Department of Cognitive Science & Artificial Intelligence, Tilburg University, Dante Building, Room D 330, Warandelaan 2, 5037 AB Tilburg, The Netherlands.
Department of Cognitive Science & Artificial Intelligence, Tilburg University, Dante Building, Room D 330, Warandelaan 2, 5037 AB Tilburg, The Netherlands.
Neurosci Biobehav Rev. 2019 Apr;99:59-89. doi: 10.1016/j.neubiorev.2019.02.001. Epub 2019 Feb 6.
In a meta-analysis of 113 experiments we examined neurophysiological outcomes of learning, and the relationship between neurophysiological and behavioral outcomes of learning. Findings showed neurophysiology yielding large effect sizes, with the majority of studies examining electroencephalography and eye-related outcome measures. Effect sizes on neurophysiological outcomes were smaller than effect sizes on behavioral outcomes, however. Neurophysiological outcomes were, but behavioral outcomes were not, influenced by several modulating factors. These factors included the sensory system in which learning took place, number of learning days, whether feedback on performance was provided, and age of participants. Controlling for these factors resulted in the effect size differences between behavior and neurophysiology to disappear. The findings of the current meta-analysis demonstrate that neurophysiology is an appropriate measure in assessing learning, particularly when taking into account factors that could have an influence on neurophysiology. We propose a first model to aid further studies that are needed to examine the exact interplay between learning, neurophysiology, behavior, individual differences, and task-related aspects.
在对 113 个实验的荟萃分析中,我们研究了学习的神经生理学结果,以及学习的神经生理学和行为结果之间的关系。研究结果表明,神经生理学产生了较大的效应量,其中大多数研究都检查了脑电图和与眼睛相关的结果测量。然而,神经生理学结果的效应量小于行为结果的效应量。神经生理学结果受到几个调节因素的影响,但行为结果不受影响。这些因素包括学习发生的感觉系统、学习天数、是否提供对表现的反馈以及参与者的年龄。控制这些因素后,行为和神经生理学之间的效应量差异就消失了。本荟萃分析的研究结果表明,神经生理学是评估学习的一种合适的方法,特别是在考虑到可能对神经生理学产生影响的因素时。我们提出了一个初步模型,以帮助进一步研究,需要研究学习、神经生理学、行为、个体差异和与任务相关方面之间的确切相互作用。