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

Non-invasive neurophysiological measures of learning: A meta-analysis. Angelica M.Tinga, Tycho T. de Back, Max M. Louwerse. Neuroscience & Biobehavioral Reviews, Volume 99, April 2019, Pages 59-89. https://doi.org/10.1016/j.neubiorev.2019.02.001

Highlights
• Non-invasive neurophysiology yields large effect sizes in learning over time.
• Effect sizes of learning on neurophysiology are smaller than on behavior.
• Neurophysiology is influenced by individual differences and task-related aspects.
• These results suggest that neurophysiology is an appropriate measure in assessing learning.
• A model on learning, behavior and neurophysiology is proposed to guide future research.

Abstract: 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.