Drifting from slow to "D'oh!": working memory capacity and mind wandering predict extreme reaction times and executive control errors.
Drifting from slow to "D'oh!": working memory capacity and mind wandering predict extreme reaction times and executive control errors.
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DOI：
10.1037/a0025896
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发表时间：
2012-05
影响因子：
2.6
通讯作者：
Kane, Michael J.
中科院分区：
文献类型：
--
作者：
McVay, Jennifer C.;Kane, Michael J.
一项结合实验、个体差异和思想抽样的研究测试了执行注意力的预测（例如，）和配位结合（例如，）工作记忆容量（WMC）我们评估了288名受试者的WMC和他们在持续注意任务中的表现和走神率;受试者完成了需要对习惯进行执行控制的去/不去版本，或者没有执行控制的警惕版本。我们进一步结合到的数据：（1）测量WMC和注意失误对最差表现规则和反应时（RT）分布的尾部或τ参数的贡献;（2）评估WMC和走神报告预测了来自定量证据积累RT模型的哪些参数，以及（3）考虑受试者内RT模式-特别是，超速--作为走神的潜在客观标志。我们发现WMC仅在某些条件下预测动作和思想控制，注意力缺失（由TUT报告和证据积累中的漂移率变异性表明）有助于τ，性能准确性以及WMC与它们的关联，并且走神体验不能通过试验到试验RT的变化来预测，因此它们不能总是从客观性能测量中推断出来。
A combined experimental, individual-differences, and thought-sampling study tested the predictions of executive attention (e.g.,) and coordinative binding (e.g.,) theories of working memory capacity (WMC). We assessed 288 subjects’ WMC and their performance and mind-wandering rates during a sustained-attention task; subjects completed either a go/no-go version requiring executive control over habit, or a vigilance version that did not. We further combined the data with those from to: (1) gauge the contributions of WMC and attentional lapses to the worst-performance rule and the tail, or τ parameter, of response time (RT) distributions; (2) assess which parameters from a quantitative evidence-accumulation RT model were predicted by WMC and mind-wandering reports, and (3) consider intra-subject RT patterns – particularly, speeding – as potential objective markers of mind wandering. We found that WMC predicted action and thought control in only some conditions, that attentional lapses (indicated by TUT reports and drift-rate variability in evidence accumulation) contributed to τ, performance accuracy, and WMC’s association with them, and that mind-wandering experiences were not predicted by trial-to-trial RT changes, and so they cannot always be inferred from objective performance measures.
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影响因子：
3.5
作者：
Conway, ARA;Cowan, N;Bunting, MF
通讯作者：
Bunting, MF
影响因子：
5.4
作者：
COHEN, JD;SERVANSCHREIBER, D
通讯作者：
SERVANSCHREIBER, D
DOI：
10.1073/pnas.0900234106
发表时间：
2009-05-26
影响因子：
11.1
作者：
Christoff, Kalina;Gordon, Alan M.;Schooler, Jonathan W.
通讯作者：
Schooler, Jonathan W.
影响因子：
3.5
作者：
Donkin, Chris;Brown, Scott;Wagenmakers, Eric-Jan
通讯作者：
Wagenmakers, Eric-Jan
影响因子：
3.5
作者：
Colflesh, Gregory J. H.;Conway, Andrew R. A.
通讯作者：
Conway, Andrew R. A.