Behavioral organization of locomotor activity and its modeling

摘要

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.