Variable rather than extreme slow reaction times distinguish brain states during sustained attention.

Variable rather than extreme slow reaction times distinguish brain states during sustained attention.
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DOI:
10.1038/s41598-021-94161-0
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发表时间:
2021-07-21
期刊:
影响因子:
4.6
通讯作者:
Esterman M
Esterman M
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Yamashita A;Rothlein D;Kucyi A;Valera EM;Germine L;Wilmer J;DeGutis J;Esterman M

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最佳注意力集中的一个常见行为标志是更快的反应或减少的反应变异性。我们之前的研究发现,在持续注意过程中,两种主导的大脑状态,这些状态在行为准确性和反应时间(RT)的变异性方面有所不同。然而,RT分布通常是正偏态的,具有长尾(即,反映偶尔的缓慢反应)。因此,更大的RT方差也可以用这个长尾来解释,而不是假设的正态分布周围的方差(即,反映了基于更快和更慢的响应的普遍的响应不稳定性)。解决这种模糊性对于更好地理解持续注意力的机制非常重要。在这里,使用超过20,000名参与者的大型数据集,他们执行了持续注意力任务,我们首先展示了exGuassian分布的实用性,可以将RT分解为策略因子,方差因子和长尾因子。然后,我们使用fMRI研究了两种大脑状态之间的差异因素。在两个独立的数据集上,结果明确表明,两种主导大脑状态之间的方差因子不同。这些研究结果表明,“次优”是不同的“慢”在行为和神经水平,并在理论和方法上指导未来的持续注意研究的影响。
A common behavioral marker of optimal attention focus is faster responses or reduced response variability. Our previous study found two dominant brain states during sustained attention, and these states differed in their behavioral accuracy and reaction time (RT) variability. However, RT distributions are often positively skewed with a long tail (i.e., reflecting occasional slow responses). Therefore, a larger RT variance could also be explained by this long tail rather than the variance around an assumed normal distribution (i.e., reflecting pervasive response instability based on both faster and slower responses). Resolving this ambiguity is important for better understanding mechanisms of sustained attention. Here, using a large dataset of over 20,000 participants who performed a sustained attention task, we first demonstrated the utility of the exGuassian distribution that can decompose RTs into a strategy factor, a variance factor, and a long tail factor. We then investigated which factor(s) differed between the two brain states using fMRI. Across two independent datasets, results indicate unambiguously that the variance factor differs between the two dominant brain states. These findings indicate that ‘suboptimal’ is different from ‘slow’ at the behavior and neural level, and have implications for theoretically and methodologically guiding future sustained attention research.
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