Space–time event sparse penalization for magneto-/electroencephalography
Open accessAbstract
This article presents a new spatio-temporal method for M/EEG source reconstruction based on the assumption that only a small number of events, localized in space and/or time, are responsible for the measured signal. Each space-time event is represented using a basis function expansion which reflects the most relevant (or measurable) features of the signal. This model of neural activity leads naturally to a Bayesian likelihood function which balances the model fit to the data with the complexity of the model, where the complexity is related to the number of included events. A novel Expectation-Maximization algorithm which maximizes the likelihood function is presented. The new method is shown to be effective on several MEG simulations of neurological activity as well as data from a self-paced finger tapping experiment.
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- Authors
- Bolstad, A., Veen, B. V., & Nowak, R.
- Affiliations
- University of Wisconsin–Madison (US)
- Corresponding author
- Bolstad, Andrew
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2009-07
- Volume
- 46
- Issue
- 4
- Pages
- 1066-1081
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2850823
- OpenAlex
- W2136760486
- Cited by
- 71
- References
- 46
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 1 · 2021: 2 · 2020: 5 · 2019: 2 · 2018: 4 · 2017: 5 · 2016: 8 · 2015: 7 · 2014: 5 · 2013: 7 · 2012: 8
- FWCI
- 3.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Biomedical Imaging and Bioengineering (R21EB005473)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Mathematics › Mathematical Physics › Numerical methods in inverse problems
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- magnetoencephalography, EEG, source localization, basis function expansion, expectation-maximization algorithm, neural activity modeling
- MeSH terms
- Algorithms, Brain Mapping, Computer Simulation, Humans, Image Processing, Computer-Assisted, Models, Neurological, Magnetoencephalography
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