Stochastic integrator models of collective decision-making

集体决策的随机积分模型

• 批准号: 8453012
• 负责人: MARK S GOLDMAN
• 金额: $ 21.23万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-10 至 2016-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8453012
• 关键词: Address; Ants; Behavior; Behavioral; Biological Models; Brain; Chemicals; Climate; Code; Collaborations; Complex; Cues; Data; Decision Making; Desiccation; Disease; Eating; Ecology; Endogenous depression; Environment; Equilibrium; Feedback; Film; Food; Goals; Human; Individual; Kinetics; Left; Life; Link; Longitudinal Studies; Measures; Methods; Mission; Modeling; Movement; Nest Leaving; Neurons; Neurosciences; Neurotransmitters; Pheromone; Population; Post-Traumatic Stress Disorders; Probability; Process; Regulation; Research; Role; Seeds; Signal Transduction; Social Behavior; Social Interaction; Societies; Source; Stress; Structure; Synapses; Synaptic Vesicles; System; Techniques; Testing; Time; To specify; United States National Institutes of Health; Vesicle; Work; base; cost; environmental change; insight; member; public health relevance; resilience; response; social; social group; theories; trafficking

DESCRIPTION (provided by applicant): Most social behavior occurs in response to interaction, yet the collective processes that regulate the behavior of social groups are poorly understood. Elucidating the role of interactions in regulating social behavior requires a simple model system in which to study the dynamical processes that allow social groups to respond to changing environmental conditions. Our long-term goal is to use the red harvester ant, Pogonomyrmex barbatus, as a model for investigating the collective regulation of behavior that leads to the resilience of social groups. Our project brings together a unique 25-year study of the behavior and ecology of a natural population of harvester ant colonies, with theoretical advances in neuroscience. We draw on the strong correspondences between the accumulation of chemical signals made by ants deciding whether to forage and the accumulation of signals that underlie decision-making at the synaptic, neuronal, and behavioral levels in neuroscience. Ant colonies operate without central control, using networks of simple interactions to regulate foraging activity and adjust to current ecological conditions. Previous work shows that the probability that outgoing foragers leave the nest, and thus the colony's overall level of foraging activity, depends on their rate of interactio with returning successful foragers. The rate of forager return depends on search time and thus on food availability. Aim 1 investigates what mechanisms allow individual ants to make foraging decisions based on social contact with other ants. We will develop a leaky integrator model, closely analogous to the stochastic accumulator models of neuroscience, for how individual ants accumulate signals in support of the decision to forage. The model predictions will be tested, and model parameters evaluated, in colonies in the field using methods applied successfully in previous work. Aim 2 seeks to explain the overall rate of colony foraging activity and trafficking of ants between forager pools inside the nest. Using colonies in the field, we will test an expanded version of the model that includes the trafficking of ants from reserve to outgoing foragers, using theory inspired by the similar trafficking of neurotransmitter vesicles in synapses Aim 3 investigates the plasticity of foraging behavior, using the models developed in Aims 1 and 2 to test whether colonies can adjust parameters in response to environmental conditions, and evaluating how collective decisions determine the resilience of the colony. Findings from this research will contribute to the mission of NIH by providing fundamental insight into the collective regulation of social behavior in response to environmental cues and social interactions.

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