Working Together: Integrating Computational Modeling Approaches to Investigate Complex Phenomena

Complex systems are made up of many entities, whose interactions emerge into distinct collective patterns. Computational modeling platforms can provide a powerful means to investigate emergent phenomena in complex systems. Some research has been carried out in recent years about promoting students' modeling practices, specifically using technologically advanced tools and approaches that allow students to create, manipulate, and test computational models. However, not much research had been carried out on the integration of several modeling approaches when investigating complex phenomena. In this paper, we describe the design principles used to develop a middle school unit about ants' collective behavior that integrates three modeling approaches: conceptual drawn models, agent-based models, and system dynamics models. We provide results from an initial implementation of an 8th grade curricular unit, indicating that students engaged with several aspects of the modeling practice. Students' conceptual knowledge about ant pheromone communication increased following learning the unit. We also found gains in students' metamodeling knowledge about models as tools for investigating phenomena. We discuss the affordances and challenges of engaging students with several modeling approaches in science classroom

Ant collective cognition allows for efficient navigation through disordered environments

International audienceThe cognitive abilities of biological organisms only make sense in the context of their environment. Here, we study longhorn crazy ant collective navigation skills within the context of a semi-natural, randomized environment. Mapping this biological setting into the ‘Ant-in-a-Labyrinth’ framework which studies physical transport through disordered media allows us to formulate precise links between the statistics of environmental challenges and the ants’ collective navigation abilities. We show that, in this environment, the ants use their numbers to collectively extend their sensing range. Although this extension is moderate, it nevertheless allows for extremely fast traversal times that overshadow known physical solutions to the ‘Ant-in-a-Labyrinth’ problem. To explain this large payoff, we use percolation theory and prove that whenever the labyrinth is solvable, a logarithmically small sensing range suffices for extreme speedup. Overall, our work demonstrates the potential advantages of group living and collective cognition in increasing a species’ habitable range

Short and Long Term Measures of Anxiety Exhibit Opposite Results

<div><p>Animal models of human diseases of the central nervous system, generalized anxiety disorder included, are essential for the study of the brain-behavior interface and obligatory for drug development; yet, these models fail to yield new insights and efficacious drugs. By increasing testing duration hundredfold and arena size tenfold, and comparing the behavior of the common animal model to that of wild mice, we raise concerns that chronic anxiety might have been measured at the wrong time, for the wrong duration, and in the wrong animal. Furthermore, the mice start the experimental session with a short period of transient adaptation to the novel environment (habituation period) and a long period reflecting the respective trait of the mice. Using common measures of anxiety reveals that mice exhibit opposite results during these periods suggesting that chronic anxiety should be measured during the post-habituation period. We recommend tools for measuring the transient period, and provide suggestions for characterizing the post habituation period.</p> </div

The dynamics of 4 classical measures of anxiety along the first 5 h in BALB/c (light gray) and wild (dark gray) mice.

<p>A: the percentage of time spent in the center of the arena, B: the percentage of time spent in the open area, C: Distance traveled (activity) per minute, D: percentage of time spent in arrest. Red vertical lines demarcate the end of the first half hour. Note that the trend, averaged over mice, shows a reversal in values of all 4 measures across the 5 h period and a consistent and large change across the first 1/2 h period, which is the maximal session length used in common studies of anxiety.</p

The stability of each of the anxiety measures is estimated by plotting the difference between the mean of the measure’s value in the first two hours and the overall mean for the period extending between 5 h and 45 h (first point in each graph), and then the standard deviation of fixed, non-overlapping blocks of 2 h, 3 h….7 h, all starting at the fifth hour (subsequent points in each graph).

<p>The stability of each of the anxiety measures is estimated by plotting the difference between the mean of the measure’s value in the first two hours and the overall mean for the period extending between 5 h and 45 h (first point in each graph), and then the standard deviation of fixed, non-overlapping blocks of 2 h, 3 h….7 h, all starting at the fifth hour (subsequent points in each graph).</p

Sequential Decision-Making in Ants and Implications to the Evidence Accumulation Decision Model

International audienceCooperative transport of large food loads by Paratrechina longicornis ants demands repeated decision-making. Inspired by the Evidence Accumulation (EA) model classically used to describe decision-making in the brain, we conducted a binary choice experiment where carrying ants rely on social information to choose between two paths. We found that the carried load performs a biased random walk that continuously alternates between the two options. We show that this motion constitutes a physical realization of the abstract EA model and exhibits an emergent version of the psychophysical Weber’s law. In contrast to the EA model, we found that the load’s random step size is not fixed but, rather, varies with both evidence and circumstances. Using theoretical modeling we show that variable step size expands the scope of the EA model from isolated to sequential decisions. We hypothesize that this phenomenon may also be relevant in neuronal circuits that perform sequential decisions

Freedom of movement and the stability of its unfolding in free exploration of mice

Exploration is a central component of human and animal behavior that has been studied in rodents for almost a century. The measures used by neuroscientists to characterize full-blown exploration are limited in exposing the dynamics of the exploratory process, leaving the morphogenesis of its structure and meaning hidden. By unfettering exploration from constraints imposed by hunger, thirst, coercion, and the confines of small cage and short session, using advanced computational tools, we reveal its meaning in the operational world of the mouse. Exploration consists of reiterated roundtrips of increasing amplitude and freedom, involving an increase in the number of independent dimensions along which the mouse moves (macro degrees of freedom). This measurable gradient can serve as a standard reference scale for the developmental dynamics of some aspects of the mouse's emotional-cognitive state and for the study of the interface between behavior and the neurophysiologic and genetic processes mediating it

Bi-stability in cooperative transport by ants in the presence of obstacles

<div><p>To cooperatively carry large food items to the nest, individual ants conform their efforts and coordinate their motion. Throughout this expedition, collective motion is driven both by internal interactions between the carrying ants and a response to newly arrived informed ants that orient the cargo towards the nest. During the transport process, the carrying group must overcome obstacles that block their path to the nest. Here, we investigate the dynamics of cooperative transport, when the motion of the ants is frustrated by a linear obstacle that obstructs the motion of the cargo. The obstacle contains a narrow opening that serves as the only available passage to the nest, and through which single ants can pass but not with the cargo. We provide an analytical model for the ant-cargo system in the constrained environment that predicts a bi-stable dynamic behavior between an oscillatory mode of motion along the obstacle and a convergent mode of motion near the opening. Using both experiments and simulations, we show how for small cargo sizes, the system exhibits spontaneous transitions between these two modes of motion due to fluctuations in the applied force on the cargo. The bi-stability provides two possible problem solving strategies for overcoming the obstacle, either by attempting to pass through the opening, or take large excursions to circumvent the obstacle.</p></div