AUTHOR=Puszta András , Pertich Ákos , Giricz Zsófia , Nyujtó Diána , Bodosi Balázs , Eördegh Gabriella , Nagy Attila 

TITLE=Predicting Stimulus Modality and Working Memory Load During Visual- and Audiovisual-Acquired Equivalence Learning

JOURNAL=Frontiers in Human Neuroscience

VOLUME=Volume 14 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2020.569142

DOI=10.3389/fnhum.2020.569142

ISSN=1662-5161

ABSTRACT=EEG correlates of the associative working memory load have been studied widely. However, within this process, the effect of stimulus modality on EEG patterns is not well understood. We reanalysed EEG datasets from one of our earlier studies that were recorded during visual and audio-visual equivalence learning tasks. The number of associations that needed to be maintained (working memory load) in the working memory was increased using a staircase method during the acquisition phase of the tasks. We used the support vector machine algorithm to predict the working memory load and the stimulus modality using the power, phase connectivity and cross-frequency coupling values obtained during the time segments with different working memory load in visual and audio-visual tasks. We observed high accuracy (>90%) in predicting the stimulus modality based on the power spectral density and from the theta–beta cross-frequency coupling. However, the accuracy in predicting the working memory load was higher (≥75% accuracy) than in predicting the stimulus modality (which was around chance level) using theta and alpha phase connectivity. This connectivity was the highest between the frontal and parietooccipital channels in low working memory load conditions. These results validate our earlier studies that dissociated the stimulus modality based on power–spectra and cross-frequency coupling during equivalence learning, and they further emphasise the importance of alpha and theta frontoparietal connectivity in the working memory load.