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Association between Motor Planning and the Frontoparietal Network in Children: An Exploratory Multimodal Study

Published online by Cambridge University Press:  22 October 2021

Ranila Bhoyroo*
Affiliation:
Institute for Health Research, School of Health Sciences, University of Notre Dame Australia, Perth, WA, Australia School of Psychology and Exercise Science, Murdoch University, Perth, WA, Australia Faculty of Health Sciences, Curtin School of Population Health, Curtin University, Perth, WA, Australia
Beth Hands
Affiliation:
Institute for Health Research, School of Health Sciences, University of Notre Dame Australia, Perth, WA, Australia
Karen Caeyenberghs
Affiliation:
Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
Alberto de Luca
Affiliation:
Image Sciences Institute, University Medical Utrecht, Utrecht, The Netherlands
Alexander Leemans
Affiliation:
Image Sciences Institute, University Medical Utrecht, Utrecht, The Netherlands
Adam Wigley
Affiliation:
Institute for Health Research, School of Health Sciences, University of Notre Dame Australia, Perth, WA, Australia
Christian Hyde
Affiliation:
Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC, Australia
*
*Correspondence and reprint requests to: Dr Ranila Bhoyroo, Institute for Health Research, The University of Notre Dame Australia, 19 Mouat Street (PO Box 1225), Fremantle, WA, 6959, Australia. E-mail: [email protected]

Abstract

Objective:

Evidence from adult literature shows the involvement of cortical grey matter areas of the frontoparietal lobe and the white matter bundle, the superior longitudinal fasciculus (SLF) in motor planning. This is yet to be confirmed in children.

Method:

A multimodal study was designed to probe the neurostructural basis of childhood motor planning. Behavioural (motor planning), magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) data were acquired from 19 boys aged 8–11 years. Motor planning was assessed using the one and two colour sequences of the octagon task. The MRI data were preprocessed and analysed using FreeSurfer 6.0. Cortical thickness and cortical surface area were extracted from the caudal middle frontal gyrus (MFG), superior frontal gyrus (SFG), precentral gyrus (PcG), supramarginal gyrus (SMG), superior parietal lobe (SPL) and the inferior parietal lobe (IPL) using the Desikan–Killiany atlas. The DWI data were preprocessed and analysed using ExploreDTI 4.8.6 and the white matter tract, the SLF was reconstructed.

Results:

Motor planning of the two colour sequence was associated with cortical thickness of the bilateral MFG and left SFG, PcG, IPL and SPL. The right SLF was related to motor planning for the two colour sequence as well as with the left cortical thickness of the SFG.

Conclusion:

Altogether, morphology within frontodorsal circuity, and the white matter bundles that support communication between them, may be associated with individual differences in childhood motor planning.

Type
Research Article
Copyright
Copyright © INS. Published by Cambridge University Press, 2021

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