Sexually coercive male chimpanzees sire more offspring.

In sexually reproducing animals, male and female reproductive strategies often conflict. In some species, males use aggression to overcome female choice, but debate persists over the extent to which this strategy is successful. Previous studies of male aggression toward females among wild chimpanzees have yielded contradictory results about the relationship between aggression and mating behavior. Critically, however, copulation frequency in primates is not always predictive of reproductive success. We analyzed a 17-year sample of behavioral and genetic data from the Kasekela chimpanzee (Pan troglodytes schweinfurthii) community in Gombe National Park, Tanzania, to test the hypothesis that male aggression toward females increases male reproductive success. We examined the effect of male aggression toward females during ovarian cycling, including periods when the females were sexually receptive (swollen) and periods when they were not. We found that, after controlling for confounding factors, male aggression during a female's swollen periods was positively correlated with copulation frequency. However, aggression toward swollen females was not predictive of paternity. Instead, aggression by high-ranking males toward females during their nonswollen periods was positively associated with likelihood of paternity. This indicates that long-term patterns of intimidation allow high-ranking males to increase their reproductive success, supporting the sexual coercion hypothesis. To our knowledge, this is the first study to present genetic evidence of sexual coercion as an adaptive strategy in a social mammal.

Dynamic neural networks supporting memory retrieval.

How do separate neural networks interact to support complex cognitive processes such as remembrance of the personal past? Autobiographical memory (AM) retrieval recruits a consistent pattern of activation that potentially comprises multiple neural networks. However, it is unclear how such large-scale neural networks interact and are modulated by properties of the memory retrieval process. In the present functional MRI (fMRI) study, we combined independent component analysis (ICA) and dynamic causal modeling (DCM) to understand the neural networks supporting AM retrieval. ICA revealed four task-related components consistent with the previous literature: 1) medial prefrontal cortex (PFC) network, associated with self-referential processes, 2) medial temporal lobe (MTL) network, associated with memory, 3) frontoparietal network, associated with strategic search, and 4) cingulooperculum network, associated with goal maintenance. DCM analysis revealed that the medial PFC network drove activation within the system, consistent with the importance of this network to AM retrieval. Additionally, memory accessibility and recollection uniquely altered connectivity between these neural networks. Recollection modulated the influence of the medial PFC on the MTL network during elaboration, suggesting that greater connectivity among subsystems of the default network supports greater re-experience. In contrast, memory accessibility modulated the influence of frontoparietal and MTL networks on the medial PFC network, suggesting that ease of retrieval involves greater fluency among the multiple networks contributing to AM. These results show the integration between neural networks supporting AM retrieval and the modulation of network connectivity by behavior.