The Effects of rTMS Combined with Motor Training on Brain Network in Resting Status
Jin Jingna1, Wang Xin1, Lin Yu2, Zhang Kai3, Li Ying1, Xiang Fang1, Liu Zhipeng1 , Yang Xuejun2, Yin Tao1,4#*
1 Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300192, China 2 Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300052, China 3 Department of Surgery, the First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China 4 Neuroscience Center, Chinese Academy of Medical Sciences, Beijing 100730, China
Abstract It was reported that repetitive transcranial magnetic stimulation (rTMS) combined with motor training could improve the motor skill, which could be used in motor rehabilitation after stroke. In this study, the effects of rTMS combined with motor training on brain neural activities were investigated based on the method of brain network. Ten healthy volunteers were recruited. The 1 Hz rTMS over the dominant hemisphere combined with unfamiliar motor training with non-dominant hand subsequently was performed rTMS combined with motor training lasted 14 days to improve the motor function of non-dominant hand. Electroencephalography (EEG) in resting state with eyes closed was recorded before and after rTMS combined with motor training. The functional connectivity was analyzed using the method of phase lag index (PLI). We constructed weighted network and calculated the network topology characteristics based on PLI, subsequently. Finally, the signed-rank test was used for statistical analysis. We found that the changes of functional connectivity could be detected mainly between functional regions rather than inside regions. The functional connectivity at lower frequency band (theta and alpha) was significantly increased, and was opposite at higher frequency band (beta, gamma1 and gamma2). Furthermore, we found that the rTMS combined with motor training had a significant influence on the functional connectivity between central region in non-dominant hemisphere and dominant frontal regions (before: 0.141 4±0.102 5;after:0.217 2±0.134 7; P<0.05) and non-dominant frontal regions(before:0.141 0±0.109 9;after:0.205 9±0.136 1; P <0.05) at alpha frequency. Node efficiency increased at low band and decreased at high band, and node path length was opposite. Specifically, the node efficiency at gamma2 bandchanged significantly, mainly in central regions of both hemisphere (left, before: 0.060 0±0.000 3; after: 0.042 9±0.001 3; P <0.05; right, before: 0.060 7±0.002 3; after: 0.041 9±0.002 4; P <0.05), and also the node path length (left, before:18.539 0±0.457 1;after:28.585 8±1.001 4;P <0.05; right, before: 18.650 8±0.438 6; after: 28.853 0±1.652 6;P <0.05). This study was helpful to understand the brain mechanism of rTMS combined with motor training on improvement of motor skill, and comprehend the impact of stroke and brain lesions on brain activities.
Jin Jingna,Wang Xin,Lin Yu, et al. The Effects of rTMS Combined with Motor Training on Brain Network in Resting Status[J]. Chinese Journal of Biomedical Engineering, 2018, 37(3): 290-296.
[1] Willingham DB. A neuropsychological theory of motor skill learning [J]. Psychol Rev, 1998, 105(3):558-584. [2] Ma Liangsuo, Narayana S, Robin DA, et al. Changes occur in resting state network of motor system during 4 weeks of motor skill learning [J]. Neuroimage, 2011, 58(1):226-233. [3] Sun FT, Miller LM, Rao AA, et al. Functional connectivity of cortical networks involved in bimanual motor sequence learning [J]. Cereb Cortex, 2007, 17(5):1227-1234. [4] Ungerleider LG, Doyon J, Karni A. Imaging brain plasticity during motor skill learning [J]. Neurobiol Learn Mem, 2002, 78(3):553-564. [5] Avenanti A, Coccia M, Ladavas E,et al. Low-frequency rTMS promotes use-dependent motor plasticity in chronic stroke: A randomized trial [J]. Neurology, 2012, 78(4):256-264. [6] Bolognini N, Pascual-Leone A, Fregni F. Using non-invasive brain stimulation to augment motor training-induced plasticity [J]. J Neuroeng Rehabil, 2009, 6:8. [7] Emara TH, Moustafa RR, Elnahas NM, et al. Repetitive transcranial magnetic stimulation at 1Hz and 5Hz produces sustained improvement in motor function and disability after ischaemic stroke [J]. Eur J Neurol, 2010, 17(9):1203-1209. [8] Lüdemann-Podubecká J, Bsl K, Theilig S, et al. The effectiveness of 1hz rtms over the primary motor area of the unaffected hemisphere to improve hand function after stroke depends on hemispheric dominance [J]. Brain Stimul, 2015, 8(4):823-830. [9] Takekawa T, Kakuda W, Uchiyama M, et al. Brain perfusion and upper limb motor function: a pilot study on the correlation between evolution of asymmetry in cerebral blood flow and improvement in Fugl-Meyer assessment score after rTMS in chronic post-stroke patients [J]. J Neuroradiol, 2014, 41(3):177-183. [10] Kondo T, Kakuda W, Yamada N, et al. Effects of repetitive transcranial magnetic stimulation and intensive occupational therapy on motor neuron excitability in poststroke hemiparetic patients: A neurophysiological investigation using F-wave parameters [J]. Int J Neurosci, 2015, 125(1):25-31. [11] 梁夏, 王金辉, 贺永. 人脑连接组研究:脑结构网络和脑功能网络[J]. 科学通报, 2010, 55(16):1565-1583. [12] 蒋田仔, 刘勇, 李永辉. 脑网络:从脑结构到脑功能 [J]. 生命科学, 2009, 21(2):181-188. [13] Sporns O, Chialvo DR, Kaiser M, et al. Organization, development and function of complex brain networks [J]. Trends Cogn Sci, 2004, 8(9):418-425. [14] Jing H, Takigawa M. Observation of EEG coherence after repetitive transcranial magnetic stimulation [J]. Clin Neurophysiol, 2000, 111(9):1620-1631. [15] Plewnia C, Rilk AJ, Soekadar SR, et al. Enhancement of long-range EEG coherence by synchronous bifocal transcranial magnetic stimulation [J]. Eur J Neurosci, 2008, 27(6):1577-1583. [16] De Vico Fallani F, Clausi S, Leggio M, et al. Interhemispheric connectivity characterizes cortical reorganization in motor-related networks after cerebellar lesions [J]. Cerebellum, 2017, 16(2):358-375. [17] Youssofzadeh V, Zanotto D, Wong-Lin K, et al. Directed functional connectivity in fronto-centroparietal circuit correlates with motor adaptation in gait training [J]. IEEE Trans Neural Syst Rehabil Eng, 2016, 24(11):1265-1275. [18] Grefkes C, Fink GR. Reorganization of cerebral networks after stroke: new insights from neuroimaging with connectivity approaches [J]. Brain, 2011, 134(5):1264-1276. [19] Grefkes C, Nowak DA, Wang LE, et al. Modulating cortical connectivity in stroke patients by rTMS assessed with fMRI and dynamic causal modeling [J]. Neuroimage, 2010, 50(1):233-242. [20] David O, Cosmelli D, Friston KJ. Evaluation of different measures of functional connectivity using a neural mass model [J]. Neuroimage, 2004, 21(2):659-673. [21] Pereda E, Quiroga RQ, Bhattacharya J. Nonlinear multivariate analysis of neurophysiological signals [J]. Prog Neurobiol, 2005, 77(1-2):1-37. [22] Stam CJ, Nolte G, Daffertshofer A. Phase lag index: assessment of functional connectivity from multichannel EEG and MEG with diminished bias from common sources [J]. Hum Brain Mapp, 2007, 28(11):1178-1193. [23] Latora V, Marchiori M. Efficient behavior of small-world networks [J]. Phys Rev Lett, 2001, 87(19):198701. [24] Bear MF, Connors BW, Paradiso MA.神经科学——探索脑:中文版[M].王建军,译.2版.北京:高等教育出版社, 2004: 179. [25] Babiloni C, Marzano N, Iacoboni M, et al. Resting state cortical rhythms in athletes: a high-resolution EEG study [J]. Brain Res Bull, 2010, 81(1):149-156. [26] Sommerville JA, Decety J. Weaving the fabric of social interaction: articulating developmental psychology and cognitive neuroscience in the domain of motor cognition [J]. Psychon Bull Rev, 2006, 13(2):179-200.
