Computational Modeling of the Effects of Sleep Deprivation on the Vigilance Decrement

Mapping between cognitive theories and psycho-physiological models of attention system performance

Declines in the capacity to sustain attention to repetitive, monotonous tasks is a phenomenon known as vigilance decrement (Endsley M, Kiris E. The out-of-the-loop performance problem and level of control in automation. 1995. Hum Factors. 37:32-64). This review compares cognitive theories with psycho-physiological models of vigilance decrement, and a gap is identified in mapping between the 2. That is, theories of vigilance decrement refer to "cognitive" resources; by contrast, psychophysiological models of the cerebral systems associated with attention explain performance functions according to neurochemical resources. A map does not currently exist in the literature that bridges the gap between cognitive theories of vigilance decrement and psychophysiological models of the human attention system. The link between "cognitive resource" theories of vigilance decrement and the psychophysiological models of attention performance is a gap in the literature that this review fills. This comprehensive review provides an expanded psychophysiological understanding of vigilance decrement that could help inform the management of declines in sustained attention capacity in operational settings. In addition, elucidating the link between cognitive theories of vigilance decrement and psychophysiological models of the human attention system might be used to treat and better understand pathologies such as attention-deficit hyperactivity disorder.

Will the real resource theory please stand up! Vigilance is a renewable resource and should be modeled as such

The vigilance decrement or decline in signal detection performance with time on task is one of the most reliable findings in the cognitive neuroscience and psychology literatures. The majority of theories proposed to explain the decrement are limited cognitive or attention resource based theories; the central nervous system is a limited capacity processor. The decrement in performance is then due to resource reallocation (or misallocation), resource depletion or some combination of both mechanisms. The role of resource depletion, in particular, is hotly debated. However, this may be due to a lack of understanding of the renewable nature of the vigilance resources and how this renewal process impacts performance during vigilance tasks. In the present paper, a simple quantitative model of vigilance resource depletion and renewal is described and shown to generate performance data similar to results seen in both humans and spiders. This model clarifies the role resource depletion and resource renewal may play in vigilance in both people and other animals.

Idiopathic Hypersomnia-A Dynamic Simulation Model

Aims of the study

Commonly used approach to illness assessment focuses on the patient's actual state supplemented by binary records of past events and conditions. This research project was designed to explain subjective experience in idiopathic hypersomnia (IH) patients influenced by their clinical symptoms and comorbidities.

Material and Methods

Forty-three IH patients of both sexes (female 60.5%, male 39.5%) were assessed using a detailed structured examination. The interview covered neurologic, psychiatric, and internal medicine anamnesis, medication past and current, substance abuse, work impairment, detailed sleep-related data, specific sleep medication, and a full-length set of questionnaires including depression, quality of life, sleepiness, anxiety, fatigue, insomnia, and sleep inertia. The data were digitized and imported into statistical software (SPSS by IBM), and dynamic simulation software (Vensim by Ventana Systems Inc.) was used to build a causal loop diagram and stocks and flows diagram as a simulation structure.

Results

The overall raw data and simulation-based patterns fit at 76.1%. The simulation results also identified the parameters that contribute the most to patients' subjective experience. These included sleep inertia, the refreshing potential of naps, the quality of nocturnal sleep, and the social aspects of the patient's life. Psychiatric disorders influence the overall pattern at a surprisingly low level. The influence of medication has been studied in detail. Although its contribution to the dynamics looks marginal at first sight, it significantly influences the contribution of other variables to the overall patient experience of the disease.

Conclusion

Even the simplified dynamic structure designed by the research team reflects the real-life events in patients with IH at the acceptable level of 76.1% and suggests that a similar structure plays an important role in the course of the disease. Therapeutic focus on the parameters identified by the model should enhance the patients' subjective experience throughout illness duration and might even turn the progress from negative into positive. Further research is needed to understand the dynamics of idiopathic hypersomnia in greater detail to better understand the causes and design therapeutic approaches to improve patients' quality of life.