ABSTRACT
For the purpose of statistical characterization of the spatio-temporal correlation structure of brain functioning from high-dimensional fMRI time series, we introduce an innovation approach. This is based on whitening the data by the Nearest-Neighbors AutoRegressive model with external inputs (NN-ARx). Correlations between the resulting innovations are an extension of the usual correlations, in which mean-correction is carried out by the dynamic NN-ARx model instead of the static, standard linear model for fMRI time series. Measures of dependencies between regions are defined by summarizing correlations among innovations at several time lags over pairs of voxels. Such summarization does not involve averaging the data over each region, which prevents loss of information in case of non-homogeneous regions. Statistical tests based on these measures are elaborated, which allow for assessing the correlation structure in search of connectivity. Results of application of the NN-ARx approach to fMRI data recorded in visual stimuli experiments are shown. Finally, a number of issues related with its potential and limitations are commented.
Subject(s)
Cerebral Cortex/anatomy & histology , Cerebral Cortex/physiology , Computer Simulation/standards , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Brain Mapping/methods , Humans , Neural Pathways/anatomy & histology , Neural Pathways/physiology , Regression Analysis , Time Factors , Touch Perception/physiology , Visual Perception/physiologyABSTRACT
Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.
Subject(s)
Brain Mapping , Cerebral Cortex/physiopathology , Electroencephalography , Epilepsy, Temporal Lobe/physiopathology , Signal Processing, Computer-Assisted , Adult , Alpha Rhythm , Child , Epilepsy, Temporal Lobe/diagnosis , Evoked Potentials/physiology , Female , Humans , Male , Mathematical Computing , Reference Values , Sleep Stages/physiologyABSTRACT
This article describes a new method for 3D QEEG tomography in the frequency domain. A variant of Statistical Parametric Mapping is presented for source log spectra. Sources are estimated by means of a Discrete Spline EEG inverse solution known as Variable Resolution Electromagnetic Tomography (VARETA). Anatomical constraints are incorporated by the use of the Montreal Neurological Institute (MNI) probabilistic brain atlas. Efficient methods are developed for frequency domain VARETA in order to estimate the source spectra for the set of 10(3)-10(5) voxels that comprise an EEG/MEG inverse solution. High resolution source Z spectra are then defined with respect to the age dependent mean and standard deviations of each voxel, which are summarized as regression equations calculated from the Cuban EEG normative database. The statistical issues involved are addressed by the use of extreme value statistics. Examples are shown that illustrate the potential clinical utility of the methods herein developed.
Subject(s)
Electroencephalography , Adolescent , Adult , Aged , Aged, 80 and over , Brain/anatomy & histology , Brain/physiology , Child , Child, Preschool , Electroencephalography/methods , Electromagnetic Phenomena , Female , Humans , Male , Middle Aged , Random Allocation , Tomography/methodsABSTRACT
Recent theoretical analysis supports the possibility that using a linked earlobe reference in EEG studies might appreciatively distort the measured electrical field due to current flow over a low resistance path across the wire joining both ears. Such an effect would invalidate published quantitative EEG norms. Evidence for the balancing effect of this distortion was sought for in the EEG of 4 patients with well localized unilateral lesions, a situation in which this distortion would be most apparent. Statistical tests failed to reveal significant differences between EEGs recorded when ears were linked or unlinked. An analysis of the equivalent circuit reveals that a high skin/electrode impedance effectively makes the linked ear reference behave as an ordinary reference.
Subject(s)
Brain/physiology , Ear, External/physiology , Electroencephalography , Electric Conductivity , Electrodes , Humans , Reference ValuesABSTRACT
Two different descriptions of EEG maturation are compared: a broad-band spectral parameters (BBSPs) model and a recently developed xi-alpha (xi alpha) model. 'Developmental equations' were obtained for both parameter sets using 1 min, eyes closed EEG sample from 165 normal children (5-12 years old). At each age, the xi alpha parameter set described the average spectrum more closely than the BBSP developmental equations. Furthermore, a more detailed picture of changes of spectral shape with age is possible with the xi alpha model. A computer simulation illustrates the possible appearance of fixed frequency bands as a byproduct of inadequate statistical models.
Subject(s)
Child Development/physiology , Electroencephalography , Aging/physiology , Brain/physiology , Child , Child, Preschool , Female , Humans , Male , Mathematics , Reference ValuesABSTRACT
A statistical approach is presented which provides efficient procedures to detect both Event Related Potential (ERP) and its spectral structure. Situations where undesirable signal or "artifact" is present, are considered. In these cases, a "noise" sample can be used which complements the insufficient knowledge given for the sample where we expect to detect the ERP. In this approach, Hotelling's T2 statistic for one and two samples arises as a natural detector of ERPs. Under the assumption of stationarity these statistics are calculated by approximate expressions in the frequency domain. For Brainstem Auditory Evoked Potentials, ROC curves confirm that the T2 statistic has higher detection rates than various indices proposed in the literature. A frequency decomposition of the T2 statistic yields a succession of complex versions of Student's t statistic that characterize the spectral structure of the ERP. Different assumptions about the recordings of ERP are discussed and several generalizations are suggested.
Subject(s)
Brain/physiology , Evoked Potentials , Models, Neurological , Models, Statistical , Brain Stem/physiology , Electrophysiology/methods , Evoked Potentials, Auditory , Evoked Potentials, Visual , Humans , Infant, Newborn , MathematicsABSTRACT
The Box-Cox power transform methodology for achieving Gaussianity is developed for a variety of models useful in neurometric statistical analysis. Algorithms are proposed for estimating the optimal transformations in the univariate and multivariate cases. Their use is briefly illustrated with neurometric data.
Subject(s)
Brain/physiology , Algorithms , Analysis of Variance , Humans , Models, NeurologicalABSTRACT
A method for the spatial analysis of EEG and EP data, based on the spherical harmonic Fourier expansion (SHE) of scalp potential measurements, is described. This model provides efficient and accurate formulas for: (1) the computation of the surface Laplacian and (2) the interpolation of electrical potentials, current source densities, test statistics and other derived variables. Physiologically based simulation experiments show that the SHE method gives better estimates of the surface Laplacian than the commonly used finite difference method. Cross-validation studies for the objective comparison of different interpolation methods demonstrate the superiority of the SHE over the commonly used methods based on the weighted (inverse distance) average of the nearest three and four neighbor values.
Subject(s)
Electroencephalography , Evoked Potentials , Fourier Analysis , Models, Neurological , Brain/physiology , HumansABSTRACT
The EEG is modelled as the superposition of two component processes: the xi and the alpha processes. In the frequency domain, the xi process is always present and appears as a spectral peak with maximum amplitude at very low frequencies, while the alpha process is characterized by a spectral peak with its maximum located in the traditional alpha band (7-13 Hz), and is not necessarily always present. The multivariate properties of EEG spectra are adequately modelled with frequency independent coherence matrices for each process. Multichannel EEG studies reveal interesting properties: (1) the generalized coherence for alpha is much larger than for xi, indicating increased functional coupling for the alpha process; (2) the alpha coherence matrix has reduced dimensionality, possibly related to a small number of generators; (3) xi coherences are zero phase with magnitudes that decrease exponentially with interelectrode distance; and (4) alpha coherences have significant nonzero phase shifts.
Subject(s)
Electroencephalography , Algorithms , Child , Child, Preschool , Humans , Models, Neurological , Reference ValuesABSTRACT
The performance of statistical evoked-potential detection methods was compared with that of human observers and among themselves by means of receiver operating characteristics (ROC) curves. The test material was a collection of brain stem auditory-evoked responses obtained from 98 infants with 60 and 30 dB nHL clicks. The observers and the statistical methods had to discriminate these responses from control recordings obtained without acoustic stimulation. Although the observers' criteria on different days varied considerably, the discrimination capacity was more stable. The discrimination capacity depended on the observers' experience. The statistical methods tested were the correlation coefficient (CCR), the standard deviation ratio (SDR) and a new method named T2R. The most efficient detection method was T2R. For false-alarm rates of 0.01 the statistical methods were more efficient than the human observers. Signal detection theory is useful for the evaluation of evoked-potential analysis methods.
Subject(s)
Evoked Potentials, Auditory , Brain Stem/physiology , Electrophysiology , Humans , Infant , Methods , Noise , Signal Processing, Computer-AssistedABSTRACT
En este trabajo se presenta un método para la estimación de los potenciales relacionados a eventos (PRE) contenidos en segmentos de electroencefalograma (EEG). El modelo presupone que en el dominio del tiempo los potenciales relacionados a eventos múltiples (PREM) se superponen aditivamente. Cada componente es de morfología constante pero su amplitud y latencia pueden variar. Se presenta un algoritmo máximo verosímil para la estimación de la forma de onda de cada componente que utiliza una estimación a priori de sus latencias. El algoritmo fue valiado con PREM simulados por computadora y utilizado en la descripción de potenciales evocados auditivos de tallo cerebral de humanos y potenciales evocados auditivos de latencia media de humanos y primates
Subject(s)
Humans , Electroencephalography , Evoked Potentials, Auditory , Acoustic Stimulation/methodsABSTRACT
El presente trabajo presenta un nuevo método para la detección de Potenciales Evocados en el dominio de la frecuencia. El cual consiste en la comparación de dos muestras de registros mediante la versión en el campo complejo del estadígrafo T2 de Hotelling para dos muestras. Una muestra está formada por segmentos de EEG y la otra por segmentos registrados durante la estimulación. Las curvas Características de Operación del Receptor muestran que una expresión aproximada del estadígrafo T2 de Hotelling para dos muestras es mejor que la medida de sincronía presentada por Fridman y que la expresión aproximada del estadígrafo T2 para una muestra desarrollada en nuestro grupo. Para determinar la composición espectral del Potencial Evocado se emplearon estadígrafos análogos. En el campo complejo, a la t de Student para una y dos muestras. Cuando está presente una señal independiente del estímulo sólo el estadígrafo para dos muestras es capaz de revelar la estructura espectral del PE
Subject(s)
Humans , Infant, Newborn , Evoked Potentials, Auditory , Acoustic Stimulation/methods , Audiometry, Evoked Response , Electroencephalography , StatisticsABSTRACT
En este trabajo se describe un nuevo método para la estimulación de la densidad de fuentes de corrientes para el EEG (electroencefalograma) y los PEs (potenciales evocados). El método consiste en que la distribución del potencial eléctrico sobre la cabeza es expandida en términos de armónicos esféricos. Condicionada a poseer una curvatura media cuadrática mínima. Esta técnica posse ventajas significativas sobre los métodos descritos en la literatura actual, como son aquellos basados en el cálculo del Laplaciano de superficie mediante diferencias finitas. Además, mediante este nuevo método es posible construir imágenes con información eléctrica sin la necesidad de utilizar funciones arbitrarias para la interpolación
Subject(s)
Humans , Electroencephalography , Evoked Potentials, Auditory , Acoustic Stimulation/methodsABSTRACT
Se estudió una muestra de 96 niños normales entre 7 y 11 años de edad, con el objetivo de ensayar nuevas estrategias de análisis del EEG. Se definieron 3 medidas globales que contienen valiosa información que resume las características más importantes evaluadas en el análisis del EEG en el dominio de la frecuencia. Se utilizaron análisis multivariados que permiten conocer desviaciones con respecto a una norma, encontrándose que las medidas globales son capaces de evaluar las regularidades que rigen la maduración del EEG
Subject(s)
Humans , Male , Female , Child , Electroencephalography , Multivariate Analysis , CubaABSTRACT
El EEG es modelado como la superposición de dos procesos componentes: y alfa. En el dominio de la frecuencia, el proceso siempre está presente y aparece como un pico espectral centrado en o Hz, mientras que el pico espectral del proceso alfa está centrado en la banda tradicional alfa (17-13 Hz), y no siempre está presente. Se postula que el processo es generado por el sistema de proyección tálamo-cortical generalizado y que su propagación ocurre mediante conecciones corticales de corto alcance, mientras que el proceso alfa está relacionado al sistema de proyección tálamo-cortical específico y se propaga vía fibras de asociación cortico-corticales de largo alcance
Subject(s)
Humans , Child, Preschool , Child , Electroencephalography , Cortical SynchronizationABSTRACT
Se realizó el análisis cuantitativo de 1 minuto de actividad electroencefalográfica (EEG) en 192 niños normales entre 5 y 12 años de edad. El espectro de frecuencias del EEG se ajustó mediante dos modelos diferentes (Medidas Espectrales de Banda Ancha y Medidas de Modelo XI-ALFA) obteniéndose dos grupos de variables cuantitativos. Se aplicaron técnicas estadísticas multivariables para comparar la variables cuantitativos de diferentes submuestras de esta población para estudiar el efecto del sexo, los antecedentes de riesgos biológicos, la circunferencia cefálica y el cociente de inteligencia sobre las mismas
Subject(s)
Humans , Child, Preschool , Child , Electroencephalography , Multivariate AnalysisABSTRACT
Se describen las variaciones con la edad de las variables cuantitativas obtenidas del Electroencefalograma mediante dos modelos de ajuste diferentes en un grupo de 192 niños normales entre 5 y 12 años de edad. Se aplican técnicas de regresión no lineal para lograr mejores ajustes de las curvas de regresión. Se comparon los resultados obtenidos con los dos modelos y se discuten las ventajas del nuevo modelo Xi-Alfa sobre el tradicional análisis de Banda Ancha
Subject(s)
Humans , Child, Preschool , Child , Spectrum Analysis , Multivariate Analysis , ElectroencephalographyABSTRACT
Se calcularon dos conjuntos diferentes de medidas cuantitativas del EEG en un grupo de 63 niños con Retraso Mental Ligero, comparándose mediante técnicas estadisticas uni y multivariadas con un grupo de niños normales. Se estudiaron medidas cuantitativas globales que permiten hacer inferencias sobre la fisiopatologia de este tipo de trastorno. Se comparan los resultados obtenidos con ambos grupos de medidas cuantitativas