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

András Puszta1,2,3, Ákos Pertich1, Zsófia Giricz1

  • 1Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway.

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|November 2, 2020
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Summary

This study reveals how electroencephalography (EEG) patterns differ between visual and audiovisual tasks. It highlights the role of theta and alpha brainwave connectivity in working memory (WM) load.

Keywords:
EEGacquired equivalence associative learning taskmachine learingstimulus modalityworking memory load (WML)

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Area of Science:

  • Cognitive Neuroscience
  • Neuroimaging

Background:

  • Extensive research exists on electroencephalography (EEG) correlates of associative working memory (WM) load.
  • The influence of stimulus modality on EEG patterns during WM processes remains less understood.

Purpose of the Study:

  • To investigate the effect of stimulus modality (visual vs. audiovisual) on EEG patterns during associative working memory.
  • To re-analyze existing EEG data to identify predictive markers for WM load and modality.

Main Methods:

  • Re-analysis of EEG datasets from visual and audiovisual equivalence learning tasks.
  • Utilized a staircase method to manipulate working memory load.
  • Employed support vector machine algorithms to predict WM load and stimulus modality using power spectral density, phase connectivity, and cross-frequency coupling (CFC).

Main Results:

  • High accuracy (>90%) in predicting stimulus modality using power spectral density and theta-beta cross-frequency coupling (CFC).
  • Predicting working memory load (≥75% accuracy) was more successful than predicting stimulus modality using theta and alpha phase connectivity.
  • Low working memory load showed maximal frontal and parieto-occipital connectivity in theta and alpha bands.

Conclusions:

  • Findings validate previous studies dissociating stimulus modality using power spectra and CFC.
  • Emphasizes the crucial role of theta and alpha frontoparietal connectivity in working memory load.
  • EEG analysis offers insights into modality-specific and load-dependent neural mechanisms in working memory.