RESUMO
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.
Assuntos
Córtex Cerebral/anatomia & histologia , Córtex Cerebral/fisiologia , Simulação por Computador/normas , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Mapeamento Encefálico/métodos , Humanos , Vias Neurais/anatomia & histologia , Vias Neurais/fisiologia , Análise de Regressão , Fatores de Tempo , Percepção do Tato/fisiologia , Percepção Visual/fisiologiaRESUMO
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.
Assuntos
Encéfalo/fisiologia , Orelha Externa/fisiologia , Eletroencefalografia , Condutividade Elétrica , Eletrodos , Humanos , Valores de ReferênciaRESUMO
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.
Assuntos
Desenvolvimento Infantil/fisiologia , Eletroencefalografia , Envelhecimento/fisiologia , Encéfalo/fisiologia , Criança , Pré-Escolar , Feminino , Humanos , Masculino , Matemática , Valores de ReferênciaRESUMO
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.
Assuntos
Encéfalo/fisiologia , Algoritmos , Análise de Variância , Humanos , Modelos NeurológicosRESUMO
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.