Comparative analysis of motor skill acquisition in a novel bimanual task: the role of mental representation and sensorimotor feedback.

SDA-M bimanual motor learning biomechanics cognitive primitives maze skill acquisition tactile pressure

Journal

Frontiers in human neuroscience
ISSN: 1662-5161
Titre abrégé: Front Hum Neurosci
Pays: Switzerland
ID NLM: 101477954

Informations de publication

Date de publication:
2024
Historique:
received: 29 04 2024
accepted: 21 08 2024
medline: 26 9 2024
pubmed: 26 9 2024
entrez: 26 9 2024
Statut: epublish

Résumé

This study investigates the multifaceted nature of motor learning in a complex bimanual task by examining the interplay between mental representation structures, biomechanics, tactile pressure, and performance. We developed a novel maze game requiring participants to maneuver a rolling sphere through a maze, exemplifying complex sequential coordination of vision and haptic control using both hands. A key component of this study is the introduction of cognitive primitives, fundamental units of cognitive and motor actions that represent specific movement patterns and strategies. Participants were divided into two groups based on initial performance: poor performers (PPG) and good performers (GPG). The experimental setup employed motion capture and innovative tactile sensors to capture a detailed multimodal picture of the interaction process. Our primary aims were to (1) assess the effects of daily practice on task performance, biomechanics, and tactile pressure, (2) examine the relationship between changes in mental representation structures and skill performance, and (3) explore the interplay between biomechanics, tactile pressure, and cognitive representation in motor learning. Performance analysis showed that motor skills improved with practice, with the GPG outperforming the PPG in maze navigation efficiency. Biomechanical analysis revealed that the GPG demonstrated superior movement strategies, as indicated by higher peak velocities and fewer velocity peaks during task execution. Tactile feedback analysis showed that GPG participants applied more precise and focused pressure with their right-hand thumb, suggesting enhanced motor control. Cognitively, both groups refined their mental representation structures over time, but the GPG exhibited a more structured and sophisticated cognitive mapping of the task post-practice. The findings highlight the intertwined nature of biomechanical control, tactile feedback, and cognitive processing in motor skill acquisition. The results support established theories, such as the cognitive action architecture approach, emphasizing the role of mental representation in planning and executing motor actions. The integration of cognitive primitives in our analysis provides a theoretical framework that connects observable behaviors to underlying cognitive strategies, enhancing the understanding of motor learning across various contexts. Our study underscores the necessity of a holistic approach to motor learning research, recognizing the complex interaction between cognitive and motor processes in skill acquisition.

Identifiants

pubmed: 39323958
doi: 10.3389/fnhum.2024.1425090
pmc: PMC11422229
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1425090

Informations de copyright

Copyright © 2024 Cienfuegos, Naceri, Maycock, Kõiva, Ritter and Schack.

Déclaration de conflit d'intérêts

JM was employed at Margin UG. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Miguel Cienfuegos (M)

Neurocognition and Action-Biomechanics Group, Bielefeld University, Bielefeld, Germany.
Center for Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.

Abdeldjallil Naceri (A)

Munich School of Robotics and Machine Intelligence (MSRM), Technical University of Munich (TUM), Munich, Germany.

Jonathan Maycock (J)

Margin UG, Bielefeld, Germany.

Risto Kõiva (R)

Center for Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.

Helge Ritter (H)

Center for Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.
Neuroinformatics Group, Bielefeld University, Bielefeld, Germany.

Thomas Schack (T)

Neurocognition and Action-Biomechanics Group, Bielefeld University, Bielefeld, Germany.
Center for Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.

Classifications MeSH