Strong anticipation: complexity matching in interpersonal coordination

Marmelat, Vivien; Delignières, Didier

doi:10.1007/s00221-012-3202-9

Cited by 95 publications

(141 citation statements)

References 49 publications

(16 reference statements)

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“…Namely, mean <t> and Aa yielded significant, positive coefficients (see Figure 6). In contrast to previous work (Marmelat & Delignieres, 2012), these findings demonstrate a relationship between local matchingphase synchrony in the current work-and complexity matching. If complexity matching is reliant on the local coupling between effectors, then increasingly different within-cycle dynamics should decrease such matching.…”

Section: Task Difficulty Modifies Complexity (Matching)contrasting

confidence: 83%

“…This value is divided by the period of the reference series. Effec tively, the close to 0° DRP found in Marmelat & Delignieres (2012) means that period matching was strong. This close period matching could have easily yielded their complexity matching results.…”

Section: Behaviorally Relevant Levels Of Controlmentioning

confidence: 91%

“…If such coupling is realizable, it is unnecessary to speak of one system as modeling another or dichotomizing local and global forms of coordination (Marmelat & Delignieres, 2012;Stephen et al, 2008Stephen et al, , 2011Studenka & Newell, 2013;Torre et al, 2103).…”

Section: Coordination From Coupling Dynamicsmentioning

confidence: 96%

“…This addition would not affect the correlation but would change Aa. This fact renders it unclear to what extent individual dyads matched complexity in past studies (Marmelat & Delignieres, 2012). Future studies would benefit from using both measures simultaneously.…”

Section: Behaviorally Relevant Levels Of Controlmentioning

confidence: 96%

“…This framework predicts that global tuning and local parameter adjustments (e.g., position, velocity or phase) can operate independently during coordination (Marmelat & Delignieres, 2012). Alternatively, we propose that complexity matching is a result of local phase adjustments during coordination Torre, Varlet, & Marmelat, 2013).…”

mentioning

confidence: 96%

See 4 more Smart Citations

Emergent complexity matching in interpersonal coordination: Local dynamics and global variability.

Fine

Likens

Amazeen

et al. 2015

Journal of Experimental Psychology: Human Perception and Perfor

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Rhythmic coordination with stimuli and other people's movements containing variable or unpredictable fluctuations might involve distinct processes: detecting the fluctuation structure and tuning to or matching the structure's temporal complexity. This framework predicts that global tuning and local parameter adjustments (e.g., position, velocity or phase) can operate independently during coordination (Marmelat & Delignières, 2012). Alternatively, we propose that complexity matching is a result of local phase adjustments during coordination (Delignières & Marmelat, 2014; Torre, Varlet, & Marmelat, 2013). The current study examined this relationship in a rhythmic interpersonal coordination task. Dyads coordinated swinging pendulums that differed in their uncoupled frequencies (detuning). We predicted that frequency detuning would require increased local corrections to maintain the intended phase pattern (in phase). This was expected to yield a relative phase shift accompanied by a change in period complexity and matching. Experimental data and numerical modeling of the pendulum dynamics confirmed our predictions. Increased relative phase shifts occurred simultaneously with increased dissociation between individuals' movement period complexity. This provided evidence that global complexity matching is intricately linked to local movement adjustments and is not a distinct coordination mechanism. These findings are considered with respect to dynamical and computational approaches to interpersonal coordination.

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Section: Task Difficulty Modifies Complexity (Matching)contrasting

confidence: 83%

Section: Behaviorally Relevant Levels Of Controlmentioning

confidence: 91%

Section: Coordination From Coupling Dynamicsmentioning

confidence: 96%

Section: Behaviorally Relevant Levels Of Controlmentioning

confidence: 96%

mentioning

confidence: 96%

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Emergent complexity matching in interpersonal coordination: Local dynamics and global variability.

Fine

Likens

Amazeen

et al. 2015

Journal of Experimental Psychology: Human Perception and Perfor

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Excessive and less complex body movement in children with autism during face‐to‐face conversation: An objective approach to behavioral quantification

et al. 2021

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The majority of existing studies investigating characteristics of overt social behavior in individuals with autism spectrum disorder (ASD) relied on informants' evaluation through questionnaires and behavioral coding techniques. As a novelty, this study aimed to quantify the complex movements produced during social interactions in order to test differences in ASD movement dynamics and their convergence, or lack thereof, during social interactions. Twenty children with ASD and twenty‐three children with typical development (TD) were videotaped while engaged in a face‐to‐face conversation with an interviewer. An image differencing technique was utilized to extract the movement time series. Spectral analyses were conducted to quantify the average power of movement, and the fractal scaling of movement. The degree of complexity matching was calculated to capture the level of behavioral coordination between the interviewer and children. Results demonstrated that the average power was significantly higher (p < 0.01), and the fractal scaling was steeper (p < 0.05) in children with ASD, suggesting excessive and less complex movement as compared to the TD peers. Complexity matching occurred between children and interviewers, but there was no reliable difference in the strength of matching between the ASD and TD children. Descriptive trends in the interviewer's behavior suggest that her movements adapted to match both ASD and TD movements equally well. The findings of our study might shed light on seeking novel behavioral markers of ASD, and on developing automatic ASD screening techniques during daily social interactions. Lay Summary By implementing an objective behavioral quantifying technique, our study demonstrated that children with autism had more body movement during face‐to‐face conversation, and they moved in a less complex way. The current diagnosis of autism heavily relies on doctor's experiences. These findings suggest a potential that autism might be automatically screened during daily social interactions.

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Cognitive science as complexity science

Favela

2020

WIRES Cognitive Science

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It is uncontroversial to claim that cognitive science studies many complex phenomena. What is less acknowledged are the contradictions among many traditional commitments of its investigative approaches and the nature of cognitive systems. Consider, for example, methodological tensions that arise due to the fact that like most natural systems, cognitive systems are nonlinear; and yet, traditionally cognitive science has relied on linear statistical data analyses. Cognitive science as complexity science is offered as an interdisciplinary framework for the investigation of cognition that can dissolve such contradictions and tensions. Here, cognition is treated as exhibiting the following four key features: emergence, nonlinearity, self‐organization, and universality. This framework integrates concepts, methods, and theories from such disciplines as systems theory, nonlinear dynamical systems theory, and synergetics. By adopting this approach, the cognitive sciences benefit from a common set of practices to investigate, explain, and understand cognition in its varied and complex forms. This article is categorized under: Computer Science > Neural Networks Psychology > Theory and Methods Philosophy > Foundations of Cognitive Science Neuroscience > Cognition

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Strong anticipation: complexity matching in interpersonal coordination

Abstract: Abstract

Cited by 95 publications

References 49 publications

Emergent complexity matching in interpersonal coordination: Local dynamics and global variability.

Emergent complexity matching in interpersonal coordination: Local dynamics and global variability.

Excessive and less complex body movement in children with autism during face‐to‐face conversation: An objective approach to behavioral quantification

Cognitive science as complexity science

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