paradoxes of cognition
  4. 2. Ultrafast action
  5. 3. Exquisite context sensitivity
  6. 4. Scale-free variation
  7. 5. The road taken and the road ahead
  8. Acknowledgment
  9. References

Perhaps the best example of ultrafast cognition concerns a classic cognitive judgment of animacy, whether a novel picture contains an animate being or exclusively inanimate objects. Under carefully controlled conditions, designed to estimate a lower bound for speeded cognition, the time from picture to the subject’s response is as fleeting as a single burst of activity across the chain of neurons connecting eye to hand, a “feed-forward pass” that seems paradoxically to involve no extra processing time at all, as though the brain did nothing in between, though surely it must have (Fabre-Thorpe, Delorme, Marlot, & Thorpe, 2001, p. 6; Wallot & Van Orden, in press). Ultrafast cognition raises the question of whether temporally distinct “information processing” is always necessary, and if not necessary, does it exist at all?

Exquisite context sensitivity represents the second paradox. The most elementary cognitive judgments, such as when or where in space an object appears, “vary with task requirements in ways indicating the use of multiple distinct mechanisms with different characteristics in different tasks” (Durgin & Sternberg, 2002, p. 288). At issue is the fact that seemingly trivial differences in a task context motivate ever-growing numbers of ad hoc cognitive structures and undecidable debates about which differences should count as trivial. On top of that, archetypical factors produce reliable effects using some laboratory methods only to disappear in the context of another laboratory method, a problem so conspicuous it has attracted public notice (Lehrer, 2010). We use the term exquisite context sensitivity, because context does not merely affect cognition, but instead is fundamentally constitutive of cognition (e.g., Kloos & Van Orden, 2009).

The third paradox amplifies the second. Cognitive activities exhibit fractal scale-free variation in repeated measurements (Gilden, 2001). Variability appears the same at all scales, suggesting common sources for the variation at all scales in all repeated measurements. But the same data can give evidence that each kind of repeated measurement is independent of every other kind of repeated measurement, thereby dissociating different sources of variation (Kello, Beltz, Holden, & Van Orden, 2007). How can the same variation paradoxically originate from both the same and different sources? The interpretation becomes absurd when one considers behavior like speech that admits an indefinite number of separate repeated measurements, all showing scale-free variation and all varying independently of one another.

Clearly, no one intended that cognitive science would become a science of endlessly new, trivial, or paradoxical cognitive components. Toward escaping that fate, this essay takes the three paradoxes at face value, marking cul-de-sacs that will require unconventional solutions to escape. The solutions come from viewing cognitive activities as self-organizing complex systems, making available the conceptual and empirical tools of complexity science. The next sections describe solutions and introduce a complexity perspective applicable to cognitive activities generally.

As we explain, synergistic, “strange-loop” control allows control problems––conventional time-sinks of computation––to be offloaded to the dynamical organization of the body. Consequently, just like ultrafast cognition, ultrafast action can occur as fast as a one-way chain of activation across the body, or faster. Zero-lag-time mechanical feedback, for example, capitalizes on the elastic properties of the body to create so-called preflexes, which dampen perturbations without computation (Brown & Loeb, 2000; Nishikawa et al., 2007; Ostry & Feldman, 2003).

2. Ultrafast action

  1. Top of page
  2. Abstract
  3. 1. Three paradoxes of cognition
  4. 2. Ultrafast action
  5. 3. Exquisite context sensitivity
  6. 4. Scale-free variation
  7. 5. The road taken and the road ahead
  8. Acknowledgment
  9. References

Synergies enable ultrafast action. Synergies are temporary assemblies of components constrained to behave as a single functional unit. They are defined as compensatory, low-dimensional relations in the dynamic activities of neuromuscular components (Kelso, 2009), not as static representational structures such as motor programs. The activity of synergies pre-reduces the degrees of freedom in the possible relations among the components so as to preserve their functional organization. For example, to say the /b/in /bob/, the lips must be in contact. A synergy insures this contact by coupling the components to produce the relation between the lips, not some target jaw position. This coupling insures the lips will compensate for each other sufficiently to render executive monitoring or intervention unnecessary (e.g., Latash, Scholz, & Schöner, 2002; Scholz & Schöner, 1999).

Synergies are physically instantiated and have reliably observable effects (Haken, 1977; Juarrero, 1999; Kelso, 1995, 1998; Kugler, Kelso, & Turvey, 1980, 1982; Turvey, 2007). To test whether a synergy exists, you can perturb one of its components and observe how the others change (Kelso, 2009). Imagine perturbing speech with a sharp, unpredictable, downward tug on a speaker’s jaw, while she attempts to say the /b/ in /bob/. Remarkably, the compensation for the displacement begins within 5–10 ms, faster than a loop of neurons can calculate a new configuration. A new configuration is necessary nevertheless because the lower lip compensates for the perturbation, not the jaw that was tugged. Within 5–10 ms the lower lip begins to stretch upward to sustain the necessary relations with the upper lip and other components to say /b/ (Kelso, Tuller, Vatikiotis-Bateson, & Fowler, 1984; see also Abbs & Gracco, 1984; Folkins & Zimmermann, 1982).

Speech articulation depends upon about 70 muscles working in concert. Uttering the equivalent of a single phoneme, the /b/ in /bob/, realizes coordinated changes among the muscles of the tongue, the lips, the jaw, and respiration in a delicate synchrony of movement through space, to be at the right time in the right place. In the intricate ballet of a single spoken sentence, each set of muscles will have taken on multiple roles to actualize the desired speech. Thus, the essential problem of speech is the perpetual coordination of so many components within the narrow trajectories required for legible speech (e.g., van Lieshout, Bose, Square, & Steele, 2007). This is called the degrees of freedom problem; there are far more possible arrangements of speech components than there are legible ways to make speech sounds.

Synergies solve the degrees of freedom problem via linkages among neuromusculoskeletal components that insure the components act coherently together (Bernstein, 1967; van Lieshout, 2004; Turvey, 1990, 2007). Temporary links emerge in feedback interactions (neurophysiological, chemical, and mechanical). The ultrafast compensations achieved by synergies require that possible actions are anticipated, but not in the sense of rules or explicit expectations. Rules and expectations are too narrowly anticipatory, making them fragile and inherently vulnerable to novelty, whether due to variety or perturbation (Van Orden, Kello, & Holden, 2010). Dynamical feedback links components to constrain each other’s activities, making anticipation more robust while still ruling out contextually inappropriate actions.

Synergetic coupling is not confined to the periphery of motor coordination and has been observed between abstract cognitive factors and peripheral components. An abrupt tug of one lip has immediate consequences for both bilabial and laryngeal gestures and both the lip gestures, of abstract phonology, and the peripheral kinematics of the larynx show ultrafast compensation (Saltzman, Löfqvist, Kay, Kinsella-Shaw, & Rubin, 1998; see also Bauer, Jancke, & Kalveram, 1995). This bi-level coupling of (kinematic) micro-dynamics and (linguistic) macro-dynamics is characteristic of complex, dynamic systems (van Lieshout, 2004).

To embrace this approach, one must reject that control originates in conventional, pre-structured, motor-schematic positions and velocities of individual components. Legible speech emerges in the nonlinear feedback interactions among the speech components. Nonlinear feedback interactions have an “attractive” power (Strogatz, 1993) that constrains the possible relations to those of legible speech and thereby sustains legible speech in the self-same relations among the components (Kloos & Van Orden, 2010). The constrain–sustain dynamic that emerges is called strange-loop control (Juarrero, 1999).

3. Exquisite context sensitivity

  1. Top of page
  2. Abstract
  3. 1. Three paradoxes of cognition
  4. 2. Ultrafast action
  5. 3. Exquisite context sensitivity
  6. 4. Scale-free variation
  7. 5. The road taken and the road ahead
  8. Acknowledgment
  9. References

Our bodies usually find the right configuration with the environment as we move. The right configuration adroitly exploits potential energy, tailoring the production of muscular forces to harvest energy from gravity and the inertial forces of the ongoing movement (Bernstein, 1967; Dickinson et al., 2000; Turvey, 2007). This is one way context pervades synergies of the body.

Synergies are “softly” (temporarily) assembled to match the context (Kugler & Turvey, 1987). An example is found in central pattern generators (CPGs), networks of motor and interneurons that produce rhythmic outputs. CPGs can be reorganized when sensory and mechanical feedback trigger neurotransmitter release that functionally alters the network connectivity (Harris-Warrick & Marder, 1991; Hooper, 2001; Morton & Chiel, 1994). Inhibitory connections can become excitatory, neurons can be recruited into networks in which they did not participate before, and previously separate networks can fuse. These modulations coincide with functional changes in behavior—for example, a mollusk slowly treading water changes abruptly, recruiting additional interneurons to enable rapid escape from a predator (Nishikawa et al., 2007).

Postural control provides abundant evidence for context-sensitive synergies. To maintain balance, the body’s center of mass (CM) cannot exceed the limits of the base of support (usually, the boundaries of the feet). Movement must be anticipated in remote preflexes and ultrafast compensation across whole-body synergies, lest we tip over (Belen’kii, Gurfinkel, & Pal’tsev, 1967). Motor scientists once expected to find a countable set of postural solutions (Nashner & McCollum, 1985). Solutions are identifiable in analyses of the dynamics of postural sway, the ceaseless, arrhythmic, low-amplitude changes in CM position. When the observed dynamics of any system change qualitatively, a newly configured underlying dynamical system must have emerged (Riley & Turvey, 2002; Saltzman & Munhall, 1992). Almost any finely drawn change in context, person, and task to be accomplished while standing yields unique postural sway dynamics—the body thus creates of itself limitless solutions (new dynamical synergies), apace with the perpetually idiosyncratic contexts in which it finds itself (Riccio & Stoffregen, 1988; Riley, Kuznetsov, & Bonnette, 2011). This might be all right, theoretically, if this paradox could be contained; if it was limited to a special class of people like acrobats, for instance. Yet all persons show the capacity to create of themselves an indefinite variety of dynamical systems to suit changes in postural demands: children (Haddad, van Emmerik, Wheat, & Hamill, 2008; Newell, 1998), elderly adults (Duarte & Sternad, 2008; Seigle, Ramdani, & Bernard, 2009), persons with neurological disorders (Donker, Ledebt, Roerdink, Savelsbergh, & Beek, 2008; Schmit et al., 2006), balance experts (Schmit, Regis, & Riley, 2005), and healthy young adults (Riley & Clark, 2003).

Interpersonal coordination of bodies and minds exhibits the same hallmarks of synergy and context sensitivity as intrapersonal coordination (Black, Riley, & McCord, 2007; Schmidt, Carello, & Turvey, 1990). Interpersonal dynamical contexts are constitutive of conversation and joint action. For example, the gaze of speaker and listener (Richardson & Dale, 2005; Richardson, Dale, & Kirkham, 2007) and postural sway (Shockley, Santana, & Fowler, 2003; Stoffregen, Giveans, Villard, Yank, & Shockley, 2009) jointly embody the coordination that coincides with effective communication (Shockley, Richardson, & Dale, 2009). The shared context of speaker and listener synchronizes brain activity, and comprehension can be predicted by the extent of local brain synchrony (Stephens, Silbert, & Hasson, 2010).

Task context can even shape the expression of learning disabilities (Hendriks & Kolk, 1997). Encouraged to read aloud very quickly, developmental dyslexics make errors associated with a deficit “lexical” process in reading, including visual/phonologic errors and semantic errors, producing symptoms of one subtype of dyslexia. When encouraged to read aloud very accurately, the same dyslexics exhibit letter-by-letter or syllable-by-syllable reading associated with a deficit “nonlexical” process in reading—the symptoms of a different subtype of dyslexia. The outcome is consistent with the proposal that cognition undergoes a phase transition, self-organizing different dynamical systems under speed versus accuracy conditions (Dutilh, Wagenmakers, Visser, & van der Maas, 2011). Speed versus accuracy “subtypes” closely parallel two subtypes of acquired dyslexia, featured in the double dissociation of reading processes that kicked off modern cognitive neuropsychology (Marshall & Newcombe, 1973, 1977). Extreme speed conditions also produce naming errors to printed words by intact persons like the errors of acquired dyslexics (Kello & Plaut, 2000). Different task demands elicit different forms of aphasia from the same brain-damaged individual, appearing agrammatic in one task context (exhibiting telegraphic speech) but paragrammatic in another (exhibiting morphological substitutions) (Hofstede & Kolk, 1994; Kolk & Heeschen, 1992; Kolk & Hofstede, 1994; Kolk, Van Grunsven, & Keyser, 1985).

Dual-task paradigms allow performance of one task to perturb the performance of another task. Pressure to respond quickly in a cognitive task perturbs and weakens the stability of motor synergies, compared to motor performance by itself (Temprado, Zanone, Monno, & Laurent, 1999, 2001). However, some cognitive tasks supply sufficient perturbation to change the organization of motor performance in dual-task conditions (Pellecchia, Shockley, & Turvey, 2005; Shockley & Turvey, 2005, 2006). Dynamical models suggest a qualitative reorganization in the latter case, a functional reorganization of motor performance under cognitive constraints (Fuchs, Haken, & Kelso, 1992). Motor performance self-organizes new dynamical solutions in a new context requiring significant cognitive demands, suggesting a higher order synergy integrating the cognitive and motor dynamics of both tasks.

Context-sensitive plasticity may be a central principle of brain architecture (Nikolić, 2010). The brain changes the functional connective topography of the default network depending on task demands (Hasson, Nusbaum, & Small, 2009). Initially, the default network was speculatively associated with spontaneous thought, like daydreaming (Mason et al., 2007; McKiernan, D’Angelo, Kaufman, & Binder, 2006). However, the spontaneous dynamics differ depending on what the participant just heard, and the temporal coordination among regions of the default network change depending on task demands and the investment of attention in the task. How could regional brain connectivity change reliably except in a direct coupling to the context of brain activity?

In theory, if synergies self-organize the body, brain, and mind, a direct coupling between context and cognition must exist, insuring that context is constitutive of cognition (Turvey, 2007). This scheme resolves longstanding dilemmas about the origins of intentions and voluntary behavior (Juarrero, 1999). Intentions supply constraints that limit the body’s degrees of freedom (Kugler, Turvey, Carello, & Shaw, 1985; Van Orden, 2010). The limited degrees of freedom circumscribe a purpose or goal in behavior by limiting the propensities for behavior to those consistent with intentions (Järvilehto, 1998). Any contingency favoring one propensity over the others breaks the symmetry of poised options to enact behavior (Kloos & Van Orden, 2010).

Exquisite context sensitivity is linked to ultrafast action (and cognition). If speech perception or motor coordination is perturbed with incremental changes of the stimulus (a change in context), synergies are perturbed in ultrafast lockstep. If a perturbation is sufficient to prompt a qualitative reorganization of perception or motor coordination, the reorganization is anticipated by predictable patterns of change in the measurements, and the time delay from the brain reorganization to the behavioral reorganization accords with ultrafast action (Fuchs et al., 1992; Kelso & Fuchs, 1995).

4. Scale-free variation

  1. Top of page
  2. Abstract
  3. 1. Three paradoxes of cognition
  4. 2. Ultrafast action
  5. 3. Exquisite context sensitivity
  6. 4. Scale-free variation
  7. 5. The road taken and the road ahead
  8. Acknowledgment
  9. References

The third paradox concerns the nature of variation in behavior. Operationally, behavior in fact means changes in some measurement of performance. Details of the variation across measured changes provide the empirical facts for understanding cognition. This is why behavioral scientists study changes in laboratory measurements so closely and become experts in statistics. Variation or variability writ large is the thing explained about cognitive performance.

Variation in repeated behavioral measurements, whether cognitive, motor, or physiological, is characteristically scale free, which must figure centrally in any account. Scale-free variation is understood using fractal geometry and is called fractal noise on that basis. Fractal geometry is the mathematics of natural irregularities. Galaxies, trees, mountains, lungs, nervous systems, arteries and veins, the timing of heartbeats, and variation in repeated measurements of behavior are all fractals. In these phenomena, the observed fractal patterns lack stable central tendencies; the “noise” is actually the signal (Liebovitch & Shehadeh, 2005).

Widespread evidence exists of fractal noise in time series of cognitive and motor data (Gilden, 2001, 2009; Holden, Choi, Amazeen, & Van Orden, 2011; Kello & Van Orden, 2009; Riley & Turvey, 2002). These fractal patterns resemble those seen widely in self-organizing systems (Bak & Chen, 1991). Given that synergies are self-organizing, this offers additional insight into all three paradoxes. Fig. 1 (top right) portrays the irregular, arrhythmic, fractal noise in variations in reading times from a self-paced reading task. The reader advances a story displayed on a screen one word at a time by pressing a key (cf. Wallot & Van Orden, 2011). The data are the times between key presses kept in the order in which the story was read and in which the keys were pressed.


Figure 1.  One participant’s self-paced word-by-word reading time data. The word-ordered, normalized durations between key presses, which advance the text to the following word, are portrayed in the upper right (x-axis is order, y-axis is normalized reading time). The specific frequencies and amplitudes of change (left side of figure) approximate the rough graph of the time-series data and become the outcome of the spectral analysis below (lower right). The spectral slope α = −0.89 expresses the scale-invariant (fractal) relation between the frequencies and amplitudes of variations in the reading time data series. Note that the y-axes of the illustrated sine waves (left) were adjusted to make the smaller amplitude sine waves visible.

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To evaluate the fractal structure, the data are decomposed into sine waves using a Fourier transform (Fig. 1, left). The sum of those sine waves approximates the irregular variation in reading times. A spectral plot (bottom right) portrays the magnitude of change in the data (the y-axis is the logarithm of magnitude squared) together with how often change of that magnitude occurs (x-axis)—rare, large changes correspond to points in the upper left of the spectral plot and common, small changes are in the lower right. The fractal pattern is suggested by the linear relation between magnitude and frequency, which implies that magnitude and frequency of change are proportional for changes of all sizes; they are scale invariant or scale free, which means they are statistically self-similar and thus compose a fractal.

In human gait, for instance, the presence of fractal noise signifies the coordination of different feedback processes (electrochemical, mechanical, informational) instantiated at different scales of the body (sensory, metabolic, neuromuscular, cognitive) each operating on different timescales. Although the basic idea of changes on different timescales is not new (cf. Newell, 1990), the idea that these changes and timescales are interdependent is new.

A change in the fractal dimension of performance gauges the coordination of mind and body in their temporal coupling to a task. Changes toward random white noise suggest the increased presence of sources of perturbation, or reduced coupling; changes toward overly regular brown noise suggest a tighter coupling in more rigid voluntary control (Van Orden, Kloos, & Wallot, 2011). In every case, coordination requires a kind of nonlinear compromise in the magnitudes of local and global changes.

The compromise reflects a tension between intrinsic local changes within components and global changes among components in synergy. All complex systems include this tension between local and global dynamics. Each component has idiosyncratic local dynamics yet the components must work together. In mathematics and physics, the tension between these tendencies is called frustration, because no solution can be other than temporary (Binder, 2008).

Frustration has advantages. If a local dynamic on one timescale were to globally dominate gait, then locomotion would unfold in an overly regular pattern, and the walker might be incapable of adapting to the variation in natural terrain. Yet if no global compromise could be reached gait would be sporadic and perilous, in a chaotic waxing and waning of powerfully opposed rhythms, failing to accommodate the regular features of smooth landscapes or paved surfaces for walking.

Scale-free variation lives between the extremes. It is a third kind of variability not to be confused with the highly predictable or random forms of variation that bracket it. A recent synthesis of studies reporting changes in fractal dimension has proposed a flexible tradeoff between the available constraints and the perturbations of the coupling between task and person (Kloos & Van Orden, 2010). Complex systems are flexible systems capable of absorbing and dissipating perturbations without a breakdown in performance, a robustness that simpler systems do not possess. As outlined above, when sufficiently perturbed, complex systems reorganize their component dynamics, creating compensatory functional capacities.

The dual-task paradigm can force a reorganization of cognitive dynamics as illustrated by changes in the fractal variation of performance. Walking on a treadmill while doing a cognitive task, participants show the same statistics in gait, for both fractal and traditional descriptive statistics, as if they were walking on the treadmill alone with no other task, but cognitive dynamics change between the single- and dual-task conditions (Kiefer, Riley, Shockley, Villard, & Van Orden, 2009). Cognitive performance shows a clear fractal pattern in the single-task condition, but in the dual-task condition it deviates toward a more random pattern in the dual-task condition while sustaining equivalent performance statistics (means and standard deviations).

Pitting the priority of motor activities against cognitive activities, the flexible cognitive system absorbs and dissipates motor perturbations without a performance breakdown, reorganizing to sustain the same accuracy in cognitive performance. Aging and disease eventually take their toll, however, and behavioral and physiological dynamics depart toward pathological rigidity or randomness. Either departure from complexity reduces the capacity for flexible, adaptable well-being (Glass, 2001; West, 2006).

5. The road taken and the road ahead

  1. Top of page
  2. Abstract
  3. 1. Three paradoxes of cognition
  4. 2. Ultrafast action
  5. 3. Exquisite context sensitivity
  6. 4. Scale-free variation
  7. 5. The road taken and the road ahead
  8. Acknowledgment
  9. References

We have reviewed cognitive and behavioral studies in the context of the three paradoxes, discovering complexity in human performance at every turn. The historical response to complexity was to prune it away in favor of elementary behaviors, or to study one part in isolation from other parts, seeking precise control in a laboratory context. This approach has been successful, undeniably so, and necessary to build a logically sound bridge to the discovery of complexity (Bechtel & Richardson, 1993).

However, divide-and-conquer has recognized limits—William James (1890/1950) and Gestalt psychologists such as Wertheimer (1924/1950) warned against exclusive reductionism. Many contemporary scientists (including many cognitive scientists) echo their concerns, being theoretically sophisticated about part-whole relations in the contemporary vein. Nonetheless, embracing complexity means something more than recognizing system wholeness.

Two approaches have been taken within the larger science of complexity. These complementary approaches differ crucially with regard to emphasis. One approach is called complexity-from-simplicity, a catchphrase popularized by the Santa Fe Institute and others (Mitchell, 2009; Wolfram, 2002). The phrase pertains to systems composed of many simple elements, each behaving according to simple rules, that in their interactions exhibit surprisingly rich and complex behavior. Trademarks include the early findings of chaos theory, connectionism, and the dynamics of cellular automata (Farmer, 1990; McClelland, Botvinick, Noelle, Plaut, Rogers, Seidenberg, & Smith, 2010; Wolfram, 1983).

Complexity-from-simplicity emphasizes strongly emergent properties that cannot be deduced from the properties of elementary components, even knowing how they interact. In cognitive science the implications of this approach are widely acknowledged (e.g., McClelland et al., 2010)—each time a claim is made that a behavior is emergent, for instance. What has been more difficult, however, is to fully confront the problem for analysis when nonlinearity is the rule and linearity the exception, to turn away from reductions to hypothetical basis functions of mind, brain, or behavior, focusing exclusively on interactions. This defines the entry point to the complementary approach emphasized in this essay.

The complement to complexity-from-simplicity is simplicity-from-complexity, or emergent simplicity (Bar-Yam, 1997), which concerns a less widely considered question: How does a high-dimensional system of vast complexity, a person for instance, produce simple, coordinated, low-dimensional behaviors? The question presents an essential challenge to cognitive science. It is fundamentally the same challenge that Bernstein (1967) identified as the degrees of freedom problem in motor coordination. This is the approach from which the synergy hypothesis is borne. It has featured less prominently in cognitive science than complexity-from-simplicity, which as noted is an entailment of connectionism, for example. Simplicity-from-complexity is perhaps the road that lies ahead.

Simplicity-from-complexity is only possible far from equilibrium in systems with many nonlinearly interacting components. The nonlinear interactions entail an “attractive” power to constrain system behavior to a relatively simple course, which we see as the low-dimensional macroscopic behavior of a person, for example. The nonlinear interactions are feedback interactions, and feedback constrains the interacting components to sustain the macroscopic behavior (Haken, 1977). This is again the constrain-sustain dynamics of the strange loop (Juarrero, 1999).

Peculiar as it may sound, in our view, the formal capacity of strange loops to self-organize behavior and generate simplicity from complexity may spur transformative progress in cognitive science, and thus represents a radical departure from the status quo. Working from this approach, we recognize that the low-dimensional coordinated actions of humans are more than mere effects or byproducts of a mind, the environment, a brain, or a stimulus, and we may discover these factors’ complex interdependencies in cognitive activities, as ordinary parts of nature after all.


  1. Top of page
  2. Abstract
  3. 1. Three paradoxes of cognition
  4. 2. Ultrafast action
  5. 3. Exquisite context sensitivity
  6. 4. Scale-free variation
  7. 5. The road taken and the road ahead
  8. Acknowledgment
  9. References
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