Rappaport Brent Ian, Shankman Stewart A, Glazer James E, Buchanan Savannah N, Weinberg Anna, Letkiewicz Allison M
Department of Psychiatry, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Department of Psychology, McGill University, Montreal, Canada.
Cogn Affect Behav Neurosci. 2025 Apr;25(2):311-328. doi: 10.3758/s13415-024-01222-8. Epub 2024 Oct 23.
The flanker task is a widely used measure of cognitive control abilities. Drift-diffusion modeling of flanker task behavior can yield separable parameters of cognitive control-related subprocesses, but the parameters' psychometrics are not well-established. We examined the reliability and validity of four behavioral measures: (1) raw accuracy, (2) reaction time (RT) interference, (3) NIH Toolbox flanker score, and (4) two drift-diffusion model (DDM) parameters-drift rate and boundary separation-capturing evidence accumulation efficiency and speed-accuracy trade-off, respectively. Participants from two independent studies - one cross-sectional (N = 381) and one with three timepoints (N = 83) - completed the flanker task while electroencephalography data were collected. Across both studies, drift rate and boundary separation demonstrated comparable split-half and test-retest reliability to accuracy, RT interference, and NIH Toolbox flanker score, but better incremental convergent validity with psychophysiological measures (i.e., the error-related negativity; ERN) and neuropsychological measures of cognitive control than the other behavioral indices. Greater drift rate (i.e., faster and more accurate responses) to congruent and incongruent stimuli, and smaller boundary separation to incongruent stimuli were related to 1) larger ERN amplitudes (in both studies) and 2) faster and more accurate inhibition and set-shifting over and above raw accuracy, reaction time, and NIH Toolbox flanker scores (in Study 1). Computational models, such as DDM, can parse behavioral performance into subprocesses that exhibit comparable reliability to other scoring approaches, but more meaningful relationships with other measures of cognitive control. The application of these computational models may be applied to existing data and enhance the identification of cognitive control deficits in psychiatric disorders.
侧翼任务是一种广泛使用的认知控制能力测量方法。侧翼任务行为的漂移扩散模型可以产生与认知控制相关子过程的可分离参数,但这些参数的心理测量学特性尚未得到充分确立。我们检验了四种行为测量指标的信度和效度:(1)原始准确率,(2)反应时干扰,(3)美国国立卫生研究院工具箱侧翼任务得分,以及(4)两个漂移扩散模型(DDM)参数——漂移率和边界分离,分别反映证据积累效率和速度-准确性权衡。来自两项独立研究的参与者——一项横断面研究(N = 381)和一项有三个时间点的研究(N = 83)——完成了侧翼任务,同时收集了脑电图数据。在两项研究中,漂移率和边界分离表现出与准确率、反应时干扰和美国国立卫生研究院工具箱侧翼任务得分相当的分半信度和重测信度,但与心理生理测量指标(即错误相关负波;ERN)和认知控制的神经心理学测量指标相比,具有更好的增量收敛效度,优于其他行为指标。对一致和不一致刺激的更大漂移率(即更快、更准确的反应),以及对不一致刺激的更小边界分离与以下方面有关:1)更大的ERN波幅(在两项研究中均如此),以及2)在原始准确率、反应时和美国国立卫生研究院工具箱侧翼任务得分之上,更快、更准确的抑制和定势转换(在研究1中)。像DDM这样的计算模型可以将行为表现解析为与其他评分方法具有可比信度的子过程,但与其他认知控制测量指标具有更有意义的关系。这些计算模型的应用可以应用于现有数据,并增强对精神疾病中认知控制缺陷的识别。