Uni-Vs.MultisensoryTraining/datacite.yml

# Metadata for DOI registration according to DataCite Metadata Schema 4.1.
# For detailed schema description see https://doi.org/10.5438/0014

## Required fields

# The main researchers involved. Include digital identifier (e.g., ORCID)
# if possible, including the prefix to indicate its type.
authors:
  -
    firstname: "Evangelos"
    lastname: "Paraskevopoulos"
    affiliation: "UCY"
    id: ""
  -
    firstname: "Alexandra"
    lastname: "Anagnostopoulou"
    affiliation: "AUTH"
    id: ""
  -
    firstname: "Nikolas"
    lastname: "Chalas"
    affiliation: "IBB"
  -
    firstname: "Maria"
    lastname: "Karagianni"
    affiliation: "AUTH"
  -
    firstname: "Panagiotis"
    lastname: "Bamidis"
    affiliation: "AUTH"

# A title to describe the published resource.
title: "Unravelling the multisensory learning advantage: Different patterns of within and across frequency-specific interactions drive uni- and multisensory neuroplasticity"

# Additional information about the resource, e.g., a brief abstract.
description: "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. The outcomes confirm the superior efficacy of multisensory learning in enhancing cognitive processes and improving multisensory processing. 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."
# Lit of keywords the resource should be associated with.
# Give as many keywords as possible, to make the resource findable.
keywords:
  - Neuroscience
  - Multisensory learning

# License information for this resource. Please provide the license name and/or a link to the license.
# Please add also a corresponding LICENSE file to the repository.
license:
  name: "Creative Commons CC0 1.0 Public Domain Dedication"
  url: "https://creativecommons.org/publicdomain/zero/1.0/"



## Optional Fields

# Funding information for this resource.
# Separate funder name and grant number by comma.
funding:
  - "HFRI: 2089"



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references:
  -
    id: "doi:10.xxx/zzzz"
    reftype: "IsSupplementTo"
    citation: "Citation1"


# Resource type. Default is Dataset, other possible values are Software, DataPaper, Image, Text.
resourcetype: Dataset

# Do not edit or remove the following line
templateversion: 1.2