Brain Network Reconfiguration During Motor Imagery Revealed by a Large-Scale Network Analysis of Scalp EEG

Mentally imagining rather physically executing the motor behaviors is defined as motor imagery (MI). During MI, the mu rhythmical oscillation of cortical neurons is the event-related desynchronization (ERD) subserving the physiological basis of MI-based brain-computer interface. In our work, we investigated the specific brain network reconfiguration from rest idle to MI task states, and also probed the underlying relationship between the brain network reconfiguration and MI related ERD. Findings revealed that comparing to rest state, the MI showed the enhanced motor area related linkages and the deactivated activity of default mode network. In addition, the reconfigured network index was closely related to the ERDs, i.e., the higher the reconfigured network index was, the more obvious the ERDs were. These findings consistently implied that the reconfiguration from rest to task states underlaid the reallocation of related brain resources, and the efficient brain reconfiguration corresponded to a better MI performance, which provided the new insights into understanding the mechanism of MI as well as the potential biomarker to evaluate the rehabilitation quality for those patients with deficits of motor function.

[1]  G. Pfurtscheller,et al.  Functional brain imaging based on ERD/ERS , 2001, Vision Research.

[2]  Fei Wang,et al.  The Dynamic Brain Networks of Motor Imagery: Time-Varying Causality Analysis of Scalp EEG , 2019, Int. J. Neural Syst..

[3]  C. Stam,et al.  The organization of physiological brain networks , 2012, Clinical Neurophysiology.

[4]  Klaus-Robert Müller,et al.  Neurophysiological predictor of SMR-based BCI performance , 2010, NeuroImage.

[5]  Anina N. Rich,et al.  Multimodal functional imaging of motor imagery using a novel paradigm , 2013, NeuroImage.

[6]  Laura Astolfi,et al.  Time-Varying Effective Connectivity for Investigating the Neurophysiological Basis of Cognitive Processes , 2014 .

[7]  Yuanqing Li,et al.  Surfing the internet with a BCI mouse , 2012, Journal of neural engineering.

[8]  Yuanqing Li,et al.  A Hybrid Brain Computer Interface to Control the Direction and Speed of a Simulated or Real Wheelchair , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[9]  K D Singh,et al.  Transient and linearly graded deactivation of the human default-mode network by a visual detection task , 2008, NeuroImage.

[10]  C. J. Stam,et al.  Cognition is related to resting-state small-world network topology: an magnetoencephalographic study , 2011, Neuroscience.

[11]  Julieta Ramos-Loyo,et al.  Relationship between resting alpha activity and the ERPs obtained during a highly demanding selective attention task. , 2004, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[12]  Yuanqing Li,et al.  An EEG-Based BCI System for 2-D Cursor Control by Combining Mu/Beta Rhythm and P300 Potential , 2010, IEEE Transactions on Biomedical Engineering.

[13]  Rudolf Stark,et al.  Motor imagery of hand actions: Decoding the content of motor imagery from brain activity in frontal and parietal motor areas , 2015, Human brain mapping.

[14]  Yuan Zhou,et al.  Abnormal Cortical Networks in Mild Cognitive Impairment and Alzheimer's Disease , 2010, PLoS Comput. Biol..

[15]  Shanbao Tong,et al.  Motor Imagery Cognitive Network after Left Ischemic Stroke: Study of the Patients during Mental Rotation Task , 2013, PloS one.

[16]  Christa Neuper,et al.  A scanning protocol for a sensorimotor rhythm-based brain–computer interface , 2009, Biological Psychology.

[17]  Lars T. Westlye,et al.  Task modulations and clinical manifestations in the brain functional connectome in 1615 fMRI datasets , 2017, NeuroImage.

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

[19]  Karl J. Friston,et al.  Dynamic causal modelling , 2003, NeuroImage.

[20]  J. Baron,et al.  Does motor imagery share neural networks with executed movement: a multivariate fMRI analysis , 2013, Front. Hum. Neurosci..

[21]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

[22]  Tao Zhang,et al.  Structural and functional correlates of motor imagery BCI performance: Insights from the patterns of fronto-parietal attention network , 2016, NeuroImage.

[23]  Rui Zhang,et al.  Differentiating Between Psychogenic Nonepileptic Seizures and Epilepsy Based on Common Spatial Pattern of Weighted EEG Resting Networks , 2014, IEEE Transactions on Biomedical Engineering.

[24]  Yanling Yin,et al.  EEG default mode network in the human brain: Spectral regional field powers , 2008, NeuroImage.

[25]  W. Qin,et al.  Interindividual reaction time variability is related to resting-state network topology: an electroencephalogram study , 2012, Neuroscience.

[26]  Jonathan D. Power,et al.  Intrinsic and Task-Evoked Network Architectures of the Human Brain , 2014, Neuron.

[27]  F. L. D. Silva,et al.  Event-related EEG/MEG synchronization and desynchronization: basic principles , 1999, Clinical Neurophysiology.

[28]  Huafu Chen,et al.  Altered functional-structural coupling of large-scale brain networks in idiopathic generalized epilepsy. , 2011, Brain : a journal of neurology.

[29]  Rajesh P. N. Rao,et al.  Correction for Miller et al., Cortical activity during motor execution, motor imagery, and imagery-based online feedback , 2010, Proceedings of the National Academy of Sciences.

[30]  Michael W. Cole,et al.  Higher Intelligence Is Associated with Less Task-Related Brain Network Reconfiguration , 2016, The Journal of Neuroscience.

[31]  M. V. D. Heuvel,et al.  Exploring the brain network: A review on resting-state fMRI functional connectivity , 2010, European Neuropsychopharmacology.

[32]  G. Pfurtscheller,et al.  Motor imagery activates primary sensorimotor area in humans , 1997, Neuroscience Letters.

[33]  Vangelis Sakkalis,et al.  Review of advanced techniques for the estimation of brain connectivity measured with EEG/MEG , 2011, Comput. Biol. Medicine.

[34]  Fei Wang,et al.  Relationships between the resting-state network and the P3: Evidence from a scalp EEG study , 2015, Scientific Reports.

[35]  Peng Xu,et al.  Efficient resting-state EEG network facilitates motor imagery performance , 2015, Journal of neural engineering.

[36]  M. Lotze,et al.  Motor imagery , 2006, Journal of Physiology-Paris.

[37]  Lester Melie-García,et al.  Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory , 2008, NeuroImage.

[38]  Tao Zhang,et al.  The Time-Varying Networks in P300: A Task-Evoked EEG Study , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[39]  Rajesh P. N. Rao,et al.  Cortical activity during motor execution, motor imagery, and imagery-based online feedback , 2010, Proceedings of the National Academy of Sciences.

[40]  Wei Wu,et al.  Multimodal BCIs: Target Detection, Multidimensional Control, and Awareness Evaluation in Patients With Disorder of Consciousness , 2016, Proceedings of the IEEE.

[41]  J. Baron,et al.  Motor Imagery: A Backdoor to the Motor System After Stroke? , 2006, Stroke.

[42]  Yu Ping Wang,et al.  Recognizing mild cognitive impairment based on network connectivity analysis of resting EEG with zero reference , 2014, Physiological measurement.

[43]  T. Mulder Motor imagery and action observation: cognitive tools for rehabilitation , 2007, Journal of Neural Transmission.

[44]  Yuanqing Li,et al.  A Hybrid BCI System Combining P300 and SSVEP and Its Application to Wheelchair Control , 2013, IEEE Transactions on Biomedical Engineering.

[45]  P. Fransson How default is the default mode of brain function? Further evidence from intrinsic BOLD signal fluctuations , 2006, Neuropsychologia.

[46]  B T Thomas Yeo,et al.  Reconfigurable task-dependent functional coupling modes cluster around a core functional architecture , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[47]  Olaf Sporns,et al.  Connectivity and complexity: the relationship between neuroanatomy and brain dynamics , 2000, Neural Networks.

[48]  G Pfurtscheller,et al.  Visualization of significant ERD/ERS patterns in multichannel EEG and ECoG data , 2002, Clinical Neurophysiology.

[49]  R. Kahn,et al.  Efficiency of Functional Brain Networks and Intellectual Performance , 2009, The Journal of Neuroscience.

[50]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .