Aggregate, or explosive, breeding is widespread among vertebrates and likely increases the probability of multiple paternity. We assessed paternity in seven field-collected clutches of the explosively breeding spotted salamander (Ambystoma maculatum) using 10 microsatellite loci to determine the frequency of multiple paternity and the number of males contributing to a female's clutch. Using the Minimum Method of allele counts, multiple paternity was evident in 70% of these egg masses. Simple allele counts underestimate the number of contributing males because this method cannot distinguish multiple fathers with common or similar alleles. Therefore, we used computer simulations to estimate from the offspring genotypes the most likely number of contributing fathers given the distributions of allele frequencies in this population. We determined that two to eight males may contribute to A. maculatum clutches; therefore, multiple paternity is a common strategy in this aggregate breeding species. In aggregate mating systems competition for mates can be intense, thus differential reproductive success (reproductive skew) among males contributing to a female's clutch could be a probable outcome. We use our data to evaluate the potential effect of reproductive skew on estimates of the number of contributing males. We simulated varying scenarios of differential male reproductive success, ranging from equal contribution to high reproductive skew among contributing sires in multiply sired clutches. Our data suggest that even intermediate levels of reproductive skew decrease confidence substantially in estimates of the number of contributing sires when parental genotypes are unknown.

Research suggests that frontal EEG asymmetry (FA) is a relatively stable trait associated with individual differences in dispositional affect (affective style) and liability to mood disorders. If FA is genetically determined, it can potentially serve as an endophenotype in genetic studies of temperament and mood disorders. The purpose of this study was to assess heritability of FA as well as alpha band EEG power measured at different frontal recording sites. Resting EEG data from a population-based sample of 246 young adult female twins including 73 monozygotic (MZ) and 50 dizygotic (DZ) pairs were analyzed using linear structural equation modeling. FA measured at mid-frontal locations (F3 and F4) showed low but significant heritability, suggesting that 27% of the observed variance can be accounted for by genetic factors. There was no evidence for genetic influences on FA measured at lateral-frontal (F7 and F8) locations. In contrast, alpha band power was highly heritable at all four frontal sites (85-87%). These findings suggest that: (1) genetic influences on FA are very modest and therefore FA has a limited utility as an endophenotype for genetic studies of mood disorders and (2) prefrontal neural circuitry underlying individual differences in affective style is characterized by high developmental plasticity.

Objective The provision of information appears to be an important feature of self‐esteem. The present studies examined whether self‐esteem possesses a status‐signaling property such that an individual's level of self‐esteem is associated with how the individual is perceived by others. Method In Study 1, trained judges watched brief videos of 157 participants and rated targets as having higher levels of self‐esteem when the targets were believed to possess more positive personality characteristics. Study 2 found that participants (357 targets) were rated as having higher levels of self‐esteem when they were given more positive personality evaluations by their friends and family members (1,615 perceivers). Results Consistent with the proposed status‐signaling model, high levels of self‐esteem were generally associated with the perception of positive personality characteristics. Conclusions These findings are discussed in the context of an extended informational model of self‐esteem consisting of both the status‐tracking and status‐signaling properties of self‐esteem.

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Human electroencephalogram (EEG) consists of complex aperiodic oscillations that are assumed to indicate underlying neural dynamics such as the number and degree of independence of oscillating neuronal networks. EEG complexity can be estimated using measures derived from nonlinear dynamic systems theory. Variations in such measures have been shown to be associated with normal individual differences in cognition and some neuropsychiatric disorders. Despite the increasing use of EEG complexity measures for the study of normal and abnormal brain functioning, little is known about genetic and environmental influences on these measures. Using the pointwise dimension (PD2) algorithm, this study assessed heritability of EEG complexity at rest in a sample of 214 young female twins consisting of 51 monozygotic (MZ) and 56 dizygotic (DZ) pairs. In MZ twins, intrapair correlations were high and statistically significant; in DZ twins, correlations were substantially smaller. Genetic analyses using linear structural equation modeling revealed high and significant heritability of EEG complexity: 62-68% in the eyes-closed condition, and 46-60% in the eyes-open condition. Results suggest that individual differences in the complexity of resting electrocortical dynamics are largely determined by genetic factors. Neurophysiological mechanisms mediating genetic variation in EEG complexity may include the degree of structural connectivity and functional differentiation among cortical neuronal assemblies. © 2005 Elsevier Ireland Ltd. All rights reserved.Keywords: Electroencephalogram; Complexity; Nonlinear dynamics; Twins; Heritability Neural activity underlying cognition and behavior is characterized by a high degree of functional differentiation and, at the same time, functional integration achieved through rapid binding of spatially distributed and functionally specialized neuronal groups [32]. To some extent, these fundamental properties of large-scale brain dynamics are reflected in the electroencephalogram (EEG) recorded from the scalp. The EEG results from the summation of postsynaptic activity of a large number of spatially distributed but functionally connected and interacting cortical neurons and neuronal assemblies. Accordingly, the EEG time series has a complex structure reflecting the complexity of the underlying neural generators [16,26]. A greater number of independent processes contributing to the EEG results in a greater complexity of EEG time series [18]. EEG complexity may reflect the number of states of a system resulting from the interaction * Corresponding author. Tel.: +1 314 286 2201; fax: +1 314 286 0092.E-mail address: andrey@matlock.wustl.edu (A.P. Anokhin).among its elements, with higher complexity reflecting a larger number of separable oscillatory networks [32].In recent years, cortical oscillations have been increasingly viewed from the perspective of nonlinear dynamic systems theory, which investigates complex, aperiodic systems capable of self-organization [9,26]. The behavior of complex syste...

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Shape variation is widespread in nature and embodies both a response to and a source for evolution and natural selection. To detect patterns of shape evolution, one must assess the quantitative genetic underpinnings of shape variation as well as the selective environment that the organisms have experienced. Here we used geometric morphometrics to assess variation in plastron shell shape in 1314 neonatal slider turtles (Trachemys scripta) from 162 clutches of laboratory-incubated eggs from two nesting areas. Multivariate analysis of variance indicated that nesting area has a limited role in describing plastron shape variation among clutches, whereas differences between individual clutches were highly significant, suggesting a prominent clutch effect. The covariation between plastron shape and several possible maternal effect variables (yolk hormone levels and egg dimensions) was assessed for a subset of clutches and found to be negligible. We subsequently employed several recently proposed methods for estimating heritability from shape variables, and generalized a univariate approach to accommodate unequal sample sizes. Univariate estimates of shape heritability based on Procrustes distances yielded large values for both nesting populations (h2 approximately 0.86), and multivariate estimates of maximal additive heritability were also large for both nesting populations (h2max approximately 0.57). We also estimated the dominant trend in heritable shape change for each nesting population and found that the direction of shape evolution was not the same for the two sites. Therefore, although the magnitude of shape evolution was similar between nesting populations, the manner in which plastron shape is evolving is not. We conclude that the univariate approach for assessing quantitative genetic parameters from geometric morphometric data has limited utility, because it is unable to accurately describe how shape is evolving.