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Commonality and Diversity of Impairments in Inhibitory Tasks After Total Sleep Deprivation: Evidence from Drift Diffusion Model

睡眠剥夺 认知 心理学 睡眠(系统调用) 睡眠剥夺对认知功能的影响 神经科学 听力学 任务(项目管理) 抑制性突触后电位 基本认知任务 警惕(心理学) 抑制性控制 贫困 反应抑制 非快速眼动睡眠 认知抑制 发展心理学 认知心理学 慢波睡眠 情感(语言学) 睡眠阶段 唤醒
作者
Yixuan Cao,Jiaorong Luo,Jia-Hui Li,Ling Wang,Ning Ma
出处
期刊:Sleep [Oxford University Press]
标识
DOI:10.1093/sleep/zsaf355
摘要

Abstract Study Objectives This study investigated the effects of total sleep deprivation on two key sub-components of inhibitory control—interference inhibition and response inhibition—and examined whether sleep deprivation affects these components through shared or distinct cognitive mechanisms. Methods Thirty-six healthy adults (mean age ± SD: 24.83 ± 2.16 years) completed the Flanker and Go/No-Go tasks, which respectively measure interference inhibition and response inhibition, under both normal sleep and total sleep deprivation conditions. Two variants of the Drift Diffusion Model were applied to decompose the behavioral performance of each task into latent cognitive processes. Results Total sleep deprivation impaired overall behavioral performance (slower reaction times and reduced accuracy) in both tasks. It also led to a marginally significant increase in false alarms in the Go/No-Go task, while interference effects in the Flanker task remained unchanged. Moreover, drift-diffusion modeling revealed parallel impairments in information processing after sleep deprivation, as reflected by the reduction in drift rates across both tasks and decreased peak amplitude of task-irrelevant activation in the Flanker task. Furthermore, the decision threshold and starting point in the Go/No-Go task decreased after sleep deprivation. Conclusions Both the Flanker and Go/No-Go tasks are undermined by sleep deprivation due to the generally degraded central information processing, while sleep loss differently impacts the sub-components of inhibitory control with only response inhibition being impaired. These findings demonstrate the practicability of computational modeling in uncovering latent cognitive deficits obscured by traditional behavioral metrics.
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