RESUMO
INTRODUCTION: Cerebrovascular disease causes different cognitive alterations. There is a need to develop tools that are capable of diagnosing them. One of them could be event related potentials. These provide an indicator of cognitive processing in real time. PATIENTS AND METHODS: A study was conducted of 10 patients with cerebral infarction in the frontal region and 10 paired healthy controls. Evaluation of the patients was performed a week after the stroke. A continuous performance test was applied to both groups together with the recording of the electrical activity in the brain in order to obtain the P300 component. The results were submitted to the non-parametric Student's t test, and the Bayesian model averaging method (BMAM) was employed to calculate the sources generating the electrical activity recorded on the electroencephalogram. RESULTS: Patients displayed significantly poorer performances compared to the healthy controls in the attention test. The BMAM showed that the P300 component was related to the right hand temporal structures in healthy controls, whereas the left temporoparietal regions were also involved in the patients. CONCLUSIONS: These findings indicate the existence of subclinical disorders affecting sustained attention and that they can only be detected by very sensitive tools; furthermore, they also have implications for the brain circuits regulating sustained attention and the P300 component.
Assuntos
Transtornos Cerebrovasculares/diagnóstico , Potenciais Evocados P300/fisiologia , Potenciais Evocados , Lobo Temporal/fisiopatologia , Atenção/fisiologia , Transtornos Cerebrovasculares/fisiopatologia , Transtornos Cerebrovasculares/psicologia , Dominância Cerebral , Eletroencefalografia , Feminino , Lobo Frontal/irrigação sanguínea , Lobo Frontal/fisiopatologia , Humanos , Masculino , Pessoa de Meia-Idade , Desempenho Psicomotor , Sensibilidade e EspecificidadeRESUMO
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.