Impaired neuronal synchrony after focal ischemic stroke in elderly patients

OBJECTIVE This study investigated whether cortical synchrony derived from electroencephalography (EEG) in elderly patients is impaired and if the impairment might reflect long-term functional recovery after stroke. METHODS The scalp EEG signals of stroke patients (N=42) were collected within seven days after the onset of stroke and analyzed with phase synchronization (PS). Neurodeficit outcome was scored twice according to the National Institute of Health Stroke Scale (NIHSS): (1) at the same day of EEG recording and (2) two months after stroke. The correlation between cortical synchrony and NIHSS was analyzed. RESULTS The level of synchronization between lesion and intact areas in the ipsilateral hemisphere was reduced significantly after stroke, while the synchronization among intact areas increased to 114% among the control subjects. Furthermore, the patients with lower inter-hemispheric synchrony after stroke were observed to have a higher NIHSS two months after stroke. CONCLUSIONS Results indicated that the infarct broke down the cortical synchrony networks and affected large-scale neural communication. Inter-hemispheric synchrony was relevant to long-term functional recovery after stroke. SIGNIFICANCE The prognostic value of PS for functional recovery after stroke might be helpful in understanding the alteration of cortical networks after ischemic injury.

[1]  Hiroshi Otsubo,et al.  Fluctuations in cortical synchronization in pediatric traumatic brain injury. , 2008, Journal of neurotrauma.

[2]  H. Bergman,et al.  Pathological synchronization in Parkinson's disease: networks, models and treatments , 2007, Trends in Neurosciences.

[3]  Karl J. Friston,et al.  Evaluation of different measures of functional connectivity using a neural mass model , 2004, NeuroImage.

[4]  A. Fingelkurts,et al.  Functional connectivity in the brain—is it an elusive concept? , 2005, Neuroscience & Biobehavioral Reviews.

[5]  P. Nunez,et al.  High-resolution EEG using spline generated surface Laplacians on spherical and ellipsoidal surfaces , 1993, IEEE Transactions on Biomedical Engineering.

[6]  R. Quiroga,et al.  Learning driver-response relationships from synchronization patterns. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[7]  Michel J. A. M. van Putten,et al.  The revised brain symmetry index , 2007, Clinical Neurophysiology.

[8]  W. Klimesch,et al.  What does phase information of oscillatory brain activity tell us about cognitive processes? , 2008, Neuroscience & Biobehavioral Reviews.

[9]  E. Aubert,et al.  Predicting Outcome in Acute Stroke: A Comparison between QEEG and the Canadian Neurological Scale , 2003, Clinical EEG.

[10]  T. Demiralp,et al.  Human EEG gamma oscillations in neuropsychiatric disorders , 2005, Clinical Neurophysiology.

[11]  Jürgen Kurths,et al.  Synchronization - A Universal Concept in Nonlinear Sciences , 2001, Cambridge Nonlinear Science Series.

[12]  Paolo Maria Rossini,et al.  Neuronal functionality assessed by magnetoencephalography is related to oxidative stress system in acute ischemic stroke , 2009, NeuroImage.

[13]  Thomas Wichmann,et al.  Pathophysiology of Parkinsonism , 2008, Clinical Neurophysiology.

[14]  Shanbao Tong,et al.  Advances in quantitative electroencephalogram analysis methods. , 2004, Annual review of biomedical engineering.

[15]  Rodrigo Quian Quiroga,et al.  Nonlinear multivariate analysis of neurophysiological signals , 2005, Progress in Neurobiology.

[16]  Robert W. Thatcher,et al.  NORMATIVE EEG DATABASES AND EEG BIOFEEDBACK , 1998 .

[17]  P. McClintock Synchronization:a universal concept in nonlinear science , 2003 .

[18]  M Tombini,et al.  Long‐term effects of stroke on neuronal rest activity in rolandic cortical areas , 2006, Journal of neuroscience research.

[19]  A Kraskov,et al.  Synchronization and Interdependence Measures and their Applications to the Electroencephalogram of Epilepsy Patients and Clustering of Data (PhD Thesis) , 2004 .

[20]  Junfeng Sun,et al.  Unified framework for detecting phase synchronization in coupled time series. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  G Pfurtscheller,et al.  Event-related coherence as a tool for studying dynamic interaction of brain regions. , 1996, Electroencephalography and clinical neurophysiology.

[22]  Wolf Singer,et al.  Neuronal Synchrony: A Versatile Code for the Definition of Relations? , 1999, Neuron.

[23]  A. Urbano,et al.  Performances of surface Laplacian estimators: A study of simulated and real scalp potential distributions , 2005, Brain Topography.

[24]  Jurriaan M. Peters,et al.  A brain symmetry index (BSI) for online EEG monitoring in carotid endarterectomy , 2004, Clinical Neurophysiology.

[25]  E Aubert,et al.  QEEG Prognostic Value in Acute Stroke , 2007, Clinical EEG and neuroscience.

[26]  Paolo Maria Rossini,et al.  Outcome prediction in acute monohemispheric stroke via magnetoencephalography , 2007, Journal of Neurology.

[27]  Cees van Leeuwen,et al.  Spatial and temporal structure of phase synchronization of spontaneous alpha EEG activity , 2004, Biological Cybernetics.

[28]  Daniele Marinazzo,et al.  Steady-state visual evoked potentials and phase synchronization in migraine patients. , 2004, Physical review letters.

[29]  Stephen E. Rose,et al.  Quantitative EEG indices of sub-acute ischaemic stroke correlate with clinical outcomes , 2007, Clinical Neurophysiology.

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

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

[32]  D. Tucker,et al.  EEG coherency. I: Statistics, reference electrode, volume conduction, Laplacians, cortical imaging, and interpretation at multiple scales. , 1997, Electroencephalography and clinical neurophysiology.

[33]  V. M. Shklovskii,et al.  The effects of lesions to subcortical conducting pathways on the electrical activity of the human cerebral cortex , 1999, Neuroscience and Behavioral Physiology.

[34]  David L McArthur,et al.  Cortical synchrony changes detected by scalp electrode electroencephalograph as traumatic brain injury patients emerge from coma. , 2007, Surgical neurology.

[35]  S. Barbay,et al.  Reorganization of remote cortical regions after ischemic brain injury: a potential substrate for stroke recovery. , 2003, Journal of neurophysiology.

[36]  P. Inchingolo,et al.  EEG source localization sensitivity due to brain lesions modeling errors , 2001, 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[37]  Biyu J. He,et al.  Breakdown of Functional Connectivity in Frontoparietal Networks Underlies Behavioral Deficits in Spatial Neglect , 2007, Neuron.

[38]  R Quian Quiroga,et al.  Performance of different synchronization measures in real data: a case study on electroencephalographic signals. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[39]  C. Elger,et al.  CAN EPILEPTIC SEIZURES BE PREDICTED? EVIDENCE FROM NONLINEAR TIME SERIES ANALYSIS OF BRAIN ELECTRICAL ACTIVITY , 1998 .

[40]  Milan Palus,et al.  EEG phase synchronization in patients with paranoid schizophrenia , 2008, Neuroscience Letters.

[41]  P. Nunez,et al.  A theoretical and experimental study of high resolution EEG based on surface Laplacians and cortical imaging. , 1994, Electroencephalography and clinical neurophysiology.

[42]  R. Barry,et al.  EEG differences between eyes-closed and eyes-open resting conditions , 2007, Clinical Neurophysiology.