Lapses in attention are ubiquitous and, unfortunately, the cause of many tragic accidents. One potential solution may be to develop assistance systems which can use objective, physiological signals to monitor attention levels and predict a lapse in attention before it occurs. As it stands, it is unclear which physiological signals are the most reliable markers of inattention, and even less is known about how reliably they will work in a more naturalistic setting. My project aims to address these questions across two experiments: a lab-based experiment and a more ‘real-world’ experiment. In this talk I will present the findings from my lab experiment, in which we combined EEG and pupillometry to detect markers of inattention during two computerised sustained attention tasks. I will then present the methods for my second, more ‘naturalistic’ experiment in which we use the same methods (EEG and pupillometry) to examine whether these markers can still be extracted from noisier data.

Three studies conducted in the context of PhD work (UNIL) aimed at proving evidence to address the question of potential gender differences in trait anxiety and executive control biases on behavioral efficacy. In scope were male and female non-clinical samples of adult young age that performed non-emotional tasks assessing basic attentional functioning (Attention Network Test – Interactions, ANT-I), sustained attention (Test of Variables of Attention, TOVA), and visual recognition abilities (Object in Location Recognition Task, OLRT). Results confirmed the intricate nature of the relationship between gender and health trait anxiety through the lens of their impact on processing efficacy in males and females. The possibility of a gendered theory in trait anxiety biases is discussed.

Daily caffeine consumption and chronic sleep restriction are highly prevalent in society. It is well established that acute caffeine intake under controlled conditions enhances vigilance and promotes wakefulness but can also delay sleep initiation and reduce electroencephalographic (EEG) markers of sleep intensity, particularly in susceptible individuals. To investigate whether these effects are also present during chronic consumption of coffee/caffeine, we recently conducted several complementary studies. We examined whether repeated coffee intake in dose and timing mimicking ‘real world’ habits maintains simple and complex attentional processes during chronic sleep restriction, such as during a busy work week. We found in genetically caffeine-sensitive individuals that regular coffee (300 mg caffeine/day) benefits most attentional tasks for 3-4 days when compared to decaffeinated coffee. Genetic variants were also used in the population-based HypnoLaus cohort, to investigate whether habitual caffeine consumption causally affects time to fall asleep, number of awakenings during sleep, and EEG-derived sleep intensity. The multi-level statistical analyses consistently showed that sleep quality was virtually unaffected when >3 caffeine-containing beverages/day were compared to 0-3 beverages/day. This conclusion was further corroborated by quantifying the sleep EEG in the laboratory in habitual caffeine consumers. Compared to placebo, daily intake of 3 x 150 mg caffeine over 10 days did not strongly impair nocturnal sleep nor subjective sleep quality in good sleepers. Finally, we tested whether an engineered delayed, pulsatile-release caffeine formula can improve the quality of morning awakening in sleep-restricted volunteers. We found that 160 mg caffeine taken at bedtime ameliorated the quality of awakening, increased positive and reduced negative affect scores, and promoted sustained attention immediately upon scheduled wake-up. Such an approach could prevent over-night caffeine withdrawal and provide a proactive strategy to attenuate disabling sleep inertia. Taken together, the studies suggest that common coffee/caffeine intake habits can transiently attenuate detrimental consequences of reduced sleep virtually without disturbing subjective and objective markers of sleep quality. Nevertheless, coffee/caffeine consumption cannot compensate for chronic sleep restriction.