Universal Scaling Law in Human Behavioral Organization

Nakamura, Tôru; Kiyono, Ken; Yoshiuchi, Kazuhiro; Nakahara, Rika; Struzik, Zbigniew R.; Yamamoto, Yoshiharu

doi:10.1103/physrevlett.99.138103

Cited by 139 publications

(238 citation statements)

References 15 publications

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“…Let us note that for human ͑arm͒ motor activity data, instead of two exponentials, a stretched exponential fit was reported. 7,9 Meanwhile, quiescence intervals are also power law distributed with exponent . Because motion intervals are in average much shorter than quiet ones, then, the statistics of interevent times is mainly dominated by that of immobility periods, in particular, sharing the same power-law decay.…”

Section: A Interevent Intervalsmentioning

confidence: 99%

“…The simplest example probably is the temporal spacing between -even inconsequential-motor activities, which appears to be scale-free. [6][7][8][9] Despite these recent efforts the mechanisms behind such statistical behavior are not understood yet. This lack of plausible models calls for alternatives which can be helpful to identify the mechanisms at work.…”

Section: Introductionmentioning

confidence: 99%

“…[6][7][8] The interest in the topic is triggered by the existence of a seemingly common feature, namely, the heavy tails of the waiting and interevent time distributions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Unraveling the fluctuations of animal motor activity

Anteneodo¹,

Chialvo²

2009

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Human and animal behavior exhibits power law correlations whose origin is controversial. In this work, the spontaneous motion of laboratory rodents was recorded during several days. It is found that animal motion is scale-free and that the scaling is introduced by the inactivity pauses both by its length as well as by its specific ordering. Furthermore, the scaling is also demonstrable in the rates of event's occurrence. A comparison with related results in humans is made and candidate models are discussed to provide clues for the origin of such dynamics. © 2009 American Institute of Physics. ͓DOI: 10.1063/1.3211189͔ Recent findings of heavy tailed distributions in the patterns of human activity reemphasized our poor understanding on the mechanisms responsible for such type of dynamics. To shed light on the most significant features of these fluctuations, the problem is here oversimplified by studying a much elementary system: the spontaneous motion of rodents recorded during several days. The analysis of the animal motion reveals a robust scaling not only in univariate distributions, comparable with the results previously reported in humans, but also in its correlation structure. It is shown that the most relevant features of the experimental results can be replicated by the statistics of the activation-threshold model proposed in another context by Davidsen and Schuster. It constitutes an alternative mechanism to queuing, cascading, and nonhomogeneous processes, currently contemplated as candidates to account for the statistics of diverse human activities, but that seem not suitable for motion patterns.

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Section: A Interevent Intervalsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Unraveling the fluctuations of animal motor activity

Anteneodo¹,

Chialvo²

2009

Chaos: An Interdisciplinary Journal of Nonlinear Science

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“…Nakamura et al investigated daily body movements of healthy people and patients with a major depression using accelerometers [41], [42]. They found a universal distribution of periods of high and low body movements.…”

Section: Discussionmentioning

confidence: 99%

“…We focused on upper-body movements of people because this is also the focus in the field of daily human behavior on different time scales [10], [11], [41], [42]. We calculated the amount of upper-body movements by the same procedure as in the previous study [12].…”

Section: Introductionmentioning

confidence: 99%

Interpersonal Coevolution of Body Movements in Daily Face-to-Face Communication

Ogata

Higo

Nozawa

et al. 2017

IEICE Trans. Inf. & Syst.

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SUMMARYPeople's body movements in daily face-to-face communication influence each other. For instance, during a heated debate, the participants use more gestures and other body movements, while in a calm discussion they use fewer gestures. This "coevolution" of interpersonal body movements occurs on multiple time scales, like minutes or hours. However, the multi-time-scale coevolution in daily communication is not clear yet.In this paper, we explore the minute-to-minute coevolution of interpersonal body movements in daily communication and investigate the characteristics of this coevolution. We present quantitative data on upper-body movements from thousand test subjects from seven organizations gathered over several months via wearable sensors. The device we employed measured upperbody movements with an accelerometer and the duration of face-to-face communication with an infrared ray sensor on a minute-by-minute basis. We defined a coevolution measure between two people as the number of per-minute changes of their body movement and compared the indices for face-to-face and non-face-to-face situations. We found that on average, the amount of people's body movements changed correspondingly for face-toface communication and that the average rate of coevolution in the case of face-to-face communication was 3-4% higher than in the case of nonface-to-face situation. These results reveal minute-to-minute coevolution of upper-body movements between people in daily communication. The finding suggests that the coevolution of body movement arises in multiple time scales.

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Critical Brain Dynamics at Large Scale

Chialvo

2014

Criticality in Neural Systems

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Essentially, all modeling of brain function from studying models of neural networks has ignored the self-organized aspects of the process, but has concentrated on designing a working brain by engineering all the connections of inputs and outputs.Per Bak[1]Abstract -Highly correlated brain dynamics produces synchronized states with no behavioral value, while weakly correlated dynamics prevent information flow. In between these states, the unique dynamical features of the critical state endow the brain with properties which are fundamental for adaptive behavior. We discuss the idea put forward two decades ago by Per Bak that the working brain stays at an intermediate (critical) regime characterized by power-law correlations. This proposal is now supported by a wide body of empirical evidence at different scales demonstrating that the spatiotemporal brain dynamics exhibit key signatures of critical dynamics, previously recognized in other complex systems. The rationale behind this program is discussed in these notes, followed by an account of the most recent results.In "Criticality in Neural Systems", Niebur E, Plenz D, Schuster HG. (eds.) 2013 (in press).

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Universal Scaling Law in Human Behavioral Organization

Cited by 139 publications

References 15 publications

Unraveling the fluctuations of animal motor activity

Unraveling the fluctuations of animal motor activity

Interpersonal Coevolution of Body Movements in Daily Face-to-Face Communication

Critical Brain Dynamics at Large Scale

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