Unravelling the multisensory learning advantage: Different patterns of within and across frequency-specific interactions drive uni- and multisensory neuroplasticity

•Multilayered connectivity analysis of EEG data models multisensory processing.•Multisensory vs. uni-sensory learning interventions induce distinct neural changes.•Multisensory training induces increased synchronization within the beta band.•Unisensory training modifies cross-frequency interaction.•...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:NeuroImage (Orlando, Fla.) Fla.), 2024-05, Vol.291, p.120582-120582, Article 120582
Hauptverfasser: Paraskevopoulos, Evangelos, Anagnostopoulou, Alexandra, Chalas, Nikolas, Karagianni, Maria, Bamidis, Panagiotis
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•Multilayered connectivity analysis of EEG data models multisensory processing.•Multisensory vs. uni-sensory learning interventions induce distinct neural changes.•Multisensory training induces increased synchronization within the beta band.•Unisensory training modifies cross-frequency interaction.•A theoretical framework aims to explain the advantage of multisensory learning. In the field of learning theory and practice, the superior efficacy of multisensory learning over uni-sensory is well-accepted. However, the underlying neural mechanisms at the macro-level of the human brain remain largely unexplored. This study addresses this gap by providing novel empirical evidence and a theoretical framework for understanding the superiority of multisensory learning. Through a cognitive, behavioral, and electroencephalographic assessment of carefully controlled uni-sensory and multisensory training interventions, our study uncovers a fundamental distinction in their neuroplastic patterns. A multilayered network analysis of pre- and post- training EEG data allowed us to model connectivity within and across different frequency bands at the cortical level. Pre-training EEG analysis unveils a complex network of distributed sources communicating through cross-frequency coupling, while comparison of pre- and post-training EEG data demonstrates significant differences in the reorganizational patterns of uni-sensory and multisensory learning. Uni-sensory training primarily modifies cross-frequency coupling between lower and higher frequencies, whereas multisensory training induces changes within the beta band in a more focused network, implying the development of a unified representation of audiovisual stimuli. In combination with behavioural and cognitive findings this suggests that, multisensory learning benefits from an automatic top-down transfer of training, while uni-sensory training relies mainly on limited bottom-up generalization. Our findings offer a compelling theoretical framework for understanding the advantage of multisensory learning.
ISSN:1053-8119
1095-9572
DOI:10.1016/j.neuroimage.2024.120582