Living in the Pink

Orden, Guy C. Van; Kloos, Heidi; Wallot, Sebastian

doi:10.1016/b978-0-444-52076-0.50022-5

Cited by 71 publications

(43 citation statements)

References 157 publications

(39 reference statements)

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“…In psychology, the emergent property generally derives from a complex system of neurons (Fingelkurts and Fingelkurts, 2004; Barrett, 2009, 2011; Van Orden et al, 2011; Fingelkurts et al, 2013). With Network Analysis, emergence derives from a complex system of components.…”

Section: Network Analysis: Contributions and Contradictionsmentioning

confidence: 99%

“…Psychological attributes can be considered as robust attractors within a complex dynamic arising from mental processes with emergent properties (Fingelkurts and Fingelkurts, 2004; Barrett, 2009, 2011; Van Orden et al, 2011; Fingelkurts et al, 2013; Maul, 2013). When psychological attributes are defined as attractors, it is the ontology of psychological attributes that is reassessed.…”

Section: Psychological Attributes In Pragmatist-realist Epistemologymentioning

confidence: 99%

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Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

2017

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Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes.

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Section: Network Analysis: Contributions and Contradictionsmentioning

confidence: 99%

Section: Psychological Attributes In Pragmatist-realist Epistemologymentioning

confidence: 99%

Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

2017

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“…This “pathological breakdown of complexity” with aging and disease is thought to reduce the adaptive capabilities of an individual (e.g., [ 25 – 28 ]) and has been documented for a wide variety of physiological functions, including heart rate dynamics, respiration, postural control, and walking. In a similar vein, the theory of optimal movement variability, proposed by Stergiou and colleagues [ 29 – 31 ], postulates that there is an optimal level of complexity associated with healthy and proficient behavior (see also [ 32 ]). Gait therapies developed in accordance with these frameworks should aim to restore optimal gait variability, operationalized as statistically persistent stride-to-stride fluctuations [ 7 , 8 , 10 , 14 , 20 , 31 ].…”

Section: Introductionmentioning

confidence: 99%

How to Sync to the Beat of a Persistent Fractal Metronome without Falling Off the Treadmill?

et al. 2015

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In rehabilitation, rhythmic acoustic cues are often used to improve gait. However, stride-time fluctuations become anti-persistent with such pacing, thereby deviating from the characteristic persistent long-range correlations in stride times of self-paced walking healthy adults. Recent studies therefore experimented with metronomes with persistence in interbeat intervals and successfully evoked persistent stride-time fluctuations. The objective of this study was to examine how participants couple their gait to a persistent metronome, evoking persistently longer or shorter stride times over multiple consecutive strides, without wandering off the treadmill. Twelve healthy participants walked on a treadmill in self-paced, isochronously paced and non-isochronously paced conditions, the latter with anti-persistent, uncorrelated and persistent correlations in interbeat intervals. Stride-to-stride fluctuations of stride times, stride lengths and stride speeds were assessed with detrended fluctuation analysis, in conjunction with an examination of the coupling between stride times and stride lengths. Stride-speed fluctuations were anti-persistent for all conditions. Stride-time and stride-length fluctuations were persistent for self-paced walking and anti-persistent for isochronous pacing. Both stride times and stride lengths changed from anti-persistence to persistence over the four non-isochronous metronome conditions, accompanied by an increasingly stronger coupling between these gait parameters, with peak values for the persistent metronomes. These results revealed that participants were able to follow the beat of a persistent metronome without falling off the treadmill by strongly coupling stride-length fluctuations to the stride-time fluctuations elicited by persistent metronomes, so as to prevent large positional displacements along the treadmill. For self-paced walking, in contrast, this coupling was very weak. In combination, these results challenge the premise that persistent metronomes in gait rehabilitation would evoke stride-to-stride dynamics reminiscent of self-paced walking healthy adults. Future studies are recommended to include an analysis of the interrelation between stride times and stride lengths in addition to the correlational structure of either one in isolation.

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“…The slope of the regression line, α, that best fits the residual variance estimates in the DFA plot can then be employed as an index of self-similarity. In short, α ≈ 0.5 corresponds to a random, non-correlated, non-similar structure of variability (i.e., white noise); α ≈ 1 corresponds to self-similar, long-range correlated or persistent structures of variability (i.e., known as fractal or pink noise); and α ≈ 1.5 corresponds to highly persistent and correlated patterns of Brownian variability (i.e., so-called Brown noise), with most time series of human behavioural fluctuations typically resulting in 0.5 < α < 1.5 11,17,18 .…”

Section: The Structure Of Behavioural Variabilitymentioning

confidence: 99%

“…Importantly, the degree to which human behavioural variability is non-random or self-similar is assumed to reflect the complexity or nested interdependence of the sensorimotor, cognitive, social and environmental processes that define a given task context 11 . Consistent with this assumption, there is now a growing body of research demonstrating how the structure of behavioural fluctuations varies across different experimental manipulations and tasks constraints 10,12,14,[19][20][21][22] .…”

Section: The Structure Of Behavioural Variabilitymentioning

confidence: 99%

Co-actors Exhibit Similarity in Their Structure of Behavioural Variation That Remains Stable Across Range of Naturalistic Activities

Rigoli

Lorenz

Coey

et al. 2020

Sci Rep

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Human behaviour, along with any natural/biological behaviour, has varying degrees of intrinsic 'noise' or variability. Many studies have shown that the structure or patterning of this variability is sensitive to changes in task and constraint. Furthermore, two or more humans interacting together often begin to exhibit similar structures of behavioural variability (i.e., the patterning of their behavioural fluctuations becomes aligned or matched) independent of any moment-to-moment synchronization (termed complexity matching). However, much of the previous work has focused on a subset of simple or contrived behaviours within the context of highly controlled laboratory tasks. In the current study, individuals and pairs performed five self-paced (unsupervised), semi-structured activities around a university campus. Empatica E4 wristbands and iPhones were used to record the participants' behavioural activity via accelerometers and GpS. the results revealed that the structure of variability in naturalistic human behaviour co-varies with the task-goal constraints, and that the patterning of the behavioural fluctuations exhibited by co-acting individuals does become aligned during the performance of everyday activities. The results also revealed that the degree of complexity matching that occurred between pairs remained invariant across activity type, indicating that this measure could be employed as a robust, task-independent index of interpersonal behaviour. When measuring any human movement or behaviour over time, the resulting measurements always contain various magnitudes of natural variability. This is true whether one considers an individual's reaction times to repeated environmental stimuli 1 , the spatial accuracy of an individual when hitting a nail with a hammer 2,3 , or an individual's stride length when walking or running 4,5. Even an individual's head and postural position while sitting or standing still fluctuates over time 6. Traditionally, such behavioural variation was assumed to be random or non-functional sensorimotor or measurement 'noise' 7-9. However, there is now a growing body of research demonstrating that the behavioural fluctuations that occur during natural human activity are typically correlated over time (i.e., exhibit varying degrees of self-similarity and non-randomness) 1,10-13. Of particular relevance here, is that research exploring the patterning of human behavioural variability has demonstrated how the structure of such variation is sensitive to changes in task and environmental constraint, with some patterns of behavioural variance being more or less random than others 11,12,14. Recent research suggests that the patterning of co-actors' behavioural variability can also become aligned or 'matched' together during task performance, even when the movements or actions of the co-actors are not locally synchronized or coordinated. This latter phenomenon has been termed complexity matching and implies that the behavioural actions and movements of co-acting individuals can become entrained...

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Living in the Pink

Cited by 71 publications

References 157 publications

Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

How to Sync to the Beat of a Persistent Fractal Metronome without Falling Off the Treadmill?

Co-actors Exhibit Similarity in Their Structure of Behavioural Variation That Remains Stable Across Range of Naturalistic Activities

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