RESUMEN
Forward solutions with different levels of complexity are employed for localization of current generators, which are responsible for the electric and magnetic fields measured from the human brain. The influence of brain anisotropy on the forward solution is poorly understood. The goal of this study is to validate an anisotropic model for the intracranial electric forward solution by comparing with the directly measured 'gold standard'. Dipolar sources are created at known locations in the brain and intracranial electroencephalogram (EEG) is recorded simultaneously. Isotropic models with increasing level of complexity are generated along with anisotropic models based on Diffusion tensor imaging (DTI). A Finite Element Method based forward solution is calculated and validated using the measured data. Major findings are (1) An anisotropic model with a linear scaling between the eigenvalues of the electrical conductivity tensor and water self-diffusion tensor in brain tissue is validated. The greatest improvement was obtained when the stimulation site is close to a region of high anisotropy. The model with a global anisotropic ratio of 10:1 between the eigenvalues (parallel: tangential to the fiber direction) has the worst performance of all the anisotropic models. (2) Inclusion of cerebrospinal fluid as well as brain anisotropy in the forward model is necessary for an accurate description of the electric field inside the skull. The results indicate that an anisotropic model based on the DTI can be constructed non-invasively and shows an improved performance when compared to the isotropic models for the calculation of the intracranial EEG forward solution.
Asunto(s)
Encéfalo/fisiología , Electroencefalografía/estadística & datos numéricos , Algoritmos , Anisotropía , Líquido Cefalorraquídeo/fisiología , Interpretación Estadística de Datos , Imagen de Difusión por Resonancia Magnética , Conductividad Eléctrica , Electrodos , Análisis de Elementos Finitos , Cabeza , Humanos , Procesamiento de Imagen Asistido por Computador , Modelos Lineales , Modelos Neurológicos , Reproducibilidad de los Resultados , Cráneo/anatomía & histologíaRESUMEN
Humans today are routinely and increasingly presented with vast quantities of data that challenge their capacity for efficient processing. To restore the balance between man and machine, it is worthwhile to explore new methods for enhancing or accelerating this capacity. This study was designed to investigate the efficacy of transcranial DC stimulation (tDCS) to reduce training time and increase proficiency in spatial recognition using a simulated synthetic aperture radar (SAR) task. Twenty-seven Air Force active duty members volunteered to participate in the study. Each participant was assigned to 1 of 3 stimulation groups and received two, 90-min training sessions on a target search and identification task using SAR imagery followed by a test. The tDCS anode was applied to site F10 according to the 10-20 electroencephalographic electrode convention while the cathode was placed on the contralateral bicep. Group 1 received anodal tDCS at 2 mA for 30 min in the first training session and sham tDCS in the second session. Group 2 received the stimulation conditions in the opposite order. Group 3 did not receive stimulation at all. Results showed that participants receiving training plus tDCS attained visual search accuracies ~25% higher than those provided with sham stimulation or no stimulation. However, a corresponding performance improvement was not found in the first training session for the change detection portion of the task. This indicates that experience with the imagery is important in the tDCS-elicited performance improvements in change detection.