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Cognitive throughput and working memory raw scores consistently differentiate resilient and vulnerable groups to sleep loss
Sleep ( IF 5.6 ) Pub Date : 2021-08-01 , DOI: 10.1093/sleep/zsab197
Tess E Brieva 1 , Courtney E Casale 1 , Erika M Yamazaki 1 , Caroline A Antler 1 , Namni Goel 1
Affiliation  

Study Objectives Substantial individual differences exist in cognitive deficits due to sleep restriction (SR) and total sleep deprivation (TSD), with various methods used to define such neurobehavioral differences. We comprehensively compared numerous methods for defining cognitive throughput and working memory resiliency and vulnerability. Methods Forty-one adults participated in a 13-day experiment: 2 baseline, 5 SR, 4 recovery, and one 36 h TSD night. The Digit Symbol Substitution Test (DSST) and Digit Span Test (DS) were administered every 2 h. Three approaches (Raw Score [average SR performance], Change from Baseline [average SR minus average baseline performance], and Variance [intraindividual variance of SR performance]), and six thresholds (±1 standard deviation, and the best/worst performing 12.5%, 20%, 25%, 33%, 50%) classified Resilient/Vulnerable groups. Kendall’s tau-b correlations compared the group categorizations’ concordance within and between DSST number correct and DS total number correct. Bias-corrected and accelerated bootstrapped t-tests compared group performance. Results The approaches generally did not categorize the same participants into Resilient/Vulnerable groups within or between measures. The Resilient groups categorized by the Raw Score approach had significantly better DSST and DS performance across all thresholds on all study days, while the Resilient groups categorized by the Change from Baseline approach had significantly better DSST and DS performance for several thresholds on most study days. By contrast, the Variance approach showed no significant DSST and DS performance group differences. Conclusion Various approaches to define cognitive throughput and working memory resilience/vulnerability to sleep loss are not synonymous. The Raw Score approach can be reliably used to differentiate resilient and vulnerable groups using DSST and DS performance during sleep loss.

中文翻译:

认知吞吐量和工作记忆原始分数始终将弹性和弱势群体与睡眠不足区分开来

研究目标 由于睡眠限制 (SR) 和完全睡眠剥夺 (TSD) 导致的认知缺陷存在显着的个体差异,有多种方法用于定义此类神经行为差异。我们全面比较了许多定义认知吞吐量和工作记忆弹性和脆弱性的方法。方法 41 名成年人参加了为期 13 天的实验:2 次基线、5 次 SR、4 次恢复和 1 次 36 小时 TSD 夜。每 2 小时进行一次数字符号替换测试 (DSST) 和数字跨度测试 (DS)。三种方法(原始分数 [平均 SR 性能]、从基线变化 [平均 SR 减去平均基线性能] 和方差 [SR 性能的个体内方差])和六个阈值(±1 标准偏差,最佳/最差表现 12.5 %, 20%, 25%, 33%, 50%) 归类为弹性/弱势群体。Kendall 的 tau-b 相关性比较了组分类在 DSST 正确数和 DS 总数正确内和之间的一致性。偏差校正和加速自举 t 检验比较了组的表现。结果 这些方法通常不会将相同的参与者分类为测量内或测量之间的弹性/弱势群体。在所有研究日,按原始分数方法分类的弹性组在所有阈值上的 DSST 和 DS 性能显着提高,而按从基线变化方法分类的弹性组在大多数研究日的几个阈值上具有显着更好的 DSST 和 DS 性能。相比之下,方差方法没有显示出显着的 DSST 和 DS 性能组差异。结论 定义认知吞吐量和工作记忆弹性/易受失眠影响的各种方法并不是同义词。原始分数方法可以可靠地使用 DSST 和 DS 在睡眠丧失期间的表现来区分弹性和弱势群体。
更新日期:2021-08-01
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