Multimodal Quantitative Neuroimaging Databases and Methods: The Cuban Human Brain Mapping Project

This article reviews the contributions of the Cuban Neuroscience Center to the evolution of the statistical parametric mapping (SPM) of quantitative Multimodal Neuroimages (qMN), from its inception to more recent work. Attention is limited to methods that compare individual qMN to normative databases (n/qMN). This evolution is described in three successive stages: (a) the development of one variant of normative topographical quantitative EEG (n/qEEG-top) which carries out statistical comparison of individual EEG spectral topographies with regard to a normative database — as part of the now popular SPM of brain descriptive parameters; (b) the development of n/qEEG tomography (n/qEEG-TOM), which employs brain electrical tomography (BET) to calculate voxelwise SPM maps of source spectral features with respect to a norm; (c) the development of a more general n/qMN by substituting EEG parameters with other neuroimaging descriptive parameters to obtain SPM maps. The study also describes the creation of Cuban normative databases, starting with the Cuban EEG database obtained in the early 90s, and more recently, the Cuban Human Brain Mapping Project (CHBMP). This project has created a 240 subject database of the normal Cuban population, obtained from a population-based random sample, comprising clinical, neuropsychological, EEG, MRI and SPECT data for the same subjects. Examples of clinical studies using qMN are given and, more importantly, receiver operator characteristics (ROC) analyses of the different developments document a sustained effort to assess the clinical usefulness of the techniques.

[1]  E. Michael Kahn,et al.  Topographic maps of brain electrical activity-pitfalls and precautions , 1988, Biological Psychiatry.

[2]  Quantitative electroencephalography: a report on the present state of computerized EEG techniques. American Psychiatric Association Task Force on Quantitative Electrophysiological Assessment. , 1991, The American journal of psychiatry.

[3]  Lourdes Valdés-Urrutia,et al.  White matter architecture rather than cortical surface area correlates with the EEG alpha rhythm , 2010, NeuroImage.

[4]  Nancy A Obuchowski,et al.  Estimating and comparing diagnostic tests' accuracy when the gold standard is not binary. , 2005, Academic radiology.

[5]  Albert Tarantola,et al.  Inverse problem theory - and methods for model parameter estimation , 2004 .

[6]  Pedro A. Valdes-Sosa,et al.  Penalized Least Squares methods for solving the EEG Inverse Problem , 2008 .

[7]  L. Wilkins Assessment: EEG brain mapping , 1989 .

[8]  E. Somersalo,et al.  Visualization of Magnetoencephalographic Data Using Minimum Current Estimates , 1999, NeuroImage.

[9]  D. Lehmann,et al.  Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. , 1994, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[10]  David P. Wipf,et al.  A unified Bayesian framework for MEG/EEG source imaging , 2009, NeuroImage.

[11]  M. N. Nuwer,et al.  Assessment of digital EEG, quantitative EEG, and EEG brain mapping: Report of the American Academy of Neurology and the American Clinical Neurophysiology Society* , 1997, Neurology.

[12]  Antoine Rémond,et al.  Methods of Analysis of Brain Electrical and Magnetic Signals , 1987 .

[13]  Robert Plonsey,et al.  Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields , 1995 .

[14]  S. Kochen,et al.  Approximate average head models for EEG source imaging , 2009, Journal of Neuroscience Methods.

[15]  R M Leahy,et al.  EEG source localization and imaging using multiple signal classification approaches. , 1999, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[16]  Gretel Sanabria-Diaz,et al.  Surface area and cortical thickness descriptors reveal different attributes of the structural human brain networks , 2010, NeuroImage.

[17]  K. Coburn,et al.  The value of quantitative electroencephalography in clinical psychiatry: a report by the Committee on Research of the American Neuropsychiatric Association. , 2006, The Journal of neuropsychiatry and clinical neurosciences.

[18]  Michael Scherg,et al.  Dipole sources potentials of the auditory cortex in normal subjects and in patients with temporal lobe lesions , 1990 .

[19]  C. Michel,et al.  Noninvasive Localization of Electromagnetic Epileptic Activity. I. Method Descriptions and Simulations , 2004, Brain Topography.

[20]  J. C. Jimenez,et al.  High resolution quantitative EEG analysis , 2005, Brain Topography.

[21]  Jose M. Sanchez-Bornot,et al.  Model driven EEG/fMRI fusion of brain oscillations , 2009, Human brain mapping.

[22]  Neurometric assessment of brain dysfunction in neurological patients , 1985 .

[23]  Stefan Haufe,et al.  Open Database of Epileptic EEG with MRI and Postoperational Assessment of Foci—a Real World Verification for the EEG Inverse Solutions , 2010, Neuroinformatics.

[24]  Nelson J. Trujillo-Barreto,et al.  Bayesian M/EEG source reconstruction with spatio-temporal priors , 2008, NeuroImage.

[25]  T. Harmony Driving activity. A quantitative study. , 1975, Activitas nervosa superior.

[26]  E. Gordon,et al.  Brain maturation in adolescence: Concurrent changes in neuroanatomy and neurophysiology , 2007, Human brain mapping.

[27]  J. B. Welch Topographic brain mapping: uses and abuses. , 1992, Hospital practice.

[28]  F. Duffy,et al.  Significance probability mapping: an aid in the topographic analysis of brain electrical activity. , 1981, Electroencephalography and clinical neurophysiology.

[29]  A. Fernández-Bouzas EEG frequency domain distributed inverse solutions in brain lesions , 1997 .

[30]  Karl J. Friston,et al.  Introduction: multimodal neuroimaging of brain connectivity , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[31]  American Electroencephalographic Society Statement on the Clinical Use of Quantitative EEG , 1987 .

[32]  T. Harmony,et al.  EEG SOURCE SPECTRA IN BRAIN INFARCTS , 1998, NeuroImage.

[33]  A K Liu,et al.  Spatiotemporal imaging of human brain activity using functional MRI constrained magnetoencephalography data: Monte Carlo simulations. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[34]  John S. Barlow,et al.  Automation of clinical electroencephalography , 1974 .

[35]  Jorge J. Riera,et al.  Spatio Temporal Distributed Inverse Solutions , 2000 .

[36]  R. Biscay Lirio,et al.  Localization error in biomedical imaging. , 1992 .

[37]  E. Martínez-Montes,et al.  Variable resolution electromagnetic tomography: a new type of inverse solution based on Bayesian formalism , 2001, NeuroImage.

[38]  Ernst Fernando Lopes Da Silva Niedermeyer,et al.  Electroencephalography, basic principles, clinical applications, and related fields , 1982 .

[39]  A. Amador,et al.  Qualitative and quantitative EEG abnormalities in violent offenders with antisocial personality disorder. , 2009, Journal of forensic and legal medicine.

[40]  B. Fisch,et al.  The role of quantitative topographic mapping or 'neurometrics' in the diagnosis of psychiatric and neurological disorders: the cons. , 1989, Electroencephalography and clinical neurophysiology.

[41]  Jorge J. Riera,et al.  Discrete Spline Electric-Magnetic Tomography (DSPECT) Based on Realistic Neuroanatomy , 2000 .

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

[43]  T. Fernández,et al.  Sources of Abnormal EEG Activity in the Presence of Brain Lesions , 1999, Clinical EEG.

[44]  P. Valdés-Sosa,et al.  ERP generator anomalies in presymptomatic carriers of the Alzheimer's disease E280A PS‐1 mutation , 2009, Human brain mapping.

[45]  F. H. Lopes da Silva,et al.  A Critical Review of Clinical Applications of Topographic Mapping of Brain Potentials , 1990, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[46]  F. H. Lopes da Silva,et al.  A critical review of clinical applications of topographic mapping of brain potentials. , 1990 .

[47]  R. Ilmoniemi,et al.  Interpreting magnetic fields of the brain: minimum norm estimates , 2006, Medical and Biological Engineering and Computing.

[48]  Nelson J. Trujillo-Barreto,et al.  Bayesian model averaging in EEG/MEG imaging , 2004, NeuroImage.

[49]  D. Neary,et al.  Dilatation of the Virchow-Robin space is a sensitive indicator of cerebral microvascular disease: study in elderly patients with dementia. , 2005, AJNR. American journal of neuroradiology.

[50]  I F Gorodnitsky,et al.  Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm. , 1995, Electroencephalography and clinical neurophysiology.

[51]  Lester Melie-García,et al.  Characterizing brain anatomical connections using diffusion weighted MRI and graph theory , 2007, NeuroImage.

[52]  G. Pfurtscheller Handbook of electroencephalography and clinical neurophysiology , 1978 .

[53]  B. Macgillivray,et al.  Brain mapping--a useful tool or a dangerous toy? , 1992, Journal of neurology, neurosurgery, and psychiatry.

[54]  T. Gasser,et al.  Transformations towards the normal distribution of broad band spectral parameters of the EEG. , 1982, Electroencephalography and clinical neurophysiology.

[55]  Anders M. Dale,et al.  Improved Localization of Cortical Activity By Combining EEG and MEG with MRI Cortical Surface Reconstruction , 2002 .

[56]  Robert W. Thatcher,et al.  HISTORY OF THE SCIENTIFIC STANDARDS OF QEEG NORMATIVE DATABASES , 2008 .

[57]  Peter A Tass,et al.  swLORETA: a novel approach to robust source localization and synchronization tomography , 2007, Physics in medicine and biology.

[58]  Jouko Lampinen,et al.  Automatic relevance determination based hierarchical Bayesian MEG inversion in practice , 2007, NeuroImage.

[59]  Nelson J. Trujillo-Barreto,et al.  The statistical identification of nonlinear brain dynamics: A progress report , 1999 .

[60]  R Biscay Lirio,et al.  Multivariate Box-Cox transformations with applications to neurometric data. , 1989, Computers in biology and medicine.

[61]  Stavros Stivaros,et al.  Potential surrogate markers of cerebral microvascular angiopathy in asymptomatic subjects at risk of stroke , 2009, European Radiology.

[62]  M. E. Spencer,et al.  A Study of Dipole Localization Accuracy for MEG and EEG using a Human Skull Phantom , 1998, NeuroImage.

[63]  Richard M. Leahy,et al.  MEG-based imaging of focal neuronal current sources , 1995, 1995 IEEE Nuclear Science Symposium and Medical Imaging Conference Record.

[64]  Karl J. Friston,et al.  Statistical parametric maps in functional imaging: A general linear approach , 1994 .

[65]  P. Valdés,et al.  QEEG in a Public Health system , 2005, Brain Topography.

[66]  Alan C. Evans,et al.  Latin American Brain Mapping Network (LABMAN) , 2009, NeuroImage.

[67]  M. Murray,et al.  EEG source imaging , 2004, Clinical Neurophysiology.

[68]  L. Kaufman,et al.  Magnetic source images determined by a lead-field analysis: the unique minimum-norm least-squares estimation , 1992, IEEE Transactions on Biomedical Engineering.

[69]  Rolando J. Biscay,et al.  Frequency domain models of the EEG , 2005, Brain Topography.

[70]  R. Thatcher,et al.  Quantitative EEG Normative Databases: Validation and Clinical Correlation , 2003 .

[71]  J Mazziotta,et al.  A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[72]  E. John,et al.  Developmental equations for the electroencephalogram. , 1980, Science.

[73]  O. Rosso,et al.  The Australian EEG Database , 2005, Clinical EEG and neuroscience.

[74]  Arthur W. Toga,et al.  A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development The International Consortium for Brain Mapping (ICBM) , 1995, NeuroImage.

[75]  E. John The role of quantitative EEG topographic mapping or 'neurometrics' in the diagnosis of psychiatric and neurological disorders: the pros. , 1989, Electroencephalography and clinical neurophysiology.

[76]  F H Duffy,et al.  Status of Quantitative EEG (QEEG) in Clinical Practice, 1994 , 1994, Clinical EEG.

[77]  P. Scheltens,et al.  A semiquantative rating scale for the assessment of signal hyperintensities on magnetic resonance imaging , 1993, Journal of the Neurological Sciences.

[78]  R. Thatcher,et al.  Evaluation and Validity of a LORETA Normative EEG Database , 2005, Clinical EEG and neuroscience.

[79]  J A Swets,et al.  Measuring the accuracy of diagnostic systems. , 1988, Science.

[80]  P. Valdés qEEG signs of HIV infection , 1997 .

[81]  P. Valdés,et al.  Multivariate statistical brain electromagnetic mapping , 2005, Brain Topography.

[82]  Assessment: EEG brain mapping. Report of the American Academy of Neurology, Therapeutics and Technology Assessment Subcommittee. , 1989, Neurology.

[83]  Eduardo Martínez-Montes,et al.  EEG source imaging with spatio‐temporal tomographic nonnegative independent component analysis , 2009, Human brain mapping.

[84]  Andrew L. Janke,et al.  Correlation of Quantitative EEG in Acute Ischemic Stroke With 30-Day NIHSS Score: Comparison With Diffusion and Perfusion MRI , 2004, Stroke.

[85]  Tomás López Jiménez,et al.  Cuban Experiences on Computing and Education , 2008, HCE3.

[86]  Karl J. Friston,et al.  DEM: A variational treatment of dynamic systems , 2008, NeuroImage.

[87]  M. E. Spencer,et al.  A Study of Dipole Localization Accuracy for MEG and EEG using a Human Skull Phantom , 1998, NeuroImage.

[88]  W. Mali,et al.  Blood pressure and progression of cerebral atrophy in patients with vascular disease. , 2009, American journal of hypertension.

[89]  P. Kaplan Intravenous Valproate Treatment of Generalized Nonconvulsive Status Epilepticus , 1999, Clinical EEG.

[90]  Stratified active screening: where neurotechnology meets public health. , 2009, MEDICC review.

[91]  R D Pascual-Marqui,et al.  Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. , 2002, Methods and findings in experimental and clinical pharmacology.