Poster No:
2084
Submission Type:
Abstract Submission
Authors:
Alexander Cook1, Huzaifa Ahmed1, Ahad Zafar1, Deborah Giaschi1, Hee Yeon Im1
Institutions:
1The University of British Columbia, Vancouver, British Columbia
First Author:
Co-Author(s):
Huzaifa Ahmed
The University of British Columbia
Vancouver, British Columbia
Ahad Zafar
The University of British Columbia
Vancouver, British Columbia
Introduction:
Children and adults develop and acquire new movements through visuomotor adaptation, which involves constant updating of internal motor models. Previous studies in adults suggest that two processes mediate internal model updates: an early, attentive processing for rapid error reduction and a later, implicit stabilization¹. Our recent behavioral study revealed distinct visuomotor adaptation patterns in younger children (6-8 years), older children (9-11 years), and adults². Children consistently showed delayed movement compared to adults, and younger children showed slower initial learning with shallower curves compared to older children and adults. This suggests that the early processing stage relying on explicit movement strategies may not be fully mature before 9 years. Neural correlates of visuomotor adaptation development have not been fully understood. To fill this knowledge gap, we employed MEG to measure brain activity in children (6-11 years) and adults (22-40 years) during a child-friendly visuomotor adaptation task.
Methods:
The task involved using a computer mouse to move a cartoon fish from a central starting point on a projection screen to a target that appeared randomly on the left or right side with equal frequency across a run. During baseline and de-adaptation, the fish moved in the same direction as the mouse. During adaptation and re-adaptation, visual feedback of the fish location was rotated 45° relative to the mouse direction, requiring corrective movements. There were 10 baseline, 60 adaptation, 30 de-adaptation, and 30 re-adaptation trials. MEG was recorded (306-channel MEGIN TRIUX) at a sampling rate of 1000 Hz. EOG, ECG, and five head position indicator coils were attached for monitoring eye movement, heartbeat, and continuous head movement. MEG data were preprocessed using spatiotemporal and extended signal-space separations, band-pass filtering (0.5–45 Hz), head movement compensation, and ICA-based artifact removal. Trial data were time-locked to target onset, and epochs were taken from 300 ms before to 1000 ms after onset. Digitized head position points were coregistered to the reconstructed scalp surface from each participant's T1W structural MRI. MEG was source-localized to the reconstructed cortical surface using dSPM. Individual source activations mapped to the inflated cortical surface were extracted from parcellated cortical labels³ for visual, parietal, and frontal regions and compared between children and adults for latency and magnitude of the peak activity.
Results:
In adults and children, peak MEG activity emerged faster during re-adaptation than initial adaptation, indicating an overall learning effect. Peak activity in motor and superior/inferior frontal areas, contralateral to the moving hand, was greater and emerged faster in adults than children, consistent with the behavioral pattern of faster movement onset in adults. Children showed greater and earlier peaks in visual areas than adults. Only adults showed pre-movement activity in motor regions at about 80 ms before target onset. Adults also demonstrated high correlations between movement onset and frontal peak MEG latency, implying a strong relationship between behavioral performance and neural processing speed.
Conclusions:
Source-localized MEG allowed the exploration of neural correlates of visuomotor adaptation development. Faster and greater involvement in frontal regions, including the motor cortex, before and after the target onset may reflect increased motor preparation and attentive processing for internal model updating in adults. The enhanced processing in visual regions may be related to a reliance on the implicit component in children. Our results suggest that involvement of the frontal regions in visuomotor adaptation is not fully mature in children at this age, consistent with our behavioral findings. This study provides insight into how neural development underlies behavioral differences in visuomotor adaptation between children and adults.
Lifespan Development:
Normal Brain Development: Fetus to Adolescence
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis 2
Motor Behavior:
Motor Planning and Execution
Visuo-Motor Functions 1
Perception, Attention and Motor Behavior:
Perception: Visual
Keywords:
Development
MEG
Motor
Vision
Other - Visuo-Motor Adaptation
1|2Indicates the priority used for review
Provide references using author date format
1. Taylor, J. A., Krakauer, J. W., & Ivry, R. B. (2014), 'Explicit and implicit contributions to learning in a sensorimotor adaptation task', The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, vol. 34, no. 8, pp. 3023–3032
2. Cook, A., Aziz, M., Zafar, A., Giaschi, D., & Im, H. Y. (2023), 'Developmental characteristics of visuomotor adaptation strategies in childhood', Journal of Vision, vol. 23, no. 9, pp. 5966
3. Destrieux, C., Fischl, B., Dale, A., & Halgren, E. (2010), 'Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature', NeuroImage, vol. 53, no. 1, pp. 1–15