Visualization of Magnetoencephalographic Data Using Minimum Current Estimates
Abstract
The locations of active brain areas can be estimated from the magnetic field the neural current sources produce. In this work we study a visualization method of magnetoencephalographic data that is based on minimum[symbol: see text] (1)-norm estimates. The method can represent several local or distributed sources and does not need explicit a priori information. We evaluated the performance of the method using simulation studies. In a situation resembling typical magnetoencephalographic measurement, the mean estimated source strength exceeded baseline level up to 2 cm from the simulated point-like source. The method can also visualize several sources, activated simultaneously or in a sequence, which we demonstrated by analyzing magnetic responses associated with sensory stimulation and a picture naming task.
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L1-norm regularization favors sparse source distribution and assumes that sources follow a Laplace prior distribution in Bayesian inference.
“L1-norm regularization favors sparse source distribution (57–60); it assumes that the sources follow a Laplace prior distribution in Bayesian inference.”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [58]
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- Authors
- Uutela, K., Hämäläinen, M., & Somersalo, E.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 1999-08
- Volume
- 10
- Issue
- 2
- Pages
- 173-180
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2091421749
- Cited by
- 512
- References
- 26
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 10 · 2023: 9 · 2022: 11 · 2021: 10 · 2020: 12 · 2019: 20 · 2018: 17 · 2017: 25 · 2016: 18 · 2015: 15 · 2014: 23 · 2013: 28 · 2012: 28
- FWCI
- 5.93
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Education
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Signal Processing › Direction-of-Arrival Estimation Techniques
- Physical Sciences › Mathematics › Mathematical Physics › Numerical methods in inverse problems
- Keywords
- magnetoencephalography, source localization, sensory stimulation, picture naming
- MeSH terms
- Algorithms, Arousal, Attention, Brain, Brain Mapping, Computer Simulation, Data Interpretation, Statistical, Humans, Image Processing, Computer-Assisted, Reference Values, Magnetoencephalography, Linear Models
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