Many animals, and particularly humans, depend on social networks for their general well-being and in many cases for their survival. The biomedical impacts of social networks on individuals can have important implications for regulating obesity and drug or alcohol abuse. The effects can also have a large impact on the functioning of any organization, ranging from small to large public and private organizations through military command and control. In many cases the central control of groups is by necessity loose or nonexistent, with the organization arising from sets of rules that each individual employs. It is therefore important to understand how adaptive, collective behavior emerges from a collection of individuals with little or no central control. The research in this proposal is aimed toward understanding group behavior by integrating models with experiments at three biological scales: from gene expression effects in neural networks of the brain, to how those networks affect behavior, to the collective dynamics of a coordinated group of individuals that operates without central control. We will investigate an important problem of group organization from a different perspective than is commonly used. Instead of having individuals who all operate under a common set of rules, as would be true of most agent-based approaches, we propose to study groups composed of individuals who vary in their behavioral rules. The latter condition is more typical of human and many animal groups; because individuals naturally differ in many ways - experience, size, age, etc. - that influence how they respond to various situations. We propose to develop the honey bee as an animal model for this type of work precisely because the survival of any individual in a large (ca 100,000 honey bees) social colony depends on the performance of the group as a whole which operates without central control. Moreover, we can study honey bee biology at multiple organizational scales. We can experimentally manipulate the expression of identified genes, monitor and manipulate neural networks in the brain, and determine the composition of honey bees of different genotypes in the colony. We will focus on how honey bee colonies solve a central problem in looking for food that humans also face. That is, how to allocate resources to exploiting a known resource versus exploring for new resources. Failure to efficiently perform both tasks by the several thousand foraging honey bees risks failure of the colony. We focus on a gene locus that has been repeatedly affiliated with one or another foraging specialty. We propose to investigate how different alleles at this locus influence the behavioral choices of individuals, and then investigate how those individuals are integrated into a colony's strategy for solving this foraging problem. We will use a novel multiscale modeling approach that integrates three biological scales using standard agent-based modeling, mean field approximations, decision making models of the brain, and gene regulatory models. Through a back-and-forth interplay between modeling and experiments, our approach will identify critical parameters that allow groups to face environmental challenges.

Public Health Relevance

How individuals with different attributes cooperate to achieve a collective goal is important for understanding adaptive group behavior. We propose to integrate a new model animal, the honey bee, with a new modeling approach, multiscale modeling, to understand the proximate and ultimate causes of how complex, adaptive collective behaviors emerge from a collection of individuals who vary in their behavioral rules.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM113967-01
Application #
8863779
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Marcus, Stephen
Project Start
2015-09-01
Project End
2019-05-31
Budget Start
2015-09-01
Budget End
2016-05-31
Support Year
1
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Arizona State University-Tempe Campus
Department
Other Basic Sciences
Type
Schools of Arts and Sciences
DUNS #
943360412
City
Tempe
State
AZ
Country
United States
Zip Code
85287
Sinakevitch, Irina; Bjorklund, George R; Newbern, Jason M et al. (2018) Comparative study of chemical neuroanatomy of the olfactory neuropil in mouse, honey bee, and human. Biol Cybern 112:127-140
Cook, Chelsea N; Mosqueiro, Thiago; Brent, Colin S et al. (2018) Individual differences in learning and biogenic amine levels influence the behavioural division between foraging honeybee scouts and recruits. J Anim Ecol :
Sinakevitch, Irina T; Wolff, Gabriella H; Pflüger, Hans-Joachim et al. (2018) Editorial: Biogenic Amines and Neuromodulation of Animal Behavior. Front Syst Neurosci 12:31
Mosqueiro, Thiago; Cook, Chelsea; Huerta, Ramon et al. (2017) Task allocation and site fidelity jointly influence foraging regulation in honeybee colonies. R Soc Open Sci 4:170344
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Birgiolas, Justas; Jernigan, Christopher M; Gerkin, Richard C et al. (2017) SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware. J Vis Exp :
Sinakevitch, Irina T; Daskalova, Sasha M; Smith, Brian H (2017) The Biogenic Amine Tyramine and its Receptor (AmTyr1) in Olfactory Neuropils in the Honey Bee (Apis mellifera) Brain. Front Syst Neurosci 11:77