Biological Rhythms Research Laboratory, Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, USA.
Sleep. 2021 Dec 10;44(12). doi: 10.1093/sleep/zsab197.
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.
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. .
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.
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.
由于睡眠限制（SR）和总睡眠剥夺（TSD），个体的认知缺陷存在很大差异，并且已经使用各种方法来定义这种神经行为差异。我们全面比较了定义认知吞吐量和工作记忆弹性和脆弱性的多种方法。
41 名成年人参加了一项为期 13 天的实验：2 个基线、5 个 SR、4 个恢复和一个 36 小时 TSD 之夜。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）。采用三种方法（原始分数[平均 SR 表现]、从基线变化[平均 SR 减去平均基线表现]和方差[SR 表现的个体内方差]）和六个阈值（±1 标准差和表现最好/最差的 12.5%、20%、25%、33%、50%）将有弹性/脆弱的组分类。肯德尔氏 tau-b 相关系数比较了 DSST 正确数和 DS 总数正确的组分类在内部和之间的一致性。偏置校正和加速 bootstrap t 检验比较了组性能。
这些方法通常不会将相同的参与者归类为同一措施内或措施之间的有弹性/脆弱的组。根据原始分数方法进行分类的有弹性的组在所有研究日的所有阈值上的 DSST 和 DS 表现都显著更好，而根据从基线变化的方法进行分类的有弹性的组在大多数研究日的几个阈值上的 DSST 和 DS 表现都显著更好。相比之下，方差方法没有显示出 DSST 和 DS 表现的显著组间差异。
定义认知吞吐量和工作记忆弹性/对睡眠不足的脆弱性的各种方法并不相同。原始分数方法可以可靠地用于区分睡眠不足期间的 DSST 和 DS 表现的有弹性和脆弱的组。
