How sleeping minds decide: state-specific reconfigurations of lexical decision-making
Xia, T.; Hu, C.-P.; Turker, B.; Musat, E. M.; Naccache, L.; Arnulf, I.; Oudiette, D.; Hu, X.
10.1101/2025.03.10.642374 bioRxivShow abstract
Decision-making is a core cognitive function that enables adaptive behavior across diverse contexts. While extensively studied in wakefulness, its persistence and reconfiguration across sleep states remain poorly understood. Here, we use computational modeling to examine lexical decision-making across wakefulness, N1 sleep, and lucid REM sleep in both healthy participants (HP) and participants with narcolepsy (NP). Using facial electromyography (EMG) to capture real-time behavioral responses to spoken words and pseudowords during sleep, we quantify how decision-making strategies adapt under different sleep and consciousness states. Our findings reveal two key insights. First, decision-making mechanisms are dynamically reconfigured across sleep states. In N1 sleep, the advantage for word (vs. pseudoword) judgments is supported by faster sensory encoding and motor preparation, combined with efficient evidence accumulation. In contrast, in lucid REM sleep, the word advantage is driven exclusively by enhanced evidence accumulation, while sensory encoding and motor preparation remain unchanged. Second, cross-state comparisons reveal distinct patterns of preservation and impairment. In N1 sleep, word judgment remains largely intact, whereas pseudoword judgment is significantly impaired, characterized by prolonged stimulus encoding, delayed motor preparation, and reduced evidence accumulation. In contrast, lucid REM sleep is marked by a global reduction in processing efficiency, reflected in slower evidence accumulation and elevated decision thresholds for both words and pseudowords. These results demonstrate that rather than being uniformly degraded, decision-making is dynamically reconfigured across sleep stages, reflecting adaptive neurocognitive strategies that sustain cognition in altered states of consciousness. By identifying state-specific computational mechanisms, this study provides new insights into the brains resilience and flexibility under changing cognitive and physiological conditions.
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