Recurrence quantification as an analysis of temporal coordination with complex signals

Charles A. Coey, Auriel Washburn, Michael J. Richardson

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

7 Citations (Scopus)

Abstract

Ample past research demonstrates that human rhythmic behavior and rhythmic coordination reveal complex dynamics. More recently, researchers have begun to examine the dynamics of coordination with complex, fractal signals. Here, we present preliminary research investigating how recurrence quantification techniques might be applied to study temporal coordination with complex signals. Participants attempted to synchronize their rhythmic finger tapping behavior with metronomes with varying fractal scaling properties. The results demonstrated that coordination, as assessed by recurrence analyses, differed with the fractal scaling of the metronome stimulus. Overall, these results suggest that recurrence analyses may aid in understanding temporal coordination between complex systems.
Original languageEnglish
Title of host publicationTranslational recurrences
Subtitle of host publicationfrom mathematical theory to real-world applications
EditorsNorbert Marwan, Michael Riley, Alessandro Giuliani, Charles L. Webber, Jr
Place of PublicationCham
PublisherSpringer, Springer Nature
Pages173-186
Number of pages14
ISBN (Electronic)9783319095318 , 3319095315
ISBN (Print)9783319095301 , 3319095307
DOIs
Publication statusPublished - 2014
Externally publishedYes
EventInternational Symposium on Recurrence Plots (5th : 2013) - Chicago, United States
Duration: 14 Aug 201316 Aug 2013

Publication series

NameSpringer proceedings in mathematics & statistics
Volume103
ISSN (Print)2194-1009
ISSN (Electronic)2194-1017

Conference

ConferenceInternational Symposium on Recurrence Plots (5th : 2013)
CountryUnited States
CityChicago
Period14/08/1316/08/13

Fingerprint

Dive into the research topics of 'Recurrence quantification as an analysis of temporal coordination with complex signals'. Together they form a unique fingerprint.

Cite this