Insomnia, the most common sleep disorder afflicting adults, is diagnostically characterized by a chronic complaint of difficulty sleeping at night and a report of consequent impairment in daytime functioning. Despite this diagnostic requirement and the relative prevalence of daytime distress in patients with insomnia, studies to date have shown only limited evidence of objective daytime impairment in this population. This investigation tested a neurobiological compensation model which attempted to explain how patients with insomnia overcome cognitive challenges resulting from chronic partial sleep loss (utilizing FMRI). The proposed model suggests that patients with insomnia might increase cortical activation during cognitive challenge (relative to good sleepers) to "compensate" for their sleep loss and that this compensation would lead to maintenance of performance. Furthermore, this study examined the relationship between brain activation and performance and brain activation and daytime complaint in patients with Primary Insomnia. 24 subjects, 13 with Primary Insomnia [PI] (7 female, 6 male) and 11 good sleeper controls [GS] (5 female, 6 male) were studied in this investigation. Patients and controls did not differ statistically in terms of age (PI: 39.8+/-8.0 yrs; GS: 37.1+/-7.7 yrs) or estimated IQ (PI: 116.3+/-8.0; GS: 115.8+/-8.5). Results from the study showed several statistically significant findings, including : a) Patients with insomnia have more disturbed sleep and greater complaints of impaired daytime functioning when compared to matched good sleeper controls b) Patients showed no evidence of cognitive impairment as a result of their sleep loss and despite their complaints of impaired daytime functioning c) Patients exhibit differential patterns of activation during the performance of cognitive tasks relative to controls d) Differences in activation between patients and controls depended to a large degree upon the type of task and level of task difficulty (patients had greater levels of activation on attention, working memory, and learning of easy words, but less activation on inhibition and learning of hard words) e) Within the insomnia sample, individuals who performed better had greater levels of activation (similar to controls) on each task f) Within the insomnia sample those individuals who had the greatest complaints of impaired daytime functioning showed less activation on each task. Overall, the results of this study provide some evidence for the effects of sleep loss on neurophysiologic activation in primary insomnia. However, these findings may suggest that the proposed "compensation" model may not adequately explain the complex interaction between sleep loss, daytime complaint, cognitive function, and activation for this population

Mosquitoes are important vectors for pathogens that infect humans and other vertebrate animals. Some aspects of adult mosquito behavior and mosquito ecology play an important role in determining the capacity of vector populations to transmit pathogens. Here, we re-examine factors affecting the transmission of pathogens by mosquitoes using a new approach. Unlike most previous models, this framework considers the behavioral states and state transitions of adult mosquitoes through a sequence of activity bouts. We developed a new framework for individual-based simulation models called MBITES (Mosquito Bout-based and Individual-based Transmission Ecology Simulator). In MBITES, it is possible to build models that simulate the behavior and ecology of adult mosquitoes in exquisite detail on complex resource landscapes generated by spatial point processes. We also developed an ordinary differential equation model which is the Kolmogorov forward equations for models developed in MBITES under a specific set of simplifying assumptions. While mosquito infection and pathogen development are one possible part of a mosquito's state, that is not our main focus. Using extensive simulation using some models developed in MBITES, we show that vectorial capacity can be understood as an emergent property of simple behavioral algorithms interacting with complex resource landscapes, and that relative density or sparsity of resources and the need to search can have profound consequences for mosquito populations' capacity to transmit pathogens.