Functional and effective brain connectivity for discrimination between Alzheimer’s patients and healthy individuals: A study on resting state EEG rhythms

[1]  Osborne Rt,et al.  Variations in graduate record examination performance by age and sex. , 1954 .

[2]  R. Reitan Validity of the Trail Making Test as an Indicator of Organic Brain Damage , 1958 .

[3]  C. Granger Investigating Causal Relations by Econometric Models and Cross-Spectral Methods , 1969 .

[4]  M. Lawton,et al.  Assessment of Older People: Self-Maintaining and Instrumental Activities of Daily Living , 1969 .

[5]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[6]  R. Katzman.,et al.  Pathological verification of ischemic score in differentiation of dementias , 1980, Annals of neurology.

[7]  V. Leirer,et al.  Development and validation of a geriatric depression screening scale: a preliminary report. , 1982, Journal of psychiatric research.

[8]  C. P. Hughes,et al.  A New Clinical Scale for the Staging of Dementia , 1982, British Journal of Psychiatry.

[9]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[10]  M. Folstein,et al.  Clinical diagnosis of Alzheimer's disease , 1984, Neurology.

[11]  Marcella Laiacona,et al.  Tre test clinici di ricerca e produzione lessicale , 1986 .

[12]  G. C. Román,et al.  Vascular dementia , 1993, Neurology.

[13]  K. Siegfried,et al.  The cholinergic hypothesis of Alzheimer's disease , 1993, European Neuropsychopharmacology.

[14]  H. Semlitsch,et al.  Discrimination between demented patients and normals based on topographic EEG slow wave activity: comparison between z statistics, discriminant analysis and artificial neural network classifiers. , 1994, Electroencephalography and clinical neurophysiology.

[15]  K. Coburn,et al.  EEG-based, neural-net predictive classification of Alzheimer's disease versus control subjects is augmented by non-linear EEG measures. , 1994, Electroencephalography and clinical neurophysiology.

[16]  Clinical and neuropathological criteria for frontotemporal dementia. The Lund and Manchester Groups. , 1994, Journal of neurology, neurosurgery, and psychiatry.

[17]  D J Greenblatt,et al.  Pharmacokinetic-Pharmacodynamic Relationships For Benzodiazepines , 1996, Clinical pharmacokinetics.

[18]  M. Kaminski,et al.  Topographic analysis of coherence and propagation of EEG activity during sleep and wakefulness. , 1997, Electroencephalography and clinical neurophysiology.

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

[20]  C Jonker,et al.  The diagnostic value of electroencephalography in mild senile Alzheimer's disease , 1999, Clinical Neurophysiology.

[21]  W. Klimesch EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis , 1999, Brain Research Reviews.

[22]  T Dierks,et al.  Discrimination of Alzheimer's disease and mild cognitive impairment by equivalent EEG sources: a cross-sectional and longitudinal study , 2000, Clinical Neurophysiology.

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

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

[25]  G. Rondouin,et al.  Diagnostic value of quantitative EEG in Alzheimer’s disease , 2001, Neurophysiologie Clinique/Clinical Neurophysiology.

[26]  Trey Sunderland,et al.  Decreased-Amyloid 1-42 and Increased Tau Levels in Cerebrospinal Fluid of Patients With Alzheimer Disease , 2003 .

[27]  I. Han,et al.  EEG Coherence in Alzheimer's Disease , 2003 .

[28]  C. Stam,et al.  EEG synchronization in mild cognitive impairment and Alzheimer's disease , 2003, Acta neurologica Scandinavica.

[29]  Trey Sunderland,et al.  Decreased beta-amyloid1-42 and increased tau levels in cerebrospinal fluid of patients with Alzheimer disease. , 2003, JAMA.

[30]  Jaeseung Jeong EEG dynamics in patients with Alzheimer's disease , 2004, Clinical Neurophysiology.

[31]  Claudio Babiloni,et al.  Abnormal fronto‐parietal coupling of brain rhythms in mild Alzheimer's disease: a multicentric EEG study , 2004, The European journal of neuroscience.

[32]  F. Collette,et al.  Alzheimer' Disease as a Disconnection Syndrome? , 2003, Neuropsychology Review.

[33]  Katarzyna J. Blinowska,et al.  A new method of the description of the information flow in the brain structures , 1991, Biological Cybernetics.

[34]  M. Kaminski,et al.  Granger causality and information flow in multivariate processes. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[35]  Katarzyna J. Blinowska,et al.  Determination of EEG activity propagation: pair-wise versus multichannel estimate , 2004, IEEE Transactions on Biomedical Engineering.

[36]  Daniel B. Rowe,et al.  An evaluation of thresholding techniques in fMRI analysis , 2004, NeuroImage.

[37]  Udo Rüb,et al.  Vulnerability of cortical neurons to Alzheimer's and Parkinson's diseases. , 2006, Journal of Alzheimer's disease : JAD.

[38]  Francesco Rundo,et al.  Fronto-parietal coupling of brain rhythms in mild cognitive impairment: A multicentric EEG study , 2006, Brain Research Bulletin.

[39]  Katarzyna J. Blinowska,et al.  Multivariate Signal Analysis by Parametric Models , 2006 .

[40]  S. Rossi,et al.  Clinical neurophysiology of aging brain: From normal aging to neurodegeneration , 2007, Progress in Neurobiology.

[41]  Christoph Lehmann,et al.  Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG) , 2007, Journal of Neuroscience Methods.

[42]  Paolo Massimo Buscema,et al.  The IFAST model, a novel parallel nonlinear EEG analysis technique, distinguishes mild cognitive impairment and Alzheimer's disease patients with high degree of accuracy , 2007, Artif. Intell. Medicine.

[43]  Claudio Babiloni,et al.  White matter vascular lesions are related to parietal‐to‐frontal coupling of EEG rhythms in mild cognitive impairment , 2008, Human brain mapping.

[44]  Massimo Buscema,et al.  Is it possible to automatically distinguish resting EEG data of normal elderly vs. mild cognitive impairment subjects with high degree of accuracy? , 2008, Clinical Neurophysiology.

[45]  Peter J. Snyder,et al.  Electroencephalography and event-related potentials as biomarkers of mild cognitive impairment and mild Alzheimer’s disease , 2008, Alzheimer's & Dementia.

[46]  Francesco Rundo,et al.  Directionality of EEG synchronization in Alzheimer's disease subjects , 2009, Neurobiology of Aging.

[47]  Claudio Babiloni,et al.  Global functional coupling of resting EEG rhythms is abnormal in mild cognitive impairment and Alzheimer's disease: A multicenter EEG study , 2009 .

[48]  G. Sandini,et al.  Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimer's disease. , 2009, Brain : a journal of neurology.

[49]  Andrzej Cichocki,et al.  A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG , 2010, NeuroImage.

[50]  A. Cichocki,et al.  Diagnosis of Alzheimer's disease from EEG signals: where are we standing? , 2010, Current Alzheimer research.

[51]  G. Frisoni,et al.  Functional network disruption in the degenerative dementias , 2011, The Lancet Neurology.

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

[53]  Karl J. Friston Functional and Effective Connectivity: A Review , 2011, Brain Connect..

[54]  Katarzyna J. Blinowska,et al.  Review of the methods of determination of directed connectivity from multichannel data , 2011, Medical & Biological Engineering & Computing.

[55]  A. Fagan,et al.  Comparison of analytical platforms for cerebrospinal fluid measures of β-amyloid 1-42, total tau, and p-tau181 for identifying Alzheimer disease amyloid plaque pathology. , 2011, Archives of neurology.

[56]  C. Babiloni,et al.  Functional connectivity in Alzheimer’s disease and Mild Cognitive Impairment: an EEG study in the framework of DECIDE project , 2012 .

[57]  David Moratal Pérez,et al.  Practical Biomedical Signal Analysis using MATLAB , 2012 .

[58]  J. Ney,et al.  Evidence-based guideline update: Intraoperative spinal monitoring with somatosensory and transcranial electrical motor evoked potentials: Report of the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology and the American Clinical Neurophysiology Society , 2012, Neurology.

[59]  W. Kukull,et al.  Accuracy of the Clinical Diagnosis of Alzheimer Disease at National Institute on Aging Alzheimer Disease Centers, 2005–2010 , 2012, Journal of neuropathology and experimental neurology.

[60]  Yung-Yang Lin,et al.  Altered Oscillation and Synchronization of Default-Mode Network Activity in Mild Alzheimer’s Disease Compared to Mild Cognitive Impairment: An Electrophysiological Study , 2013, PloS one.

[61]  P. Rossini,et al.  Cortical sources of resting state EEG rhythms are sensitive to the progression of early stage Alzheimer's disease. , 2013, Journal of Alzheimer's disease : JAD.

[62]  Katarzyna J. Blinowska,et al.  Functional Brain Networks: Random, “Small World” or Deterministic? , 2013, PloS one.

[63]  Nick C Fox,et al.  Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria , 2014, The Lancet Neurology.

[64]  Katarzyna J. Blinowska,et al.  Directed Transfer Function is not influenced by volume conduction—inexpedient pre-processing should be avoided , 2014, Front. Comput. Neurosci..

[65]  Wei-Ta Chen,et al.  Altered source-based EEG coherence of resting-state sensorimotor network in early-stage Alzheimer's disease compared to mild cognitive impairment , 2014, Neuroscience Letters.

[66]  Andrzej Cichocki,et al.  A hybrid feature selection approach for the early diagnosis of Alzheimer’s disease , 2015, Journal of neural engineering.

[67]  C. Babiloni,et al.  Brain neural synchronization and functional coupling in Alzheimer's disease as revealed by resting state EEG rhythms. , 2016, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.