Readiness-to-hand, extended cognition, and multifractality Lin Nie (lin.nie@uconn.edu) Department of Psychology, 406 Babbidge Road, Unit 1020 Storrs, CT 06279 USA Dobromir G. Dotov (dobromir.dotov@uconn.edu) Department of Psychology, 406 Babbidge Road, Unit 1020 Storrs, CT 06279 USA Anthony Chemero (tony.chemero@fandm.edu ) Department of Psychology, Franklin & Marshall College, PO Box 3003 Lancaster, PA 17604 USA Abstract A recent set of experiments of ours supported the notion of a transition in experience from readiness-to-hand to unreadiness-to- hand proposed by phenomenological philosopher Martin Heidegger. They were also an experimental demonstration of an extended cognitive system. We generated and then temporarily disrupted an interaction- dominant system that spans a human participant, a computer mouse, and a task performed on the computer screen. Our claim that this system was interaction dominant was based on the detection of 1/f noise at the hand-tool interface. The inference from the presence of 1/f noise to the presence of an interaction-dominant system is occasionally disputed. Increasing evidence suggests that inference from multifractality to interaction dominance is more certain than 1/f- like scaling alone. In this paper, we reanalyze the data using the wavelet transform modulus maxima method, showing that the human-mouse system displays multifractality. This reinforces our claims that the system is interaction dominant. Keywords: perception; Heidegger; extended cognition; tool- use. Introduction Background Heidegger’s relevance to research in AI has been long demonstrated conceptually (Dreyfus, 1979), however, little to none has been done to incorporate his notions into empirical studies. In a former set of published experiments (see Dotov, Nie, & Chemero, 2010 for necessary details), we provided evidence for the transition in experience of tools from readiness-to-hand to unreadiness-to-hand as proposed by Heidegger's phenomenological analysis of the modes of being of tools. When you are smoothly coping with a hammer that is ready-to-hand, the ready-to-hand hammer recedes in your experience, and your focus is on the task you are completing. A key point here is that from Heidegger’s perspective there is no need to presuppose that the place of the bones and tissues of your hand in your experience while working on a manual task is in any sense privileged relative to the place of the other tools making the task space. Your experience of the hammer is no different than the experience of the hand with which you are wielding it. This has inspired the hypothesis of extended cognition, i.e., the claim that cognitive systems sometimes extend beyond the biological body (van Gelder, 1995; Clark, 2008). Hammers and other tools that are ready-to-hand are literally part of the cognitive system. When a tool malfunctions, however, and becomes unready-to-hand, it becomes the object of concern; it is no longer part of the extended cognitive system, rather it is the thing that that the cognitive system is concerned with. To demonstrate Heidegger’s proposed transition and an extended cognitive system is to show that a human participant and a tool together comprised an interaction- dominant system. An interaction-dominant system (IDS) is a softly assembled system in which any part can take or lose the role of a functional unit of the system, depending upon the richness of physical coupling. Interaction-dominant dynamics can be contrasted with component-dominant dynamics more characteristic of traditional cognitive architectures (van Orden, Holden, and Turvey, 2003; Holden, van Orden, and Turvey, 2009). In component-dominant dynamics, behavior is the product of a rigidly delineated architecture of modules, each with pre-determined functions; in interaction-dominant dynamics, on the other hand, coordinated processes alter one another’s dynamics, with complex interactions extending to the body’s periphery and, sometimes, beyond. Simply put, when, as part of an experiment, a participant is repeating a word, a portion of her bodily and neural resources, along with environmental support structures,
[1]
E. Wagenmakers,et al.
Theories and models for 1/f(beta) noise in human movement science.
,
2009,
Human movement science.
[2]
C. Sparrow.
The Fractal Geometry of Nature
,
1984
.
[3]
J. Henriksson.
Human movement science
,
2012,
Acta physiologica.
[4]
Larry S. Liebovitch,et al.
TRANSITION FROM PERSISTENT TO ANTIPERSISTENT CORRELATION IN BIOLOGICAL SYSTEMS
,
1997
.
[5]
A. Chemero,et al.
A Demonstration of the Transition from Ready-to-Hand to Unready-to-Hand
,
2010,
PloS one.
[6]
T. Gelder,et al.
What Might Cognition Be, If Not Computation?
,
1995
.
[7]
J. A. Scott Kelso,et al.
Dynamic Encounters: Long Memory During Functional Stabilization
,
1999
.
[8]
Beatrix Vereijken,et al.
Interaction-dominant dynamics in human cognition: beyond 1/f(alpha) fluctuation.
,
2010,
Journal of experimental psychology. General.
[9]
H. Stanley,et al.
Behavioral-independent features of complex heartbeat dynamics.
,
2001,
Physical review letters.
[10]
Mirko Farina.
Supersizing the Mind: Embodiment, Action and Cognitive Extension.
,
2010
.
[11]
Marcel Ausloos,et al.
Low-order variability diagrams for short-range correlation evidence in financial data: BGL-USD exchange rate, Dow Jones industrial average, gold ounce price
,
1999
.
[12]
Geoffrey Hunter.
What Computers Can't Do
,
1988,
Philosophy.
[13]
B. Vereijken,et al.
Beyond 1 / f α fluctuation-1 Interaction-dominant dynamics in human cognition : Beyond 1 / f α fluctuation
,
2010
.
[14]
J. Kwapień,et al.
Wavelet versus detrended fluctuation analysis of multifractal structures.
,
2006,
Physical review. E, Statistical, nonlinear, and soft matter physics.
[15]
Thomas L. Thornton,et al.
Provenance of correlations in psychological data
,
2005,
Psychonomic bulletin & review.
[16]
E. Bacry,et al.
Multifractal formalism for fractal signals: The structure-function approach versus the wavelet-transform modulus-maxima method.
,
1993,
Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.
[17]
L. Amaral,et al.
Multifractality in human heartbeat dynamics
,
1998,
Nature.