Quantifying uncertainty due to fission-fusion dynamics as a component of social complexity.

Groups of animals (including humans) may show flexible grouping patterns, in which temporary aggregations or subgroups come together and split, changing composition over short temporal scales, (i.e. fission and fusion). A high degree of fission-fusion dynamics may constrain the regulation of social relationships, introducing uncertainty in interactions between group members. Here we use Shannon's entropy to quantify the predictability of subgroup composition for three species known to differ in the way their subgroups come together and split over time: spider monkeys (Ateles geoffroyi), chimpanzees (Pan troglodytes) and geladas (Theropithecus gelada). We formulate a random expectation of entropy that considers subgroup size variation and sample size, against which the observed entropy in subgroup composition can be compared. Using the theory of set partitioning, we also develop a method to estimate the number of subgroups that the group is likely to be divided into, based on the composition and size of single focal subgroups. Our results indicate that Shannon's entropy and the estimated number of subgroups present at a given time provide quantitative metrics of uncertainty in the social environment (within which social relationships must be regulated) for groups with different degrees of fission-fusion dynamics. These metrics also represent an indirect quantification of the cognitive challenges posed by socially dynamic environments. Overall, our novel methodological approach provides new insight for understanding the evolution of social complexity and the mechanisms to cope with the uncertainty that results from fission-fusion dynamics.

Regression and simulation models for human and baboon brain parameters / Modelo regresivo y simulación para los parámetros cerebrales humanos y del babuino

The variations in morphometric parameter of mammalian brains may be influenced by process of functional complexity, evolution and adaptation. Comparative analysis of linear measurements of cerebrum in the human and baboon has shown morphometric differences. In the present study linear measurements from human and baboon cerebrum (n=10 each) were used to predict various values for human and baboon brain and body parameters through multiple regression models. The average brain weights were found to be 2.08 percent and 0.84 percent of the body weights for humans and baboons respectively. The elasticity of regression models revealed that unit percentage increase in Occipital-Frontal (OF) distance would increase the human brain weight by 66.19 percent, while the baboon brain weight would increase by 7.63 percent. The unit percentage increase in the Height of Temporal Lobe (HTL) would increase the human brain weight by 16.28 percent, while the baboon brain weight would increase by only 0.28 percent. Unit percentage increase in Frontal-Temporal (FT) distance would decrease the human and baboon brain weights by 14.04 percent and 0.46 percent respectively. Inter-species values were also predicted through simulation techniques by using the ratios of model parameters with application of programming language Python. The OF, FT and HTL values for human were found to be 2.01 times, 1.55 times and 1.91 times respectively to that of baboon.

Las variaciones en los parámetros morfométricos del cerebro de los mamíferos pueden estar influenciadas por el proceso de complejidad funcional de la evolución y adaptación. Análisis comparativo de las mediciones lineales del cerebro en el humano y babuino han puesto de manifiesto las diferencias morfométricas. En este estudio las mediciones lineales del cerebro humano y babuinos (n = 10 cada uno) fueron utilizados para predecir los valores distintivos para el cerebro de humanos y monos babuinos y los parámetros del cuerpo a través de modelos de regresión múltiple. El peso medio del cerebro resultó ser 2,08 por ciento y 0,84 por ciento del peso corporal de los seres humanos y los babuinos, respectivamente. La elasticidad de los modelos de regresión reveló que el aumento de una unidad porcentual en la distancia occipital-frontal (DE) aumentaría el peso del cerebro humano en 66,19 por ciento, mientras que el peso del cerebro babuino se incrementaría en 7,63 por ciento. El porcentaje de aumento en la altura de lóbulo temporal (HTL) aumentaría el peso del cerebro humano en 16,28 por ciento, mientras que el peso del cerebro babuino aumentaría en sólo el 0,28 por ciento. Si aumenta la distancia frontal-temporal (FT) se reduciría el peso del cerebro humano y babuinos en 14,04 por ciento y 0,46 por ciento, respectivamente. También se prevéen valores entre las especies a través de técnicas de simulación, mediante el uso de proporciones de los parámetros del modelo con la aplicación del lenguaje de programación Python. Los valores humanos de DE, FT y HTL resultaron ser 2,01, 1,55 y 1,91 veces, respectivamente con respecto a la de los babuinos.