Long-term Chinese calligraphic handwriting training has a positive effect on brain network efficiency

RESEARCH ARTICLE Long-term Chinese calligraphic handwriting training has a positive effect on brain network efficiency Wen Chen ID1,2,3,4, Yong He2,3, Chuansheng Chen5, Ming Zhu2,3, Suyu Bi6,7, Jin Liu2,3, Mingrui Xia2,3, Qixiang Lin2,3, Yiwen Wang7*, Wenjing Wang2,3* a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 1 Advanced Innovation Center for Future Education, Beijing Normal University, Beijing, China, 2 State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China, 3 IDG/ McGovern Institute for Brain Research, Beijing Normal University, Beijing, China, 4 College of Information Science and Technology, Beijing Normal University, Beijing, China, 5 Department of Psychological Science, University of California Irvine, Irvine, California, United States of America, 6 School of International Journalism and Communication, Beijing Foreign Studies University, Beijing, China, 7 School of Arts and Media, Beijing Normal University, Beijing, China * (WW); (YW) Abstract OPEN ACCESS Citation: Chen W, He Y, Chen C, Zhu M, Bi S, Liu J, et al. (2019) Long-term Chinese calligraphic handwriting training has a positive effect on brain network efficiency. PLoS ONE 14(1): e0210962. https://doi.org/10.1371/journal.pone.0210962 Editor: Lutz Jäncke, University of Zurich, SWITZERLAND Received: June 6, 2018 Accepted: January 5, 2019 Published: January 25, 2019 Copyright: © 2019 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: The correlation matrix data set of resting state brain data for network analyses is available on the Figshare repository (DOI: 10.6084/m9.figshare.7562975, URL: https://figshare.com/s/ 7f8d94d0e6b9fe819760). Funding: This study was supported by the 14YJAZH081 (received by WW) Project of the Ministry of Education of the People’s Republic of China (http://en.moe.gov.cn/) and the No.31221003 (received by YH) Project of the National Natural Science Foundation of the As a visual art form, Chinese calligraphic handwriting (CCH) has been found to correlate with certain brain activity and to induce functional connectivity reorganization of the brain. This study investigated the effect of long-term CCH training on brain functional plasticity as assessed with network measures. With the resting-state fMRI data from 31 participants with at least five years of CCH training and 40 controls, we constructed brain functional networks, examined group differences at both the whole brain and modular levels, and correlated the topological characteristics with calligraphy skills. We found that, compared to the control group, the CCH group showed shorter characteristic path lengths and higher local efficiency in certain brain areas in the frontal and parietal cortices, limbic system, basal ganglia, and thalamus. Moreover, these network measures in the cingulate cortex, caudate nucleus, and thalamus were associated with CCH performance (i.e., copying and creating skills). These results suggest that long-term CCH training has a positive effect on the topological characteristics of brain networks. 1. Introduction Chinese calligraphic handwriting (CCH) is a 3000-year-old art form. To master CCH skills requires years of intensive practice that involves sensory perception, motor skills, as well as multiple cognitive and emotional elements [1, 2]. Following previous research that found both structural and functional brain plasticity in response to many types of intensive training such as musical training [3, 4], driving [5], and juggling [6, 7], we have examined brain plasticity related to CCH training. Our previous two studies found that CCH training strengthened the RSFC of brain areas involved in updating and inhibition [8] and decreased the volume of the posterior cingulate cortex (PCC) [9]. PLOS ONE | https://doi.org/10.1371/journal.pone.0210962 January 25, 2019 1 / 15 CCH training and brain network efficiency People’s Republic of China (http://www.nsfc.gov. cn/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. In addition to the traditional univariate neuroimaging methods such as voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) used in the studies mentioned above, researchers have recently paid attention to brain connectivity networks or modular organization. Brain network analysis can mathematically describe various topological parameters of the brain’s organization in terms of graphs or networks, including the smallworldness, modularity, and regional network parameters [10, 11]. Studies have proved that functionally connected resting-state brain networks are associated with the anatomical connectivity of the brain [12, 13]. Given our previous findings of CCH training’s effects on the RSFC of certain brain areas [8], we hypothesized long-term CCH practicing would have an effect on the topological parameters of the resting-state brain network, including the frontal and parietal cortices, basal ganglia, and PCC. We explored the long-term CCH training’s effect on the topological characteristics of the whole brain and four specific modules. These modules were selected because of their relevance to visual processing (Module I), sensorimotor functions (Module II), and DMN (Module III), all of which are involved in CCH. More details of the brain areas included in each module are shown Fig 1 and S1 Table. Finally, within the CCH group, we further investigated the relationship between global and local network measures and calligraphy skills. Fig 1. Visualization of the four modules selected for network efficiency analyses. Modules I, II, and III mean the sets of brain areas involved in visual processing, sensorimotor functions, and the DMN, respectively. L: left hemisphere; R: right hemisphere. https://doi.org/10.1371/journal.pone.0210962.g001 PLOS ONE | https://doi.org/10.1371/journal.pone.0210962 January 25, 2019 2 / 15 CCH training and brain network efficiency 2. Materials and methods 2.1. Participants Participants were recruited from Beijing Normal University, Beijing, China. The CCH group included 32 students who majored in calligraphy and had at least five years of formal training in CCH and the control group included 44 students who had no more than a few months of basic CCH skill training. All subjects were right-handed native Chinese speakers. Participants’ IQ was measured with Raven’s Advanced Progressive Matrices (APM) (for details, see Chen et al., 2017) [8]. Each participant signed an informed consent form after a full explanation of the study procedure. This study was approved by the Institutional Review (...truncated)