The development of locomotor kinematics in neonatal rats: an agent-based modeling analysis in group and individual contexts

Modelling the emergence of rodent filial huddling from physiological huddling

Huddling behaviour in neonatal rodents reduces the metabolic costs of physiological thermoregulation. However, animals continue to huddle into adulthood, at ambient temperatures where they are able to sustain a basal metabolism in isolation from the huddle. This 'filial huddling' in older animals is known to be guided by olfactory rather than thermal cues. The present study aimed to test whether thermally rewarding contacts between young mice, experienced when thermogenesis in brown adipose fat tissue (BAT) is highest, could give rise to olfactory preferences that persist as filial huddling interactions in adults. To this end, a simple model was constructed to fit existing data on the development of mouse thermal physiology and behaviour. The form of the model that emerged yields a remarkable explanation for filial huddling; associative learning maintains huddling into adulthood via processes that reduce thermodynamic entropy from BAT metabolism and increase information about social ordering among littermates.

The (Mathematical) Modeling Process in Biosciences

In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology.

Theory development with agent-based models

Many social phenomena do not result solely from intentional actions by isolated individuals, but rather emerge as the result of repeated interactions among multiple individuals over time. However, such phenomena are often poorly captured by traditional empirical techniques. Moreover, complex adaptive systems are insufficiently described by verbal models. In this paper, we discuss how organizational psychologists and group dynamics researchers may benefit from the adoption of formal modeling, particularly agent-based modeling, for developing and testing richer theories. Agent-based modeling is well suited to capture multilevel dynamic processes and offers superior precision to verbal models. As an example, we present a model of social identity dynamics used to test the predictions of Brewer’s (1991) optimal distinctiveness theory, and discuss how the model extends the theory and produces novel research questions. We close with a general discussion on theory development using agent-based models.

A Self-Organising Model of Thermoregulatory Huddling

Endotherms such as rats and mice huddle together to keep warm. The huddle is considered to be an example of a self-organising system, because complex properties of the collective group behaviour are thought to emerge spontaneously through simple interactions between individuals. Groups of rodent pups display two such emergent properties. First, huddling undergoes a 'phase transition', such that pups start to aggregate rapidly as the temperature of the environment falls below a critical temperature. Second, the huddle maintains a constant 'pup flow', where cooler pups at the periphery continually displace warmer pups at the centre. We set out to test whether these complex group behaviours can emerge spontaneously from local interactions between individuals. We designed a model using a minimal set of assumptions about how individual pups interact, by simply turning towards heat sources, and show in computer simulations that the model reproduces the first emergent property--the phase transition. However, this minimal model tends to produce an unnatural behaviour where several smaller aggregates emerge rather than one large huddle. We found that an extension of the minimal model to include heat exchange between pups allows the group to maintain one large huddle but eradicates the phase transition, whereas inclusion of an additional homeostatic term recovers the phase transition for large huddles. As an unanticipated consequence, the extended model also naturally gave rise to the second observed emergent property--a continuous pup flow. The model therefore serves as a minimal description of huddling as a self-organising system, and as an existence proof that group-level huddling dynamics emerge spontaneously through simple interactions between individuals. We derive a specific testable prediction: Increasing the capacity of the individual to generate or conserve heat will increase the range of ambient temperatures over which adaptive thermoregulatory huddling will emerge.

Movement patterns, social dynamics, and the evolution of cooperation

The structure of social interactions influences many aspects of social life, including the spread of information and behavior, and the evolution of social phenotypes. After dispersal, organisms move around throughout their lives, and the patterns of their movement influence their social encounters over the course of their lifespan. Though both space and mobility are known to influence social evolution, there is little analysis of the influence of specific movement patterns on evolutionary dynamics. We explored the effects of random movement strategies on the evolution of cooperation using an agent-based prisoner's dilemma model with mobile agents. This is the first systematic analysis of a model in which cooperators and defectors can use different random movement strategies, which we chose to fall on a spectrum between highly exploratory and highly restricted in their search tendencies. Because limited dispersal and restrictions to local neighborhood size are known to influence the ability of cooperators to effectively assort, we also assessed the robustness of our findings with respect to dispersal and local capacity constraints. We show that differences in patterns of movement can dramatically influence the likelihood of cooperator success, and that the effects of different movement patterns are sensitive to environmental assumptions about offspring dispersal and local space constraints. Since local interactions implicitly generate dynamic social interaction networks, we also measured the average number of unique and total interactions over a lifetime and considered how these emergent network dynamics helped explain the results. This work extends what is known about mobility and the evolution of cooperation, and also has general implications for social models with randomly moving agents.

The role of orienting in vibrissal touch sensing

Rodents, such as rats and mice, are strongly tactile animals who explore the environment with their long mobile facial whiskers, or macrovibrissae, and orient to explore objects further with their shorter, more densely packed, microvibrissae. Although whisker motion (whisking) has been extensively studied, less is known about how rodents orient their vibrissal system to investigate unexpected stimuli. We describe two studies that address this question. In the first we seek to characterize how adult rats orient toward unexpected macrovibrissal contacts with objects and examine the microvibrissal exploration behavior following such contacts. We show that rats orient to the nearest macrovibrissal contact on an unexpected object, progressively homing in on the nearest contact point on the object in each subsequent whisk. Following contact, rats "dab" against the object with their microvibrissae at an average rate of approximately 8 Hz, which suggests synchronization of microvibrissal dabbing with macrovibrissal motion, and an amplitude of 5 mm. In study two, we examine the role of orienting to tactile contacts in developing rat pups for maintaining aggregations (huddles). We show that young pups are able to orient to contacts with nearby conspecifics before their eyes open implying an important role for the macrovibrissae, which are present from birth, in maintaining contact with conspecifics. Overall, these data suggest that orienting to tactile cues, detected by the vibrissal system, plays a crucial role throughout the life of a rat.

Observe, simplify, titrate, model, and synthesize: a paradigm for analyzing behavior

Phenomena in behavior and their underlying neural mechanisms are exquisitely complex problems. Infrequently do we reflect on our basic strategies of investigation and analysis, or formally confront the actual challenges of achieving an understanding of the phenomena that inspire research. Philip Teitelbaum is distinct in his elegant approaches to understanding behavioral phenomena and their associated neural processes. He also articulated his views on effective approaches to scientific analyses of brain and behavior, his vision of how behavior and the nervous system are patterned, and what constitutes basic understanding. His rubrics involve careful observation and description of behavior, simplification of the complexity, analysis of elements, and re-integration through different forms of synthesis. Research on the development of huddling behavior by individual and groups of rats is reviewed in a context of Teitelbaum's rubrics of research, with the goal of appreciating his broad and positive influence on the scientific community.