Effects of tDCS on Brain Functional Network of Patients After Stroke

Transcranial direct current stimulation (tDCS) is an emerging brain intervention technique. However, the effects of tDCS on stroke patients are unclear. In this study, Granger Causality (GC) is used to construct brain functional networks of the tDCS group (9 cases) and the sham tDCS group (11 cases). Some parameters of brain functional networks are analyzed comparatively, such as degree, clustering coefficient, betweenness centrality, characteristic path length, and efficiency. In tDCS group, the results show that the distribution of degree changes greatly in left prefrontal lobe and left temporal lobe regions, the distribution of betweenness centrality transfers, characteristic path length decreases, clustering coefficient and efficiency increase significantly ( $p< 0.05$ ) after stimulation. However, there is no significant difference in sham tDCS group. In this study, the positive effects of tDCS on the therapeutic of stroke are clarified and the evidence for the effects of tDCS on stroke is provided.

[1]  D. Corbett,et al.  Aerobic Training and Mobilization Early Post-stroke: Cautions and Considerations , 2019, Front. Neurol..

[2]  C. Rorden,et al.  Transcranial Direct Current Stimulation vs Sham Stimulation to Treat Aphasia After Stroke: A Randomized Clinical Trial , 2018, JAMA neurology.

[3]  Mohammad Reza Khosravi,et al.  Brain-Controlled Adaptive Lower Limb Exoskeleton for Rehabilitation of Post-Stroke Paralyzed , 2019, IEEE Access.

[4]  O. Sporns,et al.  Mapping the Structural Core of Human Cerebral Cortex , 2008, PLoS biology.

[5]  Mykola Pechenizkiy,et al.  Effect of linear mixing in EEG on synchronization and complex network measures studied using the Kuramoto model , 2019, Physica A: Statistical Mechanics and its Applications.

[6]  Fatai Sado,et al.  Assist-as-Needed Robotic Rehabilitation Strategy Based on z-Spline Estimated Functional Ability , 2020, IEEE Access.

[7]  Qiang Fang,et al.  A Longitudinal Investigation of the Efficacy of Supported In-Home Post-Stroke Rehabilitation , 2020, IEEE Access.

[8]  V Latora,et al.  Efficient behavior of small-world networks. , 2001, Physical review letters.

[9]  Leonardo Mostarda,et al.  Artificial Muscle Intelligence System With Deep Learning for Post-Stroke Assistance and Rehabilitation , 2019, IEEE Access.

[10]  Rongrong Fu,et al.  EEG intentions recognition in dynamic complex object control task by functional brain networks and regularized discriminant analysis , 2020, Biomed. Signal Process. Control..

[11]  Nick S. Ward,et al.  Restoring brain function after stroke — bridging the gap between animals and humans , 2017, Nature Reviews Neurology.

[12]  Mark E. J. Newman,et al.  Ego-centered networks and the ripple effect , 2001, Soc. Networks.

[13]  S. Scott,et al.  Retrieving meaning after temporal lobe infarction: The role of the basal language area , 2004, Annals of neurology.

[14]  Andrea Landherr,et al.  A Critical Review of Centrality Measures in Social Networks , 2010, Bus. Inf. Syst. Eng..

[15]  Angelo Gemignani,et al.  Motor stroke recovery after tDCS: a systematic review , 2019, Reviews in the neurosciences.

[16]  P. Stanzione,et al.  Transcranial direct current stimulation of the affected hemisphere does not accelerate recovery of acute stroke patients , 2013, European journal of neurology.

[17]  R. Huganir,et al.  Local potentiation of excitatory synapses by serotonin and its alteration in rodent models of depression , 2013, Nature Neuroscience.

[18]  Sung Chan Jun,et al.  Geometrical Variation’s Influence on the Effects of Stimulation May be Important in the Conventional and Multi-Array tDCS–Comparison of Electrical Fields Computed , 2019, IEEE Access.

[19]  C. Granger.  Investigating causal relations by econometric models and cross-spectral methods , 1969 .

[20]  Xue Wang,et al.  Estimating Granger causality after stimulus onset: A cautionary note , 2008, NeuroImage.

[21]  Koichi Sameshima,et al.  Using partial directed coherence to describe neuronal ensemble interactions , 1999, Journal of Neuroscience Methods.

[22]  Mingzhou Ding,et al.  Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance , 2001, Biological Cybernetics.

[23]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[24]  Marcus Kaiser,et al.  Nonoptimal Component Placement, but Short Processing Paths, due to Long-Distance Projections in Neural Systems , 2006, PLoS Comput. Biol..

[25]  H. Johansen-Berg,et al.  The Role of GABA in Human Motor Learning , 2011, Current Biology.

[26]  Dingguo Zhang,et al.  Using tDCS as an Add-On Treatment Prior to FES Therapy in Improving Upper Limb Function in Severe Chronic Stroke Patients: A Randomized Controlled Study , 2018, Front. Hum. Neurosci..

[27]  Harry O. Posten,et al.  The robustness of the two—sample t—test over the Pearson system , 1978 .

[28]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[29]  V. Feigin,et al.  Global Burden of Stroke. , 2017, Circulation research.

[30]  David Phillips,et al.  Graph theoretic analysis of structural connectivity across the spectrum of Alzheimer's disease: The importance of graph creation methods , 2015, NeuroImage: Clinical.

[31]  P. Langhorne,et al.  Repetitive Task Training for Improving Functional Ability After Stroke , 2009, The Cochrane database of systematic reviews.

[32]  Roel M. Willems,et al.  Differential roles for left inferior frontal and superior temporal cortex in multimodal integration of action and language , 2009, NeuroImage.

[33]  L. Merabet,et al.  Clinical research with transcranial direct current stimulation (tDCS): Challenges and future directions , 2012, Brain Stimulation.

[34]  K. Kendrick,et al.  Partial Granger causality—Eliminating exogenous inputs and latent variables , 2008, Journal of Neuroscience Methods.

[35]  A. Seth,et al.  Granger Causality Analysis in Neuroscience and Neuroimaging , 2015, The Journal of Neuroscience.

[36]  A. Vovk,et al.  Increased cognitive load during simple and complex motor tasks in acute stage after stroke. , 2007, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[37]  Hojjat Adeli,et al.  Complexity of weighted graph: A new technique to investigate structural complexity of brain activities with applications to aging and autism , 2017, Neuroscience Letters.

[38]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[39]  Jonathan D. Power,et al.  Functional Brain Networks Develop from a “Local to Distributed” Organization , 2009, PLoS Comput. Biol..

[40]  Osvaldo A. Rosso,et al.  Characterization of Visuomotor/Imaginary Movements in EEG: An Information Theory and Complex Network Approach , 2019, Front. Phys..

[41]  Hao Li,et al.  China’s response to the rising stroke burden , 2019, BMJ.

[42]  Francesca N. Delling,et al.  Heart Disease and Stroke Statistics—2020 Update: A Report From the American Heart Association , 2020, Circulation.

[43]  S. Bressler,et al.  Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[44]  Febo Cincotti,et al.  Multiscale topological properties of functional brain networks during motor imagery after stroke , 2013, NeuroImage.

[45]  Vimonwan Hiengkaew,et al.  Effect of single-session dual-tDCS before physical therapy on lower-limb performance in sub-acute stroke patients: A randomized sham-controlled crossover study. , 2018, Annals of physical and rehabilitation medicine.

[46]  Aiguo Song,et al.  Development of a Novel Home Based Multi-Scene Upper Limb Rehabilitation Training and Evaluation System for Post-Stroke Patients , 2019, IEEE Access.

[47]  O. Witte,et al.  Reduced tonic inhibition after stroke promotes motor performance and epileptic seizures , 2016, Scientific Reports.

[48]  Vahab Youssofzadeh,et al.  Temporal Information of Directed Causal Connectivity in Multi-Trial ERP Data using Partial Granger Causality , 2015, Neuroinformatics.

[49]  Jungwon Yoon,et al.  Development of a Robotic Companion to Provide Haptic Force Interaction for Overground Gait Rehabilitation , 2020, IEEE Access.

[50]  Jonathan D. Power,et al.  The Development of Human Functional Brain Networks , 2010, Neuron.

[51]  F. dos Santos,et al.  Effects of Transcranial Direct Current Stimulation (tDCS) and Exercises Treadmill on Autonomic Modulation of Hemiparetic Patients Due To Stroke—Clinic Test, Controlled, Randomized, Double-Blind , 2020, Frontiers in Neurology.

[52]  Danielle Smith Bassett,et al.  Small-World Brain Networks , 2006, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[53]  Bin He,et al.  High-Definition Transcranial Direct Current Stimulation Induces Both Acute and Persistent Changes in Broadband Cortical Synchronization: A Simultaneous tDCS–EEG Study , 2014, IEEE Transactions on Biomedical Engineering.

[54]  F. Cincotti,et al.  Evaluation of the Brain Network Organization From EEG Signals: A Preliminary Evidence in Stroke Patient , 2009, Anatomical record.

[55]  Guizhi Xu,et al.  Time-varying dynamic Bayesian network model and its application to brain connectivity using electrocorticograph , 2016 .

[56]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[57]  Gillian Hill,et al.  An Architecture for Complex Systems , 1997, EUROCAST.

[58]  J. Martinerie,et al.  The brainweb: Phase synchronization and large-scale integration , 2001, Nature Reviews Neuroscience.

[59]  C. Granger.  Testing for causality: a personal viewpoint , 1980 .

[60]  W. Marsden.  I and J , 2012 .