SynthesisBrain topography2019
Variation in Reported Human Head Tissue Electrical Conductivity Values.
Synthesis in Brain topography, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 117 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
117 citing papers in PubMed.
- Electric field simulation and appropriate electrode positioning for optimized transcranial direct current stimulation of stroke patients: an in Silico model.Scientific reports · 2024Trial
- Atlas-based electrical source imaging for mouse EEG: Application to an Fmr1 knockout model.NeuroImage · 2026Article
- Direction-Dependent Effects of White-Matter Conductivity Anisotropy on Modulation Depth and Spatial Extent in Transcranial Interference Stimulation: A Simulation Study.Brain topography · 2026Article
- Cerebellar Transcranial Alternating Current Stimulation: Frequency-Specific Modulation of Human Gait.Cerebellum (London, England) · 2026Article
- Non-invasive mapping of the temporal processing hierarchy in the human visual cortex.PLoS computational biology · 2026Article
- Forward model of rat electroencephalogram: influence of inhomogeneous and anisotropic skull.Scientific reports · 2026Article
- Linking reduced prefrontal microcircuit inhibition in schizophrenia to EEG biomarkers in silico.PLoS computational biology · 2026Article
- Cranial Sutures Alter Computational Models of Transcranial Electrical Stimulation.The journal of ECT · 2026Article
- Normative modeling of MEG brain oscillations across the human lifespan.Communications biology · 2026Article
- Transcutaneous interference spinal cord stimulation: leadfield-based pareto optimization of electrode montages for improved focality.Biomedical engineering letters · 2026Article
- The Impact of Brain Tumors and Craniotomy Lesions on Scalp EEG.Brain topography · 2026Article
- Inferring neural sources from electroencephalography: foundations and frontiers.Journal of neural engineering · 2026Review
- Neurochemical-hemodynamic-electrophysiological coupling in the neonatal brain: a multimodal MRS-fMRI-EEG investigation.Frontiers in neuroscience · 2026Article
- MRI-guided personalized tDCS planning for target engagement of the swallowing motor cortex after stroke: a finite-element modeling study.Frontiers in neurology · 2026Article
- Ultrasound-guided structural fusion enhances the interpretability of electrical impedance tomography for layered tissue imaging.Journal of electrical bioimpedance · 2026Article
- Simulating tDCS-induced electric fields in stroke patients: Realistic-lesion head models are needed.NeuroImage. Clinical · 2026Article
- Linking Age Changes in Human Cortical Microcircuits to Impaired Brain Function and EEG Biomarkers.Aging cell · 2026Article
- Machine learning enhanced noninvasive transcranial stroke detection using a portable eddy current damping sensor.iScience · 2025Article
- Article
- Comparison of Frequency-Specific Transcranial Alternating Current Stimulations on Cognitive Function in Patients With Mild Cognitive Impairment.Psychiatry investigation · 2025Article
57 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electromagnetic source characterisation requires accurate volume conductor models representing head geometry and the electrical conductivity field. Head tissue conductivity is often assumed from previous literature, however, despite extensive research, measurements are inconsistent. A meta-analysis of reported human head electrical conductivity values was therefore conducted to determine significant variation and subsequent influential factors. Of 3121 identified publications spanning three databases, 56 papers were included in data extraction. Conductivity values were categorised according to tissue type, and recorded alongside methodology, measurement condition, current frequency, tissue temperature, participant pathology and age. We found variation in electrical conductivity of the whole-skull, the spongiform layer of the skull, isotropic, perpendicularly- and parallelly-oriented white matter (WM) and the brain-to-skull-conductivity ratio (BSCR) could be significantly attributed to a combination of differences in methodology and demographics. This large variation should be acknowledged, and care should be taken when creating volume conductor models, ideally constructing them on an individual basis, rather than assuming them from the literature. When personalised models are unavailable, it is suggested weighted average means from the current meta-analysis are used. Assigning conductivity as: 0.41 S/m for the scalp, 0.02 S/m for the whole skull, or when better modelled as a three-layer skull 0.048 S/m for the spongiform layer, 0.007 S/m for the inner compact and 0.005 S/m for the outer compact, as well as 1.71 S/m for the CSF, 0.47 S/m for the grey matter, 0.22 S/m for WM and 50.4 for the BSCR.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.