Diversity, individualisation, and enhancement in motor learning: Current challenges and future directions from the first Theoretical and Applied Advances in Motor Learning Conference

The field of motor learning faces a critical gap between foundational theory and real-world application. This editorial synthesizes expert discussions from the First Theoretical and Applied Advances in Motor Learning Conference to address key issues impeding further progress. We are hampered by the science of averages, characterized by an over-reliance on data from homogenous, Western, Educated, Industrialised, Rich, and Democratic (WEIRD) populations and a flawed assumption of cognitive uniformity. This approach masks critical individual differences, limiting the translational potential of our science and leading to one-size-fits-all enhancement strategies. We propose a multi-tiered roadmap for the maturation of our field. The foundational priorities are structural: embracing co-creation with diverse communities, moving beyond WEIRD science, and implementing structured mentorship and active sponsorship to empower a new generation of scholars. Building on this, we advocate for technology-driven individualisation like using advanced Mobile Brain/Body Imaging techniques for the development of neurophenotypes, to fulfill the potential of Brain-Computer Interfaces. Finally, we call for a precision enhancement framework, shifting from learning boosters to a diagnostic-to-prescriptive model that targets specific, identified bottlenecks. This roadmap allows our field to build upon its foundational principles to create a more effective, accessible, and equitable motor learning science for all.

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Publication Details

Published
2025-10-29
DOI
https://doi.org/10.31234/osf.io/93hsa_v1
Primary Topic
Motor Control and Adaptation
Type
article
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article

Diversity, individualisation, and enhancement in motor learning: Current challenges and future directions from the first Theoretical and Applied Advances in Motor Learning Conference

Jordan A. Taylor, Andreea Ioana Sburlea, Pablo Maceira-Elvira, Maarten A. Immink et al.
Motor Control and Adaptation
article

Diversity, individualisation, and enhancement in motor learning: Current challenges and future directions from the first Theoretical and Applied Advances in Motor Learning Conference

Jordan A. Taylor, Andreea Ioana Sburlea, Pablo Maceira-Elvira, Maarten A. Immink, Marit F. L. Ruitenberg, Rachael D. Seidler, Stefan Panzer, Willem B. Verwey, Elger Abrahamse, Klaus Blischke, Friedhelm C. Hummel, Arnaud Boutin, David L. Wright, Russell Weili Chan, Katja Kornysheva, Rob van der Lubbe, Raoul M. Bongers
article en

Abstract

The field of motor learning faces a critical gap between foundational theory and real-world application. This editorial synthesizes expert discussions from the First Theoretical and Applied Advances in Motor Learning Conference to address key issues impeding further progress. We are hampered by the science of averages, characterized by an over-reliance on data from homogenous, Western, Educated, Industrialised, Rich, and Democratic (WEIRD) populations and a flawed assumption of cognitive uniformity. This approach masks critical individual differences, limiting the translational potential of our science and leading to one-size-fits-all enhancement strategies. We propose a multi-tiered roadmap for the maturation of our field. The foundational priorities are structural: embracing co-creation with diverse communities, moving beyond WEIRD science, and implementing structured mentorship and active sponsorship to empower a new generation of scholars. Building on this, we advocate for technology-driven individualisation like using advanced Mobile Brain/Body Imaging techniques for the development of neurophenotypes, to fulfill the potential of Brain-Computer Interfaces. Finally, we call for a precision enhancement framework, shifting from learning boosters to a diagnostic-to-prescriptive model that targets specific, identified bottlenecks. This roadmap allows our field to build upon its foundational principles to create a more effective, accessible, and equitable motor learning science for all.

Openalex Percentile: Top 69%
Motor Control and Adaptation
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