Self-organization in the movement activity of social insects (Hymenoptera: Formicidae)

Neves, Felipe Marcel; Pie, Márcio R.; Viana, Ricardo L.

doi:10.1063/1.4756220

Cited by 4 publications

(4 citation statements)

References 17 publications

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“…The recurrence analysis permits further investigations to understand deeply patterns within time series. For instance, preliminary results indicate a progress to a more deterministic behavior with increasing densities, however by very different processes [ 62 ]. Our first study using recurrence plots and recurrence quantification analysis in animal behavior suggests that the activity dynamics of ants are composed by a plethora of complex patterns that ranges from stochastics signals and degrees of predictability.…”

Section: Discussionmentioning

confidence: 99%

Recurrence analysis of ant activity patterns

2017

Self Cite

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In this study, we used recurrence quantification analysis (RQA) and recurrence plots (RPs) to compare the movement activity of individual workers of three ant species, as well as a gregarious beetle species. RQA and RPs quantify the number and duration of recurrences of a dynamical system, including a detailed quantification of signals that could be stochastic, deterministic, or both. First, we found substantial differences between the activity dynamics of beetles and ants, with the results suggesting that the beetles have quasi-periodic dynamics and the ants do not. Second, workers from different ant species varied with respect to their dynamics, presenting degrees of predictability as well as stochastic signals. Finally, differences were found among minor and major caste of the same (dimorphic) ant species. Our results underscore the potential of RQA and RPs in the analysis of complex behavioral patterns, as well as in general inferences on animal behavior and other biological phenomena.

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Section: Discussionmentioning

confidence: 99%

Recurrence analysis of ant activity patterns

2017

Self Cite

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“…They were introduced by Eckmann et al [14], and are frequently used in time series research and applications. A few instances are the analysis of social insects behavior [29], protein structural prediction [31], stock market analysis [2], and multimodal communicative signals analysis [10]. One field of study that the use of recurrence plot is relatively common is the analysis of biological signals.…”

Section: Related Workmentioning

confidence: 99%

Time Series Classification Using Compression Distance of Recurrence Plots

Silva

Souza²,

Batista

2013

2013 IEEE 13th International Conference on Data Mining

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Abstract-There is a huge increase of interest for time series methods and techniques. Virtually every piece of information collected from human, natural, and biological processes is susceptible to changes over time, and the study of how these changes occur is a central issue in fully understanding such processes. Among all time series mining tasks, classification is likely to be the most prominent one. In time series classification there is a significant body of empirical research that indicates that k-nearest neighbor rule in the time domain is very effective. However, certain time series features are not easily identified in this domain and a change in representation may reveal some significant and unknown features. In this work, we propose the use of recurrence plots as representation domain for time series classification. Our approach measures the similarity between recurrence plots using Campana-Keogh (CK-1) distance, a Kolmogorov complexitybased distance that uses video compression algorithms to estimate image similarity. We show that recurrence plots allied to CK-1 distance lead to significant improvements in accuracy rates compared to Euclidean distance and Dynamic Time Warping in several data sets. Although recurrence plots cannot provide the best accuracy rates for all data sets, we demonstrate that we can predict ahead of time that our method will outperform the time representation with Euclidean and Dynamic Time Warping distances.

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“…In social animals, the study of interactive behaviors is crucial, because conspecifics are a vital element of the animal’s niche, providing the lion’s share of stimulation and structure that influences individual behavior (Calhoun, 2016; Schweinfurth, 2020). Thus, it is likely from the study of intra- and interspecific interactions, and not only the individual animals themselves, that we can learn inter alia about the mechanisms for such complex behaviors as collective action hunting, mating behavior, play-fighting, agonistic behavior, or establishment of group hierarchies (for examples of their complexity, see Blanchard, Flannelly, & Blanchard, 1988; Diakow, 1975; MacNulty, Mech, & Smith, 2007; Neves, Pie, & Viana, 2012; Pellis & Pellis, 2007, 2015; Reznikova, Levenets, Panteleeva, & Ryabko, 2017).…”

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confidence: 99%

Recurrence quantification analysis in the study of online coordination in Norway rats (Rattus norvegicus).

Pérez

Stryjek

Rączaszek-Leonardi

2021

Journal of Comparative Psychology

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In social animals, studying interactions with conspecifics is crucial for understanding even basic physiological, behavioral, and cognitive processes. Due to a visible “ecological turn” in behavioral research, we observe a rapid development of novel methods devoted to studying interaction. In this article, we offer a case study of an animal interactive behavior, which uses new methods of video-recorded motion capturing combined with time-series analysis called recurrence quantification analysis. We apply the method to the video-recorded behavioral sequence observed in Rattus norvegicus to evidence the fine-grained structure of this behavior. We show how such dynamical analyses can lead to insights about the processes behind such behavioral patterns and their change. Finally, we show how this approach can be successfully applied to other examples of highly coordinated behaviors in the animal world.

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Self-organization in the movement activity of social insects (Hymenoptera: Formicidae)

Cited by 4 publications

References 17 publications

Recurrence analysis of ant activity patterns

Recurrence analysis of ant activity patterns

Time Series Classification Using Compression Distance of Recurrence Plots

Recurrence quantification analysis in the study of online coordination in Norway rats (Rattus norvegicus).

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