TheEGA+GNMframework: An integrative approach to modelling behavioural syndromes

Abstract

Behavioural syndromes refer to correlated suites of behavioural traits exhibiting consistent among‐individual variation, i.e. personality. Factor analysis (FA) is currently the dominant method for modelling behavioural syndromes in humans and animals. Although FA is useful for inferring the latent causes underlying trait correlations, it does not account for the pairwise behavioural interactions that also contribute to syndrome structure. Given that latent factors and pairwise interactions are likely ubiquitous causes of trait covariation, both should be modelled simultaneously. Currently, however, behavioural ecologists lack an integrative framework for describing and inferring such behavioural syndromes. Generalized network modelling (GNM), representing an integration of FA and Gaussian graphical modelling (GGM), meets this challenge. We provide a theoretical introduction to GNM as well as a method for detecting latent factors in GGMs called exploratory graph analysis (EGA). We then propose the novel EGA+GNM framework for modelling multiple sources of trait correlations and ensuring more robust causal inferences. To empirically demonstrate the utility of this framework, we compare models derived from EGA+GNM and FA using observational measures of social and arousal behaviour in common marmosets Callithrix jacchus. Using information‐theoretic model comparison, we find support for EGA+GNM models compared to models generated by FA. Two EGA+GNM models suggest that while latent factors contribute to the emergence of clustered sociability and arousal behaviours, correlations among these traits may also be partially explained by pairwise interactions. Additionally, these behavioural clusters are hypothesized to be causally linked by a positive pairwise interaction between allogrooming and activity level. These results support our claim that EGA+GNM provides a superior and integrative framework for describing behavioural syndromes. Consequently, by simultaneously modelling both latent factors and pairwise interactions, behavioural ecologists can better understand the evolutionary causes and consequences of animal personality. A formal overview of the EGA+GNM framework and a R tutorial demonstrating its application are provided in the electronic .

Criteria for acceptable studies of animal personality and behavioural syndromes

“…Unfortunately, using PCA to summarize the major axes of variation in these correlation matrices does not allow assessments of how well such multivariate data fit specific alternative biological hypotheses. A more suitable statistical tool in this case is structural equation modelling (SEM) (Grace, 2006) or similar multivariate methods such as factor analysis or path analysis (Martin et al., 2019), because particular a priori hypotheses for specific covariance structures (e.g., based on the available literature) can then be tested and formally compared to find the most likely fit (Dingemanse, Dochtermann, & Wright, 2010; Dochtermann & Jenkins, 2007).…”

Temporal consistency and ecological validity of personality structure in common marmosets (Callithrix jacchus): A unifying field and laboratory approach

“…Common marmosets ( Callithrix jacchus ) are highly social cooperatively breeding New World primates that live in cohesive family groups in a variety of different habitats, from the Atlantic rain forest to the semiarid area of shrub forests (Garber et al, 2019) and have been studied in a variety of socio‐cognitive questions (Schiel & Souto, 2017). In recent years, these monkeys have become the focus of personality studies under lab conditions: they display consistent interindividual differences when assessed in a battery of experiments (Díaz et al, 2020; Koski & Burkart, 2015; Šlipogor et al, 2016; Tomassetti et al, 2019), observations (Martin et al, 2019; Masilkova et al, 2020; Šlipogor et al, 2020), questionnaires (Inoue‐Murayama et al, 2018; Koski et al, 2017; Weiss et al, 2020), and by using a combination of several different personality assessment methods (Iwanicki & Lehmann, 2015; Šlipogor et al, 2020). However, little is known about long‐term consistency of their personality structure, and no study to this date assessed the personality of wild common marmoset populations.…”

Personality, Subjective Well-Being, and the Serotonin 1a Receptor Gene in Common Marmosets (Callithrix jacchus)

“…Researchers have also been examining the extent to which common marmoset personality resembles and differs from that of other species. As in other species, behavioral experiments have revealed the presence of stable traits in common marmosets (10,11).…”

“…Studies of common marmosets have revealed the presence of stable personality traits [10, 11], although one study found that these traits can be modified via social facilitation or social group effects [12]. Studies have also found that personality traits in common marmosets are heritable and related to well-being [13], associated with the strength of laterality [14], and the binding potential of serotonin transporters in the brain [15].…”