Objective:Translatability of preclinical results remains a major obstacle in neuropsychiatric research. Even when cognitive tests in preclinical models show translational validity for human testing, with sensitivity to clinical deficits, there remains the issue of heterogeneity among human participants. Norming of performance on cognitive tasks enable corrections for any differences in performance that may arise from the influence of socioeconomic factors, and thus a more direct comparison with preclinical testing results. The 5-choice continuous performance task (5C-CPT) is a test sensitive to changes in sustained attention and cognitive control in rodent manipulations and clinical populations, including schizophrenia and bipolar disorder. Herein, we present normed results of 5C-CPT data from a cohort of human participants, enabling greater comparison to future clinical and rodent testing.Participants and Methods:5C-CPT data were generated from a range of participants from the Translational Methamphetamine AIDS Research Center (n=82) and a study of bipolar disorder (n=45). Participant demographics were as follows: Age M=38.5, SD=16.7, Education: M=14.5, SD=1.9, 45% female, 10% Asian, 17% African American, 27% Hispanic, and 46% non-Hispanic White. We used the test2norm R-package to create norms for each of the major outcomes from the 5C-CPT. Non-normally distributed raw scores were transformed to generate more normally distributed data needed for the norming process. Raw scores were first converted into uniform scaled scores that range from 0-20 where a higher score indicated better performance. We then generated T-score formulas, which are standardized residuals and scaled to have a mean of 50 and standard deviation of 10. The residuals are obtained from regressions, modeled using multiple fractional polynomial method (MFP), which regresses scaled scores on demographic variables, which a user wishes to control for (gender, age, education, ethnicity, etc.). MFP models allow to fit non-linear effects for numeric demographic factors (e.g., age), if such effects exist.Results:New, demographically corrected T-score formulas were calculated for each major outcome of the 5C-CPT: reaction time (MCL), reaction time variability (VarRT), dprime, hit rate (HR) and false-alarm rate (FAR). MFP models showed that age had a significant effect on MCL, VarRT, dprime, and HR (all p<0.01), while gender only showed a significant effect for MCL and VarRT (all p<0.05). Interestingly, education and ethnicity did not show a significant effect for any MFP model and none of the demographic factors (age, education, gender, ethnicity) were significant in the model for FAR. As defined in the test2norm package, all scaled scores had a mean of 10 and SD of 3 and all T-scores had a mean of 50 and SD of 10.Conclusions:The 5C-CPT is a test of attention and cognitive control available for human testing, reverse-translated from rodent studies. The normative data generated here will enable future comparisons of data without the need for additional control studies. Furthermore, comparing these normative data to manipulations will enable further comparisons to rodent testing, with manipulations relative to baseline becoming more meaningful. Thus, the 5C-CPT is a viable tool for conducting cross-species translational research toward developing novel therapeutics that treat dysfunctional attentional and cognitive control.

中文翻译：

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17 注意力和认知控制的反向翻译 5 项选择连续表现测试 (5C-CPT) 规范

目的：临床前结果的可转化性仍然是神经精神病学研究的主要障碍。即使临床前模型中的认知测试显示出人类测试的转化有效性，并且对临床缺陷敏感，人类参与者之间仍然存在异质性问题。对认知任务的表现进行标准化可以纠正可能因社会经济因素的影响而产生的任何表现差异，从而与临床前测试结果进行更直接的比较。五项选择连续表现任务（5C-CPT）是一项对啮齿动物操作和临床人群（包括精神分裂症和双相情感障碍）持续注意力和认知控制变化敏感的测试。在此，我们展示了一组人类参与者的 5C-CPT 数据标准化结果，以便与未来的临床和啮齿动物测试进行更好的比较。参与者和方法：5C-CPT 数据是由转化甲基苯丙胺艾滋病研究中心的一系列参与者生成的(n=82) 和躁郁症研究 (n=45)。参与者人口统计数据如下：年龄 M=38.5，SD=16.7，教育程度：M=14.5，SD=1.9，45% 女性，10% 亚洲人，17% 非裔美国人，27% 西班牙裔，46% 非西班牙裔白人。我们使用 test2norm R 包为 5C-CPT 的每个主要结果创建规范。非正态分布的原始分数经过转换以生成标准化过程所需的更正态分布的数据。原始分数首先转换为统一的分数，范围为 0-20，分数越高表示性能越好。然后，我们生成 T 分数公式，该公式是标准化残差，并缩放为平均值为 50、标准差为 10。残差是通过使用多重分数多项式方法 (MFP) 建模的回归获得的，该方法对人口变量的缩放分数进行回归，用户希望控制的内容（性别、年龄、教育程度、种族等）。MFP 模型允许拟合数字人口统计因素（例如年龄）的非线性效应（如果存在此类效应）。 结果：针对 5C-CPT 的每个主要结果计算了新的、人口统计校正的 T 分数公式：反应时间（MCL） )、反应时间变异性 (VarRT)、dprime、命中率 (HR) 和误报率 (FAR)。MFP模型显示年龄对MCL、VarRT、dprime和HR有显着影响（均p<0.01），而性别仅对MCL和VarRT有显着影响（均p<0.05）。有趣的是，教育和种族对任何 MFP 模型均未显示出显着影响，并且人口因素（年龄、教育、性别、种族）在 FAR 模型中均不显着。根据 test2norm 包中的定义，所有量表分数的平均值为 10，SD 为 3，所有 T 分数的平均值为 50，SD 为 10。结论：5C-CPT 是一项注意力和认知控制测试，适用于人体测试，从啮齿动物研究反向翻译。此处生成的规范数据将使将来能够进行数据比较，而无需进行额外的对照研究。此外，将这些规范数据与操作进行比较将能够进一步与啮齿动物测试进行比较，相对于基线的操作变得更有意义。因此，5C-CPT 是进行跨物种转化研究的可行工具，旨在开发治疗注意力和认知控制功能障碍的新型疗法。