Introduction: There is widespread literature on the interaction between cannabis use and sleep, yet the mechanisms that underlie this relationship are not well understood. Several factors lead to inconsistencies in this relationship suggesting a nuanced interaction between cannabis and sleep. An important question that remains to be addressed is the temporal relationship between disrupted sleep and cannabis use. This literature review summarizes the existing literature on the association between disrupted sleep and cannabis toward the goal of addressing the question of the chronology of these reported effects. Materials and Methods: We conducted a review of the literature using PubMed to summarize current knowledge on the association between cannabis use and sleep in humans. Results: We identified 31 studies on the association of cannabis use and sleep. The findings from these studies were mixed. Cannabis was associated with a variety of impacts on sleep ranging from beneficial effects, such as reduced sleep-onset latency, to negative outcomes, such as reduced sleep duration and suppressed rapid eye movement oscillations. The chronology of the interaction of cannabis and sleep was unclear, although much of the current literature focus on factors that modulate how cannabis impairs sleep after initial use. Conclusion:There was sufficient evidence to suggest that cannabis use alters circadian rhythms, and hence, negatively impacts sleep. The current literature is largely from studies utilizing self-report measures of sleep; thus, objective measures of sleep are needed. In addition, although there were no empirical studies on the temporal relationship between cannabis use and sleep, the majority of the literature focused on characterizing sleep impairment after cannabis use.

Traditionally, quantitative electroencephalography (QEEG) studies collect data within controlled laboratory environments that limit the external validity of scientific conclusions. To probe these validity limits, we used a mobile EEG system to record electrophysiological signals from human participants while they were located within a controlled laboratory environment and an uncontrolled outdoor environment exhibiting several moderate background influences. Participants performed two tasks during these recordings, one engaging brain activity related to several complex cognitive functions (number sense, attention, memory, executive function) and the other engaging two default brain states. We computed EEG spectral power over three frequency bands (theta: 4–7 Hz, alpha: 8–13 Hz, low beta: 14–20 Hz) where EEG oscillatory activity is known to correlate with the neurocognitive states engaged by these tasks. Null hypothesis significance testing yielded significant EEG power effects typical of the neurocognitive states engaged by each task, but only a beta-band power difference between the two background recording environments during the default brain state. Bayesian analysis showed that the remaining environment null effects were unlikely to reflect measurement insensitivities. This overall pattern of results supports the external validity of laboratory EEG power findings for complex and default neurocognitive states engaged within moderately uncontrolled environments.

Higher-fidelity human behavioral models promise to enhance a wide range of simulations where high-risk and high-threat environments make human performance assessment difficult. This paper explores a methodology for implementing high fidelity human behaviors in simulation. In addition to combat models, first-responder simulations for police, fire, and rescue may benefit. Homeland security simulations ranging from border patrol to civil defense and the Global War on Terrorism are also prime candidates for these techniques.

This paper describes a component-based design for a virtual network construction and simulation tool to be used for educational purposes. In this study, the elemenfs o f a compurer n e~o r k are defined in terms o j discrete objects. It presents the component hierarchy and design requirements far modeling a network, and describes the means by which rhese objects can be modeled and instantiated us simulated network components using XML and Java. Following an overview of the elements os the u4ADNET (Military Academy AtturWDefense Network) project and a discussion of its goah and requirements, the components required to build a virtud network are defined, Jili'owed by implementation details and additional design considerations. 1 . 2.