The impact of sleep loss on decision making: Opening the cognitive black box

The impact of sleep loss on decision-making is well-documented, yet current quantitative methods often obscure the cognitive mechanisms underlying these impairments. This review examines evidence from key studies on how sleep deprivation affects decision-making domains, including risk propensity, effort and delay discounting, Bayesian reasoning, and cognitive flexibility. We critique the prevalent reliance on global behavioural metrics, highlighting three key limitations: 1) sleep-driven cognitive effects may be masked despite non-significant behavioural outcomes, 2) alternative cognitive strategies are often overlooked, and 3) these metrics fail to incorporate advances in cognitive neuroscience. To address these issues, we advocate for integrating computational cognitive models with existing quantitative methods. These models provide precise estimates of latent cognitive processes often missed by conventional analyses. As an exemplar, we reanalyse previously published data, revealing sleep-related deficits in value sensitivity and increased decision noise. These insights highlight the utility of computational cognitive models in supplementing traditional methods to uncover how sleep loss affects specific cognitive processes essential for decision-making. Beyond improving mechanistic insights, computational cognitive models may enhance the accuracy and interpretability of sleep research and inform the development of targeted interventions to mitigate decision-making impairments caused by sleep loss.