PubMed Health⌕ Search

PubMed · 10916164

EEG and implanted sources in the brain.

Abstract

Localisation procedures are based on models of the EEG that are relatively simple. The models are based on assumptions and choices of parameters that can be mistaken. Thus, it is crucial to validate the localisation procedures used in EEG. One of the options is to use the data obtained with electrodes that are implanted within the brain of an epileptic patient as part of the pre-surgical evaluation. When one of two neighbouring electrodes is used as a current source and the other as a current sink this can be regarded as a current dipole. The current injected has to be below the threshold for activation of cells. The position of this dipole can be deduced from magnetic resonance or X-ray images. The current dipole gives rise to a potential distribution at the scalp that can be measured by EEG. The measurements can be compared with the potential distribution that is calculated in a forward computation. Another method is to use the measured potential at the scalp to localize the source and to compare the result with the actual position of the dipole. In this paper the measured potential distributions at the scalp due to implanted dipoles were used to evaluate different volume conductor models. Since intracerebral and subdural electrodes were introduced through trephine holes over the fronto-central areas, and the diameter of the holes was rather large, approximately 23 mm, special effort was put into modelling the skull. Two important assumptions could be validated in this study: the electric currents within the head are Ohmic and a dipole can be used to model the induced electric activity of pairs of contacts on subdural electrodes or intra cerebral electrodes.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M van Burik, M Peters. 1999. EEG and implanted sources in the brain.. https://doi.org/10.1076/138134551999121070515ft367

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

A MAGIBU-based model for pediatric and juvenile CNS tumors: an in-house epigenetic decision-support framework compared with online DNA methylation classifiers.

Background: DNA methylation profiling is a tool that provides key support for central nervous system (CNS) tumor classification. However, diagnostically ambiguous pediatric cases may result in discordant outputs across classifiers. We developed MAGIBU, a cross-platform, projection-based framework that embeds individual methylomes into a fixed CNS reference landscape, ranking diagnostic entities by local epigenetic proximity to support clinician-led integrative diagnosis. Methods: As a proof-of-concept, we evaluated MAGIBU in eight morphologically challenging pediatric/juvenile CNS tumors with unresolved diagnoses after institutional and central pathology review. To establish a benchmark in the absence of a definitive histopathological ground truth, a consensus epigenetic reference was defined a priori for cases showing concordant results between the Heidelberg CNS Tumor Methylation Classifier and Methylscape Analysis. Comparisons were also performed with Epigenomic Digital Pathology (EpiDiP). To validate MAGIBU beyond this discovery cohort, performance was assessed at the family level across the CNS methylation spectrum (n = 678, 28 methylation families), on non-array platforms (whole-genome bisulfite sequencing and Oxford Nanopore), and in a focused analysis of the low-grade glioma and diffuse midline glioma compartment across four independent cohorts (n = 670). Results: In the discovery cohort, MAGIBU achieved high concordance with the consensus reference (Cohen's κ = 0.855), outperforming EpiDiP (κ = 0.278), which frequently placed low-grade tumors in proximity to higher-grade reference regions. Conclusions: MAGIBU provides a stable, quantitative differential diagnosis framework that mitigates the limitations of rigid categorical assignments. By leveraging a distance-based proximity metric, it offers a transparent decision-support tool that integrates effectively with clinical, radiological, and molecular data. While performance is inherently dependent on reference atlas composition, MAGIBU represents a robust complementary approach for the diagnostic workup of ambiguous CNS tumors.

Brain↗

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Brain↗