Behavioral organization of locomotor activity and its modeling
Behavioral organization of locomotor activity and its modeling
复制标题
运动活动的行为组织及其建模
DOI：
10.1109/scis-isis.2012.6505400
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Y. Yamamoto
中科院分区：
文献类型：
--
作者：
T. Nakamura;Y. Yamamoto
最近，我们研究了人类和小鼠运动活动的动力学特性，发现了两种物种共有的行为组织的统计规律。具体来说，我们研究了休息和活跃期是如何交织在日常生活中，并发现，身体活动计数连续高于预定义的阈值的活跃期持续时间遵循拉伸指数（γ型）累积分布的特征时间，无论是在健康个体和重度抑郁症患者。相反，两组低于阈值的静息期持续时间在20年内服从无标度幂律累积分布，患者的标度指数显着降低。此外，我们还发现了患有重度抑郁症的人类和消除了生物钟基因的小鼠的统计规律的共同崩溃。这些发现表明存在一个基本的原则，管理行为组织，并有望促进神经行为疾病，包括抑郁症的病理生理学的理解。在本文中，我们回顾了我们以前的论文中报道的行为组织的统计规律，并通过一个基于优先级的排队模型讨论了其出现和崩溃的可能解释，该模型最初是为了解释社会人类行为的突发性，如电子邮件通信，网络浏览和贸易交易。
Recently, we have studied the dynamical properties of locomotor activity in both humans and mice, and discovered identical statistical laws of behavioral organization shared with both species. Specifically, we examined how resting and active periods were interwoven in daily life, and found that active period durations with physical activity counts successively above a predefined threshold followed a stretched exponential (gamma-type) cumulative distribution with characteristic time, both in healthy individuals and in patients with major depressive disorder. On the contrary, resting period durations below the threshold for both groups obeyed a scale free power-law cumulative distribution over two decades, with significantly lower scaling exponents in the patients. Furthermore, we also discovered a shared breakdown of the statistical law in humans suffering from major depressive disorders and mice with a circadian clock gene eliminated. These findings suggest the presence of an underlying principle governing behavioral organization, and are expected to facilitate the understanding of the pathophysiology of neurobehavioral diseases, including depression. In this paper, we review the statistical laws of behavioral organization reported in our previous paper and discuss a possible explanation for its emergence and breakdown through a priority-based queuing model originally developed to explain the bursty nature of social human behavior, such as email communications, web-browsing, and trade transactions.