Program in Neurosciences and Mental Health, Hospital for Sick Children Research Institute, Toronto, Canada; Institute of Medical Sciences and Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Canada.
Neuropsychology and Functional Neuroimaging Research Group at Center for Research in Cognition and Neurosciences (CRCN) and ULB Neurosciences Institute (UNI), Brussels, Belgium; Laboratoire de Cartographie fonctionnelle du Cerveau, UNI, ULB, Brussels, Belgium.
Neuropsychologia. 2019 Apr;127:48-56. doi: 10.1016/j.neuropsychologia.2019.02.007. Epub 2019 Feb 13.
In previous studies we have provided evidence that performance in speeded response tasks with infrequent target stimuli reflects both automatic and controlled cognitive processes, based on differences in reaction time (RT) and task-related brain responses (Cheyne et al. 2012, Isabella et al. 2015). Here we test the hypothesis that such shifts in cognitive control may be influenced by changes in cognitive load related to stimulus predictability, and that these changes can be indexed by task-evoked pupillary responses (TEPR). We manipulated stimulus predictability using fixed stimulus sequences that were unknown to the participants in a Go/Switch task (requiring a switch response on 25% of trials) while monitoring TEPR as a measure of cognitive load in 12 healthy adults. Results showed significant improvement in performance (reduced RT, increased efficiency) for repeated sequences compared to occasional deviant sequences (10% probability) indicating that incidental learning of the predictable sequences facilitated performance. All behavioral measures varied between Switch and Go trials (RT, efficiency), however mean TEPR amplitude (mTEPR) and latency to maximum pupil dilation were particularly sensitive to Go/Switch. Results were consistent with the hypothesis that mTEPR indexes cognitive load, whereas TEPR latency indexes time to response selection, independent from response execution. The present study provides evidence that incidental pattern learning during response inhibition tasks may modulate several cognitive processes including cognitive load, effort, response selection and execution, which can in turn have differential effects on measures of performance. In particular, we demonstrate that reaction time may not be indicative of underlying cognitive load.
在之前的研究中,我们提供了证据表明,在频繁出现目标刺激的快速反应任务中,基于反应时间(RT)和与任务相关的大脑反应的差异,表现反映了自动和受控的认知过程(Cheyne 等人,2012 年;Isabella 等人,2015 年)。在这里,我们测试了这样一种假设,即认知控制的这种转变可能受到与刺激可预测性相关的认知负荷变化的影响,并且这些变化可以通过任务诱发的瞳孔反应(TEPR)来标记。我们使用参与者未知的固定刺激序列在 Go/Switch 任务中操纵刺激可预测性(要求在 25%的试验中进行切换响应),同时监测 TEPR 作为认知负荷的测量指标在 12 名健康成年人中。结果表明,与偶尔出现的异常序列(10%的概率)相比,重复序列的性能明显提高(RT 降低,效率提高),表明对可预测序列的偶然学习促进了性能。所有行为测量值在 Switch 和 Go 试验之间均有所变化(RT,效率),但是平均 TEPR 幅度(mTEPR)和最大瞳孔扩张的潜伏期对 Go/Switch 特别敏感。结果与假设一致,即 mTEPR 指标认知负荷,而 TEPR 潜伏期指标响应选择的时间,独立于响应执行。本研究提供了证据表明,反应抑制任务中的偶然模式学习可能调节包括认知负荷、努力、响应选择和执行在内的几种认知过程,这些过程反过来又会对性能测量产生不同的影响。特别是,我们证明反应时间可能不能指示潜在的认知负荷。