Laterality 2020: Response to the article commentaries.

Hemispheric asymmetries genetics laterality lateralization neuroimaging

Journal

Laterality
ISSN: 1464-0678
Titre abrégé: Laterality
Pays: England
ID NLM: 9609064

Informations de publication

Date de publication:
May 2021
Historique:
pubmed: 29 5 2021
medline: 16 6 2021
entrez: 28 5 2021
Statut: ppublish

Résumé

In our recent opinion paper "Laterality 2020: entering the next decade", we highlighted trends that we thought are likely to shape laterality research in the 2020s. Our opinion paper inspired 11 commentaries by experts from several disciplines which discussed a wide range of topics complementing the 10 trends we identified in the opinion paper. In this reply, we summarize and discuss the 11 commentaries by clustering them into 3 different main topics. The topic that was covered by the largest number of commentaries was the role of comparative and evolutionary approaches in laterality research. Moreover, several comments focused on the ontogenesis of hemispheric asymmetries and the importance of reliability and validity in laterality research. Embracing the technical advances, research trends and controversies laid out in the commentaries will significantly improve our understanding of several of the core questions of laterality research.

Identifiants

pubmed: 34047243
doi: 10.1080/1357650X.2021.1932983
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

348-357

Auteurs

Sebastian Ocklenburg (S)

Institute of Cognitive Neuroscience, Biopsychology, Faculty of Psychology, Ruhr-University Bochum, Bochum, Germany.

Gesa Berretz (G)

Institute of Cognitive Neuroscience, Biopsychology, Faculty of Psychology, Ruhr-University Bochum, Bochum, Germany.

Julian Packheiser (J)

Institute of Cognitive Neuroscience, Biopsychology, Faculty of Psychology, Ruhr-University Bochum, Bochum, Germany.

Patrick Friedrich (P)

Brain and Behaviour (INM-7), Institute of Neuroscience and Medicine, Forschungszentrum Jülich, Jülich, Germany.

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Classifications MeSH