Poster C55, Wednesday, August 21, 2019, 10:45 am – 12:30 pm, Restaurant Hall
Development of the brain network supporting handwriting in middle childhood
Marieke Longcamp1, Palmis Sarah1, Habib Michel1, Anton Jean Luc2, Nazarian Bruno2, Sein Julien2, Velay Jean Luc1;1Laboratoire de Neurosciences Cognitives, CNRS UMR 7291, Aix-Marseille University, 2Institut de Neurosciences de la Timone, CNRS & AMU
Introduction: Handwriting is among the finest movements of our repertoire and requires years of training to be perfectly mastered. The brain network supporting handwriting has previously been defined in adults but its organization in children has never been investigated. Behaviorally, the progressive acquisition of the motor patterns is characterized by a switch in the control mode. Children proceed through an online adjustment of the trajectory. Adults switch to a fully proactive, automatized control mode. We measured the changes in the handwriting network between age 8/11 and adulthood. In adults, the network is formed of 5 key regions (left dorsal premotor cortex, superior parietal lobule, fusiform and inferior frontal gyri, and right cerebellum). We hypothesized that the automated writing of adults would rely on more focal and stronger activations in this network. We also expected that the more controlled writing of children would recruit extra visual, somatosensory and prefrontal regions. Methods: 65 right-handed native French speakers (23 adults, 42 children (8/11 years-old)) were instructed to write the alphabet, the days of the week and to draw loops in consecutive 16s blocks, while being scanned. The writing kinematics were recorded on an MRI-compatible digitizing tablet. The velocity profiles and the number of stops were analyzed. MRI data were acquired on a 3-Tesla MRI Scanner (Magnetom-Prisma, Siemens, Erlangen, Germany). We acquired a high-resolution T1 volume, a fieldmap, and BOLD images (gradient-echo EPI, 335 volumes in a single session). The images were processed with SPM12. They were corrected for head motion and for distortions, and normalized using a group template. Head motion and physiological noise were further accounted for by using the TAPAS toolbox with extra regressors of no-interest in the individual statistical models. Second-level analyses were carried out using the GLMflex toolbox with factors condition (letters vs loops / words vs loops) and group (adult vs children). We focus on the main effect of group. Results: The tablet recordings confirmed the presence of behavioral effects within the scanner, with a higher velocity and lower number of stops in adults. The handwriting network previously described in adults was also strongly activated in children. A quantification of the coordinates of the local maxima in the 5 key regions indicated that activations in children were more diffuse than in adults, except in the right cerebellum. The left fusiform activation was more anterior in children. In addition, the primary motor cortices and the right anterior lateral cerebellum were more strongly activated in adults. Finally, we found that contrary to adults, children recruited prefrontal regions (anterior cingulate cortex, inferior frontal gyrus pars orbitalis). Conclusions: This study constitutes the first investigation of the handwriting network in typical children. Our results suggest that the network supporting orthographic and motor processing is already established in middle-childhood. Its elements are less focalized in children than in adults. Our results also highlight the major role of prefrontal regions in learning this complex skill. Finally, they confirm the importance of the motor cortices and anterior cerebellum in the performance of automated handwriting.
Themes: Language Production, Development
Method: Functional Imaging