Browse
Submit Data
Databases
API
Help

Dataset Information

14 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Individual variations lead to universal and cross-species patterns of social behavior.

ABSTRACT: The duration of interaction events in a society is a fundamental measure of its collective nature and potentially reflects variability in individual behavior. Here we performed a high-throughput measurement of trophallaxis and face-to-face event durations experienced by a colony of honeybees over their entire lifetimes. The interaction time distribution is heavy-tailed, as previously reported for human face-to-face interactions. We developed a theory of pair interactions that takes into account individual variability and predicts the scaling behavior for both bee and extant human datasets. The individual variability of worker honeybees was nonzero but less than that of humans, possibly reflecting their greater genetic relatedness. Our work shows how individual differences can lead to universal patterns of behavior that transcend species and specific mechanisms for social interactions.

SUBMITTER: Choi SH

PROVIDER: S-EPMC7749354 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Cross species comparison of expression patterns

Project description:Comparison of expression in liver samples of human, chimp, orang and rhesus, by using a novel multi-species cDNA array Keywords: other

2005-01-25 | GSE2009 | GEO

Cross species comparison of expression patterns

Project description:Comparison of expression in liver samples of human, chimp, orang and rhesus, by using a novel multi-species cDNA array

2010-06-10 | E-GEOD-2009 | biostudies-arrayexpress

Cross species comparison of expression patterns

Project description:Cross species comparison of expression patterns

| PRJNA91829 | ENA

Social learning may lead to population level conformity without individual level frequency bias.

Project description:A requirement of culture, whether animal or human, is some degree of conformity of behavior within populations. Researchers of gene-culture coevolution have suggested that population level conformity may result from frequency-biased social learning: individuals sampling multiple role models and preferentially adopting the majority behavior in the sample. When learning from a single role model, frequency-bias is not possible. We show why a population-level trend, either conformist or anticonformist, may nonetheless be almost inevitable in a population of individuals that learn through social enhancement, that is, using observations of others' behavior to update their own probability of using a behavior in the future. The exact specification of individuals' updating rule determines the direction of the trend. These results offer a new interpretation of previous findings from simulations of social enhancement in combination with reinforcement learning, and demonstrate how results of dynamical models may strongly depend on seemingly innocuous choices of model specifications, and how important it is to obtain empirical data on which to base such choices.

| S-EPMC5725437 | biostudies-other

Species, sex and individual differences in the vasotocin/vasopressin system: relationship to neurochemical signaling in the social behavior neural network.

Project description:Arginine-vasotocin (AVT)/arginine vasopressin (AVP) are members of the AVP/oxytocin (OT) superfamily of peptides that are involved in the regulation of social behavior, social cognition and emotion. Comparative studies have revealed that AVT/AVP and their receptors are found throughout the "social behavior neural network (SBNN)" and display the properties expected from a signaling system that controls social behavior (i.e., species, sex and individual differences and modulation by gonadal hormones and social factors). Neurochemical signaling within the SBNN likely involves a complex combination of synaptic mechanisms that co-release multiple chemical signals (e.g., classical neurotransmitters and AVT/AVP as well as other peptides) and non-synaptic mechanisms (i.e., volume transmission). Crosstalk between AVP/OT peptides and receptors within the SBNN is likely. A better understanding of the functional properties of neurochemical signaling in the SBNN will allow for a more refined examination of the relationships between this peptide system and species, sex and individual differences in sociality.

| S-EPMC4317378 | biostudies-literature

Individual bee brain behavior-age

Project description:This experiment examines gene expression profiles in individual honey bee brains (adult worker Apis mellifera). The purpose is to test whether behavioral phenotype can be predicted by expression profiles in individual brains in a naturalistic context (i.e., colonies in the field). The two behavioral phenotypes examined are 'nurse' and 'forager'. Other factors examined are age, genotype (full-sister group), and colony environment.<br><br> An additional processed data file is available on the FTP site for this experiment.

2011-02-03 | E-MEXP-24 | biostudies-arrayexpress

Cross-Species Comparison Identifies Proneural specific patterns of genetic alterations in Glioblastoma

2014-01-17 | GSE36940 | GEO

Individual, Social, and Environmental Correlates of Active Transportation Patterns in French Women.

Project description:The objectives were (1) to define physical activity (PA) and sedentary behaviors (SB) patterns in daily life contexts (work, leisure, and transportation) in French working women from NutriNet-Santé web-cohort and (2) to identify pattern(s) of active transportation and their individual, social, and environmental correlates. 23,432 participants completed two questionnaires to evaluate PA and SB in daily life contexts and individual representations of residential neighborhood and transportation modes. Hierarchical cluster analysis was performed which identified 6 distinct movement behavior patterns: (i) active occupation, high sedentary leisure, (ii) sedentary occupation, low leisure, (iii) sedentary transportation, (iv) sedentary occupation and leisure, (v) active transportation, and (vi) active leisure. Multinomial logistic regressions were performed to identify correlates of the "active transportation" cluster. The perceived environmental characteristics positively associated with "active transportation" included "high availability of destinations around home," "presence of bicycle paths," and "low traffic." A "positive image of walking/cycling," the "individual feeling of being physically active," and a "high use of active transport modes by relatives/friends" were positively related to "active transportation," identified as a unique pattern regarding individual and environmental correlates. Identification of PA and SB context-specific patterns will help to understand movement behaviors' complexity and to design interventions to promote active transportation in specific subgroups.

| S-EPMC5498903 | biostudies-literature

Competition for resources can explain patterns of social and individual learning in nature.

Project description:In nature, animals often ignore socially available information despite the multiple theoretical benefits of social learning over individual trial-and-error learning. Using information filtered by others is quicker, more efficient and less risky than randomly sampling the environment. To explain the mix of social and individual learning used by animals in nature, most models penalize the quality of socially derived information as either out of date, of poor fidelity or costly to acquire. Competition for limited resources, a fundamental evolutionary force, provides a compelling, yet hitherto overlooked, explanation for the evolution of mixed-learning strategies. We present a novel model of social learning that incorporates competition and demonstrates that (i) social learning is favoured when competition is weak, but (ii) if competition is strong social learning is favoured only when resource quality is highly variable and there is low environmental turnover. The frequency of social learning in our model always evolves until it reduces the mean foraging success of the population. The results of our model are consistent with empirical studies showing that individuals rely less on social information where resources vary little in quality and where there is high within-patch competition. Our model provides a framework for understanding the evolution of social learning, a prerequisite for human cumulative culture.

| S-EPMC4614750 | biostudies-other

Cross-Species Comparison Identifies Proneural specific patterns of genetic alterations in Glioblastoma

Project description:The determinants of the genetic complexity of Glioblastoma are poorly understood. We generated murine Glioblastomas by transforming glial progenitors in the adult brain with PDGF expression and PTEN deletion +/- p53 deletion. PDGF+PTEN-/- tumors developed additional deletions of specific genes in up to 100% of the tumors, whereas PDGF+PTEN-/-p53-/- tumors did not. Cross-species comparison with data from tCGA database and published in Verhaak, 2010, showed that consistent genetic deletions observed in mouse tumors were specific to human Proneural Glioblastoma. These findings show that the genetic alterations that accumulate during tumor progression are determined by the initiating genetic alterations and by the cellular context in which they occur. Murine gliomas were induced in vivo by retroviral mediated PDGF overexpression, PTEN deletion with or without p53 deletion using Cre/lox system. Tumors were subsequently harvested for sequencing and aCGH analysis. Paired liver DNA was used for hybridization. For PDGF+PTEN-/- tumors, different timepoints were obtained including 21, 35 days post tumor induction, as well as endstage tumors.

2014-01-17 | E-GEOD-36940 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data