Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA) – A Method for Quantifying Correlation between Multivariate Time-Series

Abstract In this paper, Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA) is introduced. It is an extension of Multidimensional Recurrence Quantification Analysis (MdRQA), which allows to quantify the (auto-)recurrence properties of a single multidimensional time-series. MdCRQA extends MdRQA to bi-variate cases to allow for the quantification of the co-evolution of two multidimensional time-series. Moreover, it is shown how a Diagonal Cross-Recurrence Profile (DCRP) can be computed from the MdCRQA output that allows to capture time-lagged coupling between two multidimensional time-series. The core concepts of these analyses are described, as well as practical aspects of their application. In the supplementary materials to this paper, implementations of MdCRQA and the DCRP as MatLab- and R-functions are provided.

[1]  Joseph A. Bulbulia,et al.  Synchronized arousal between performers and related spectators in a fire-walking ritual , 2011, Proceedings of the National Academy of Sciences.

[2]  O. Rössler An equation for continuous chaos , 1976 .

[3]  Mehmet Emre Çek,et al.  Analysis of observed chaotic data , 2004 .

[4]  J. Gilkerson,et al.  Vocal interaction dynamics of children with and without autism , 2010 .

[5]  Charles L. Webber,et al.  Cross recurrence quantification of coupled oscillators , 2002 .

[6]  Daniel C. Richardson,et al.  The Dynamics of Reference and Shared Visual Attention , 2011, Front. Psychology.

[7]  Michael J. Richardson,et al.  Articulatory constraints on interpersonal postural coordination. , 2007, Journal of experimental psychology. Human perception and performance.

[8]  Sebastian Wallot,et al.  Beyond Synchrony: Joint Action in a Complex Production Task Reveals Beneficial Effects of Decreased Interpersonal Synchrony , 2016, PloS one.

[9]  Sebastian Wallot,et al.  Multidimensional Recurrence Quantification Analysis (MdRQA) for the Analysis of Multidimensional Time-Series: A Software Implementation in MATLAB and Its Application to Group-Level Data in Joint Action , 2016, Front. Psychol..

[10]  E. Lorenz Deterministic nonperiodic flow , 1963 .

[11]  K. Shockley,et al.  Mutual interpersonal postural constraints are involved in cooperative conversation. , 2003, Journal of experimental psychology. Human perception and performance.

[12]  Sebastian Wallot,et al.  Analyzing Multivariate Dynamics Using Cross-Recurrence Quantification Analysis (CRQA), Diagonal-Cross-Recurrence Profiles (DCRP), and Multidimensional Recurrence Quantification Analysis (MdRQA) – A Tutorial in R , 2018, Front. Psychol..

[13]  Riccardo Fusaroli,et al.  Investigating Conversational Dynamics: Interactive Alignment, Interpersonal Synergy, and Collective Task Performance , 2016, Cogn. Sci..

[14]  Sebastian Wallot,et al.  Using complexity metrics with R-R intervals and BPM heart rate measures , 2013, Front. Physiol..

[15]  Jürgen Kurths,et al.  Recurrence plots for the analysis of complex systems , 2009 .

[16]  Sebastian Wallot,et al.  A Tutorial Introduction to Recurrence Quantification Analysis (RQA) for Keystroke Logging Data , 2019 .

[17]  Sebastian Wallot,et al.  Calculation of Average Mutual Information (AMI) and False-Nearest Neighbors (FNN) for the Estimation of Embedding Parameters of Multidimensional Time Series in Matlab , 2018, Front. Psychol..

[18]  Iris Nomikou,et al.  Constructing Interaction: The Development of Gaze Dynamics , 2016 .

[19]  Rick Dale,et al.  Behavior Matching in Multimodal Communication Is Synchronized , 2012, Cogn. Sci..

[20]  Sebastian Wallot,et al.  Recurrence Quantification Analysis of Processes and Products of Discourse: A Tutorial in R , 2017 .

[21]  J. Eskildsen,et al.  Physiological evidence of interpersonal dynamics in a cooperative production task , 2016, Physiology & Behavior.

[22]  Alessandro Giuliani,et al.  Combinatorics and synchronization in natural semiotics , 2006 .

[23]  Daniel C. Richardson,et al.  Nominal Cross Recurrence as a Generalized Lag Sequential Analysis for Behavioral Streams , 2011, Int. J. Bifurc. Chaos.

[24]  Daniel C. Richardson,et al.  Looking To Understand: The Coupling Between Speakers' and Listeners' Eye Movements and Its Relationship to Discourse Comprehension , 2005, Cogn. Sci..

[25]  F. Takens Detecting strange attractors in turbulence , 1981 .

[26]  Moreno I. Coco,et al.  Cross-recurrence quantification analysis of categorical and continuous time series: an R package , 2013, Front. Psychol..

[27]  K. Shockley Cross Recurrence Quantification of Interpersonal Postural Activity , 2004 .

[28]  A. O. Adelakun,et al.  Comparative study on Radio Refractivity Gradient in the troposphere using Chaotic Quantifiers , 2019, Heliyon.

[29]  Riccardo Fusaroli,et al.  Analyzing Social Interactions: The Promises and Challenges of Using Cross Recurrence Quantification Analysis , 2014 .

[30]  Christopher T. Kello,et al.  Multiple Coordination Patterns in Infant and Adult Vocalizations. , 2017, Infancy : the official journal of the International Society on Infant Studies.

[31]  James P. Crutchfield,et al.  Geometry from a Time Series , 1980 .

[32]  Sebastian Wallot,et al.  A tutorial introduction to fractal and recurrence analyses of reading , 2012 .

[33]  H. Abarbanel,et al.  Determining embedding dimension for phase-space reconstruction using a geometrical construction. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[34]  Alexandra Paxton,et al.  Movement dynamics reflect a functional role for weak coupling and role structure in dyadic problem solving , 2015, Cognitive Processing.

[35]  Moreno I. Coco,et al.  Performance in a Collaborative Search Task: The Role of Feedback and Alignment , 2018, Top. Cogn. Sci..