Electromagnetic Tomography
Electromagnetic Tomography - Related Videos
02:37
The Electromagnetic Spectrum
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2020
The electromagnetic spectrum consists of all the types of electromagnetic radiation arranged according to their frequency and wavelength. Each of the various colors of visible light has specific frequencies and wavelengths associated with them, and you can see that visible light makes up only a small portion of the electromagnetic spectrum. Because the technologies developed to work in various parts of the electromagnetic spectrum are different, for reasons of convenience and historical...
01:24
The Electromagnetic Spectrum
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2025
Electromagnetic waves are categorized according to their wavelengths and frequencies, giving the electromagnetic spectrum. These waves are classified as radio, infrared, ultraviolet, etc. Radio waves refer to electromagnetic radiation with wavelengths ranging from millimeters to kilometers. Radio waves are commonly used for audio communications (i.e., radios) and typically result from an alternating current in the wires of a broadcast antenna. They cover a broad wavelength range and are used...
06:03
Use of Electromagnetic Navigational Transthoracic Needle Aspiration (E-TTNA) for Sampling of Lung Nodules
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Cited by 12 •
2015
We describe the novel use of electromagnetic navigational guided transthoracic needle aspiration for the pathologic assessment of human lung nodules.
01:30
Electromagnetic Waves
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2023
James Clerk Maxwell formulated a single theory combining all the electric and magnetic effects scientists knew during that time, calling the phenomena his theory predicted “Electromagnetic waves”. He brought together all the work that had been done by brilliant physicists such as Oersted, Coulomb, Gauss, and Faraday and added his own insights to develop the overarching theory of electromagnetism. Maxwell’s equations, combined with the Lorentz force law, encompass all the laws of electricity and...
01:31
Electromagnetic Fields
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2026
Electric fields generated by static charges, often referred to as electrostatic fields, are characteristically different from electric fields created by time-varying magnetic fields. While the former is a conservative field, implying that no net work is done on a test charge if it goes around in a complete loop in the field, the latter is, by definition, not a conservative field; net work is done, and it is proportional to the rate of change of magnetic flux. However, the observation of Gauss's...
FAQs
The central challenge is the inverse nature of the reconstruction: measured signals are available at the body surface, but the underlying locations and strengths of activity are hidden. Mathematical inverse methods estimate source configurations that could have produced those measurements. Consequently, a source map is an evidence-based model, not a direct observation of neuronal tissue.
Head anatomy and modeling assumptions shape how surface measurements are related to possible sources inside the brain. If those inputs or assumptions change, the estimated location and strength of activity can also change. For that reason, researchers interpret reconstructed maps alongside the quality of the sensor data and the assumptions used to generate them.
EEG and MEG contribute different kinds of surface measurements: EEG records electrical signals, whereas MEG records magnetic signals generated by synchronized neuronal currents. The selected sensor modality therefore determines which measurements enter the reconstruction. In either case, mathematical source estimation converts the recorded activity into a model of likely brain locations and strengths.
A typical workflow begins by recording activity with surface sensors, such as EEG or MEG. Researchers then use mathematical inverse methods to estimate the likely locations and strengths of the underlying sources, taking head anatomy and modeling assumptions into account. The resulting source maps are interpreted in relation to the neural process or stimulus being studied.
Source maps can help researchers examine brain organization, communication, and responses to stimuli. By estimating where activity arises and how strong it may be, the maps provide a way to study physiological processes that are not directly visible from surface recordings alone. Their value lies in connecting measured signals with hypotheses about activity inside the brain.
In epilepsy research, reconstructed source maps can support clinical investigation by indicating the likely brain locations associated with recorded electrical or magnetic activity. These estimates do not directly reveal hidden tissue, so interpretation must consider data quality, head anatomy, and model assumptions. Used carefully, the approach can help relate abnormal activity patterns to candidate brain regions.