2016
DOI: 10.1007/978-3-319-29922-8_11
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Chromatic and Anisotropic Cross-Recurrence Quantification Analysis of Interpersonal Behavior

Abstract: Cross-recurrence quantification analysis (CRQA) is a powerful nonlinear time-series method to study coordination and cooperation between people. This chapter concentrates on two methodological issues related to CRQA on categorical data streams, which are commonly encountered in the behavioral sciences. Firstly, we introduce a more general definition of recurrence as 'behavioral matching', which can be applied to several kinds of matches simultaneously, visualized by a color coding. We will refer to this as cro… Show more

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Cited by 26 publications
(42 citation statements)
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“…Generally, such structures indicate instances where behaviors which are briefly expressed by one subsystem are accompanied by episodes of lingering in the matching behavior by the other subsystem. This provides information about the shared dynamics of the gesture–speech interaction, and specifically about the strength and direction of the coupling between the two subsystems, as we shall demonstrate (see Cox et al, 2016 ). Thus far, research using CRQA has focused on diagonal and vertical lines.…”
Section: Methodsmentioning
confidence: 65%
See 1 more Smart Citation
“…Generally, such structures indicate instances where behaviors which are briefly expressed by one subsystem are accompanied by episodes of lingering in the matching behavior by the other subsystem. This provides information about the shared dynamics of the gesture–speech interaction, and specifically about the strength and direction of the coupling between the two subsystems, as we shall demonstrate (see Cox et al, 2016 ). Thus far, research using CRQA has focused on diagonal and vertical lines.…”
Section: Methodsmentioning
confidence: 65%
“…To capture the asymmetric dynamic attunement between gestures and speech, we performed anisotropic CRQA ( Cox et al, 2016 ), by calculating recurrence measures for the horizontal and vertical line structures separately and comparing them. The first measure derived from the line structures is ‘Laminarity,’ defined as the proportion of recurrent points that are part of a vertical (LAM V ) or horizontal (LAM H ) line structure.…”
Section: Methodsmentioning
confidence: 99%
“…captures the unpredictability of a system's state (i.e., behavioral category). We calculated Shannon entropy by means of the following formula: Recurrence -the re-occurrence of states over time -is a central property of complex dynamical systems, such as the weather, mechanical engines, and also humans (Abney et al, 2014;Cox et al, 2016;Riley & Turvey, 2002;Wijnants et al, 2012). These recurrences are represented in a Recurrence Plot (RP), which, for categorical time series, is created by plotting that time series against itself in a plane and marking all instances that pertain to the same state in x and y with a dot (see Figure 3, panel d).…”
Section: Discussionmentioning
confidence: 99%
“…The Shannon entropy of the frequency HAND MOVEMENTS, SPEECH, AND TASK PROPERTIES [PREPRINT] 17 distribution of the diagonal line lengths gives a measure of complexity of the system (Pellecchia & Shockley, 2005;Webber Jr. & Zbilut, 2005). However, in categorical RQA, vertical and horizontal lines (Cox et al, 2016;Xu et al, 2020), and the rectangular block structures (Leonardi, 2018), are much more informative about a system's dynamics, instead of diagonal lines (also see Figure 3, panel d). Therefore, the Shannon entropy of the frequency distribution of the size of the block structures in the RP is better measure of a system's Complexity, specifically suited for categorical data (Leonardi, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…Interrater agreements for assistance provided by mothers, exploratory utensil use by infants, and feeding-relevant utensil use by infants were k D :80, :71, and :78, respectively. The methods of cross-recurrence quantification analysis used in this part of the investigation have been described in detail elsewhere (Cox, van der Steen, Guevara, de Jonge-Hoekstra, & van Dijk, 2016;Warlaumont et al, 2014).…”
Section: Data Codingmentioning
confidence: 99%