Fernandez Marie S A, Soula Hedi A, Mariette Mylene M, Vignal Clémentine
Univ Lyon, UJM-Saint-Etienne, Centre Nationnal de la Recherche Scientifique, Neuro-PSI/ENES UMR9197Saint-Etienne, France; EPI BEAGLE INRIAVilleurbanne, France.
EPI BEAGLE INRIAVilleurbanne, France; Institut National de la Santé et de la Recherche Médicale U1060 INSAVilleurbanne, France.
Front Psychol. 2016 Nov 29;7:1816. doi: 10.3389/fpsyg.2016.01816. eCollection 2016.
Social networks are often inferred from spatial associations, but other parameters like acoustic communication are likely to play a central role in within group interactions. However, it is currently difficult to determine which individual initiates vocalizations, or who responds to whom. To this aim, we designed a method that allows analyzing group vocal network while controlling for spatial networks, by positioning each group member in equidistant individual cages and analyzing continuous vocal interactions semi-automatically. We applied this method to two types of zebra finch groups, composed of either two adult females and two juveniles, or four young adults (juveniles from the first groups). Young often co-occur in the same social group as adults but are likely to have a different social role, which may be reflected in their vocal interactions. Therefore, we tested the hypothesis that the social structure of the group influences the parameters of the group vocal network. We found that groups including juveniles presented periods with higher level of activity than groups composed of young adults. Using two types of analyses (Markov analysis and cross-correlation), we showed that juveniles as well as adults were more likely to respond to individuals of their own age-class (i.e. to call one after another, in terms of turn-taking, and within a short time-window, in terms of time delay). When juveniles turned into adulthood, they showed adult characteristics of vocal patterns. Together our results suggest that vocal behavior changes during ontogeny, and individuals are more strongly connected with individuals of the same age-class within acoustic networks.
社交网络通常是从空间关联中推断出来的，但其他参数，如声学通讯，在群体内部互动中可能起着核心作用。然而，目前很难确定是哪个个体发起发声，或者谁对谁做出回应。为了实现这一目标，我们设计了一种方法，通过将每个群体成员放置在等距的单独笼子里，并半自动分析连续的发声互动，从而在控制空间网络的同时分析群体发声网络。我们将这种方法应用于两种类型的斑胸草雀群体，一种由两只成年雌性和两只幼鸟组成，另一种由四只年轻成年鸟（来自第一组的幼鸟）组成。幼鸟经常与成年鸟同处一个社会群体中，但它们可能具有不同的社会角色，这可能会在它们的发声互动中得到体现。因此，我们检验了这样一个假设，即群体的社会结构会影响群体发声网络的参数。我们发现，包含幼鸟的群体比由年轻成年鸟组成的群体有更高的活动水平时期。通过两种分析方法（马尔可夫分析和互相关分析），我们表明，幼鸟和成年鸟都更有可能对同年龄组的个体做出回应（即轮流发声，且在短时间窗口内存在时间延迟）。当幼鸟成长为成年鸟时，它们表现出成年鸟的发声模式特征。我们的研究结果共同表明，发声行为在个体发育过程中会发生变化，并且在声学网络中，个体与同年龄组的个体联系更为紧密。
