Project description:Many animals, including humans, have evolved to live and move in groups. In humans, disrupted social interactions are a fundamental feature of many psychiatric disorders. However, we know little about how genes regulate social behavior. Zebrafish may serve as a powerful model to explore this question. By comparing the behavior of wild-type fish with 90 mutant lines, we show that mutations of genes associated with human psychiatric disorders can alter the collective behavior of adult zebrafish. We identify three categories of behavioral variation across mutants: "scattered," in which fish show reduced cohesion; "coordinated," in which fish swim more in aligned schools; and "huddled," in which fish form dense but disordered groups. Changes in individual interaction rules can explain these differences. This work demonstrates how emergent patterns in animal groups can be altered by genetic changes in individuals and establishes a framework for understanding the fundamentals of social information processing.
Project description:Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviors to population-level outcomes. In this paper, we introduce a simple generative model for the collective behavior of millions of social networking site users who are deciding between different software applications. Our model incorporates two distinct mechanisms: one is associated with recent decisions of users, and the other reflects the cumulative popularity of each application. Importantly, although various combinations of the two mechanisms yield long-time behavior that is consistent with data, the only models that reproduce the observed temporal dynamics are those that strongly emphasize the recent popularity of applications over their cumulative popularity. This demonstrates--even when using purely observational data without experimental design--that temporal data-driven modeling can effectively distinguish between competing microscopic mechanisms, allowing us to uncover previously unidentified aspects of collective online behavior.
Project description:Complex schooling behaviors result from local interactions among individuals. Yet, how sensory signals from neighbors are analyzed in the visuomotor stream of animals is poorly understood. Here, we studied aggregation behavior in larval zebrafish and found that over development larvae transition from overdispersed groups to tight shoals. Using a virtual reality assay, we characterized the algorithms fish use to transform visual inputs from neighbors into movement decisions. We found that young larvae turn away from virtual neighbors by integrating and averaging retina-wide visual occupancy within each eye, and by using a winner-take-all strategy for binocular integration. As fish mature, their responses expand to include attraction to virtual neighbors, which is based on similar algorithms of visual integration. Using model simulations, we show that the observed algorithms accurately predict group structure over development. These findings allow us to make testable predictions regarding the neuronal circuits underlying collective behavior in zebrafish.
Project description:Animal groups often make decisions sequentially, from the front to the back of the group. In such cases, individuals can use the choices made by earlier ranks, a form of social information, to inform their own choice. The optimal strategy for such decisions has been explored in models which differ on, for example, whether or not agents take into account the sequence of observed choices. The models demonstrate that choices made later in a sequence are more informative, but it is not clear if animals use this information or rely instead on simpler heuristics, such as quorum rules. We show that a simple rule 'copy the last observed choice', gives similar predictions to those of optimal models for most likely sequences. We trained groups of zebrafish to choose one arm of a Y-maze and used them to demonstrate various sequences to naive fish. We show that the naive fish appear to use a simple rule, most often copying the choice of the last demonstrator, which results in near-optimal choices at a fraction of the computational cost.
Project description:The master circadian clock in fish has been considered to reside in the pineal gland. This dogma is challenged, however, by the finding that most zebrafish tissues contain molecular clocks that are directly reset by light. To further examine the role of the pineal gland oscillator in the zebrafish circadian system, we generated a transgenic line in which the molecular clock is selectively blocked in the melatonin-producing cells of the pineal gland by a dominant-negative strategy. As a result, clock-controlled rhythms of melatonin production in the adult pineal gland were disrupted. Moreover, transcriptome analysis revealed that the circadian expression pattern of the majority of clock-controlled genes in the adult pineal gland is abolished. Importantly, circadian rhythms of behavior in zebrafish larvae were affected: rhythms of place preference under constant darkness were eliminated, and rhythms of locomotor activity under constant dark and constant dim light conditions were markedly attenuated. On the other hand, global peripheral molecular oscillators, as measured in whole larvae, were unaffected in this model. In conclusion, characterization of this novel transgenic model provides evidence that the molecular clock in the melatonin-producing cells of the pineal gland plays a key role, possibly as part of a multiple pacemaker system, in modulating circadian rhythms of behavior.
Project description:The objective of this protocol is to provide a detailed description for the construction and use of a behavioral apparatus, the zBox, for high-throughput behavioral measurements in larval zebrafish (Danio rerio). The zBox is used to measure behavior in multiple individuals simultaneously. Individual fish are housed in wells of multi-well plates and receive acoustic/vibration stimuli with simultaneous recording of behavior. Automated analysis of behavioral movies is performed with MATLAB scripts. This protocol was adapted from two of our previously published papers (Levitz et al., 2013; Pantoja et al., 2016). The zBox provides an easy to setup flexible platform for behavioral experiments in zebrafish larvae.
Project description:Understanding how the nervous system recognizes salient stimuli in the environment and selects and executes the appropriate behavioral responses is a fundamental question in systems neuroscience. To facilitate the neuroethological study of visually guided behavior in larval zebrafish, we developed "virtual reality" assays in which precisely controlled visual cues can be presented to larvae whilst their behavior is automatically monitored using machine vision algorithms. Freely swimming larvae responded to moving stimuli in a size-dependent manner: they directed multiple low amplitude orienting turns (∼20°) toward small moving spots (1°) but reacted to larger spots (10°) with high-amplitude aversive turns (∼60°). The tracking of small spots led us to examine how larvae respond to prey during hunting routines. By analyzing movie sequences of larvae hunting paramecia, we discovered that all prey capture routines commence with eye convergence and larvae maintain their eyes in a highly converged position for the duration of the prey-tracking and capture swim phases. We adapted our virtual reality assay to deliver artificial visual cues to partially restrained larvae and found that small moving spots evoked convergent eye movements and J-turns of the tail, which are defining features of natural hunting. We propose that eye convergence represents the engagement of a predatory mode of behavior in larval fish and serves to increase the region of binocular visual space to enable stereoscopic targeting of prey.
Project description:Collective cell migration is a fundamental process, occurring during embryogenesis and cancer metastasis. Neural crest cells exhibit such coordinated migration, where aberrant motion can lead to fatality or dysfunction of the embryo. Migration involves at least two complementary mechanisms: contact inhibition of locomotion (a repulsive interaction corresponding to a directional change of migration upon contact with a reciprocating cell), and co-attraction (a mutual chemoattraction mechanism). Here, we develop and employ a parameterized discrete element model of neural crest cells, to investigate how these mechanisms contribute to long-range directional migration during development. Motion is characterized using a coherence parameter and the time taken to reach, collectively, a target location. The simulated cell group is shown to switch from a diffusive to a persistent state as the response-rate to co-attraction is increased. Furthermore, the model predicts that when co-attraction is inhibited, neural crest cells can migrate into restrictive regions. Indeed, inhibition of co-attraction in vivo and in vitro leads to cell invasion into restrictive areas, confirming the prediction of the model. This suggests that the interplay between the complementary mechanisms may contribute to guidance of the neural crest. We conclude that directional migration is a system property and does not require action of external chemoattractants.
Project description:Complex ethological behaviors could be constructed from finite modules that are reproducible functional units of behavior. Here, we test this idea for foraging and develop methods to dissect rich behavior patterns in mice. We uncover discrete modules of foraging behavior reproducible across different strains and ages, as well as nonmodular behavioral sequences. Modules differ in terms of form, expression frequency, and expression timing and are expressed in a probabilistically determined order. Modules shape economic patterns of feeding, exposure, activity, and perseveration responses. The modular architecture of foraging changes developmentally, and different developmental, genetic, and parental effects are found to shape the expression of specific modules. Dissecting modules from complex patterns is powerful for phenotype analysis. We discover that both parental alleles of the imprinted Prader-Willi syndrome gene Magel2 are functional in mice but regulate different modules. Our study found that complex economic patterns are built from finite, genetically controlled modules.
Project description:Living cells adapt and respond actively to the mechanical properties of their environment. In addition to biochemical mechanotransduction, evidence exists for a myosin-dependent purely mechanical sensitivity to the stiffness of the surroundings at the scale of the whole cell. Using a minimal model of the dynamics of actomyosin cortex, we show that the interplay of myosin power strokes with the rapidly remodeling actin network results in a regulation of force and cell shape that adapts to the stiffness of the environment. Instantaneous changes of the environment stiffness are found to trigger an intrinsic mechanical response of the actomyosin cortex. Cortical retrograde flow resulting from actin polymerization at the edges is shown to be modulated by the stress resulting from myosin contractility, which in turn, regulates the cell length in a force-dependent manner. The model describes the maximum force that cells can exert and the maximum speed at which they can contract, which are measured experimentally. These limiting cases are found to be associated with energy dissipation phenomena, which are of the same nature as those taking place during the contraction of a whole muscle. This similarity explains the fact that single nonmuscle cell and whole-muscle contraction both follow a Hill-like force-velocity relationship.