Non-invasive neurophysiological measures of learning: A meta-analysis

Publication date: Available online 6 February 2019Source: Neuroscience & Biobehavioral ReviewsAuthor(s): Angelica M. Tinga, Tycho T. de Back, Max M. LouwerseAbstractIn 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.

Source: Neuroscience and Biobehavioral Reviews - February 6, 2019 Category: Neuroscience Source Type: research