The high rate of fatal suicidal behavior (SB) in men is an urgent issue as highlighted in the public eye via news sources and media outlets. In this study, we have attempted to address this issue and understand the neural substrates underlying the gender differences in the rate of fatal SB. The Interpersonal–Psychological Theory of Suicide has proposed an explanation for the seemingly paradoxical relationship between gender and SB, i.e., greater non-fatal suicide attempts by women but higher number of deaths by suicide in men. This theory states that possessing suicidal desire (due to conditions such as depression) alone is not sufficient for a lethal suicide attempt. It is imperative for an individual to have the acquired capability for suicide (ACS) along with suicidal desire in order to die by suicide. Therefore, higher levels of ACS in men may explain why men are more likely to die by suicide than women, despite being less likely to experience suicidal ideation or depression. In this study, we used activation likelihood estimation meta-analysis to investigate a potential ACS network that involves neural substrates underlying emotional stoicism, sensation-seeking, pain tolerance, and fearlessness of death, along with a potential depression network that involves neural substrates that underlie clinical depression. Brain regions commonly found in ACS and depression networks for males and females were further used as seeds to obtain regions functionally and structurally connected to them. We found that the male-specific networks were more widespread and diverse than the female-specific ones. Also, while the former involved motor regions, such as the premotor cortex and cerebellum, the latter was dominated by limbic regions. This may support the fact that suicidal desire generally leads to fatal/decisive action in males, while, in females, it manifests as depression, ideation, and generally non-fatal actions. The proposed model is a first attempt to characterize the neural networks underlying gender differences in SB. Future studies should examine the proposed network to better characterize and refine this network using tasks specifically targeted toward constructs underlying ACS.

Progress in neurodevelopmental brain research has been achieved through the use of animal models. Such models not only help understanding biological changes that govern brain development, maturation and aging, but are also essential for identifying possible mechanisms of neurodevelopmental and age-related chronic disorders, and to evaluate possible interventions with potential relevance to human disease. Genetic relationship of rhesus monkeys to humans makes those animals a great candidate for such models. With the typical lifespan of 25 years, they undergo cognitive maturation and aging that is similar to this observed in humans. Quantitative structural neuroimaging has been proposed as one of the candidate in vivo biomarkers for tracking white matter brain maturation and aging. While lifespan trajectories of white matter changes have been mapped in humans, such knowledge is not available for nonhuman primates. Here, we analyze and model lifespan trajectories of white matter microstructure using in vivo diffusion imaging in a sample of 44 rhesus monkeys. We report quantitative parameters (including slopes and peaks) of lifespan trajectories for 8 individual white matter tracts. We show different trajectories for cellular and extracellular microstructural imaging components that are associated with white matter maturation and aging, and discuss similarities and differences between those in humans and rhesus monkeys, the importance of our findings, and future directions for the field.Significance Statement: Quantitative structural neuroimaging has been proposed as one of the candidate in vivo biomarkers for tracking brain maturation and aging. While lifespan trajectories of structural white matter changes have been mapped in humans, such knowledge is not available for rhesus monkeys. We present here results of the analysis and modeling of the lifespan trajectories of white matter microstructure using in vivo diffusion imaging in a sample of 44 rhesus monkeys (age 4-27). We report and anatomically map lifespan changes related to cellular and extracellular microstructural components that are associated with white matter maturation and aging.