Neuromagnetic source reconstruction [electronic resource]
Saved in:
| Online Access: |
Online Access |
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| Corporate Author: | |
| Format: | Government Document Electronic eBook |
| Language: | English |
| Published: |
Washington, D.C. : Oak Ridge, Tenn. :
United States. Dept. of Energy ; distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy,
1994.
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| Subjects: |
| Abstract: | In neuromagnetic source reconstruction, a functional map of neural activity is constructed from noninvasive magnetoencephalographic (MEG) measurements. The overall reconstruction problem is under-determined, so some form of source modeling must be applied. We review the two main classes of reconstruction techniques-parametric current dipole models and nonparametric distributed source reconstructions. Current dipole reconstructions use a physically plausible source model, but are limited to cases in which the neural currents are expected to be highly sparse and localized. Distributed source reconstructions can be applied to a wider variety of cases, but must incorporate an implicit source, model in order to arrive at a single reconstruction. We examine distributed source reconstruction in a Bayesian framework to highlight the implicit nonphysical Gaussian assumptions of minimum norm based reconstruction algorithms. We conclude with a brief discussion of alternative non-Gaussian approachs. |
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| Item Description: | Published through the Information Bridge: DOE Scientific and Technical Information. 12/31/1994. "la-ur--94-4378" " conf-9505158--1" "DE95005242" ": NIMH Grant R01-MH-53213" IEEE conference on acoustics, speech and signal processing,Detroit, MI (United States),8-12 May 1995. Lewis, P.S.; Leahy, R.M.; Mosher, J.C. |
| Physical Description: | 4 p. : digital, PDF file. |