Bayesian analysis of MEG visual evoked responses

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The authors developed a method for analyzing neural electromagnetic data that allows probabilistic inferences to be drawn about regions of activation. The method involves the generation of a large number of possible solutions which both fir the data and prior expectations about the nature of probable solutions made explicit by a Bayesian formalism. In addition, they have introduced a model for the current distributions that produce MEG and (EEG) data that allows extended regions of activity, and can easily incorporate prior information such as anatomical constraints from MRI. To evaluate the feasibility and utility of the Bayesian approach with actual ... continued below

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9 p.

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Schmidt, D.M.; George, J.S. & Wood, C.C. April 1, 1999.

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Description

The authors developed a method for analyzing neural electromagnetic data that allows probabilistic inferences to be drawn about regions of activation. The method involves the generation of a large number of possible solutions which both fir the data and prior expectations about the nature of probable solutions made explicit by a Bayesian formalism. In addition, they have introduced a model for the current distributions that produce MEG and (EEG) data that allows extended regions of activity, and can easily incorporate prior information such as anatomical constraints from MRI. To evaluate the feasibility and utility of the Bayesian approach with actual data, they analyzed MEG data from a visual evoked response experiment. They compared Bayesian analyses of MEG responses to visual stimuli in the left and right visual fields, in order to examine the sensitivity of the method to detect known features of human visual cortex organization. They also examined the changing pattern of cortical activation as a function of time.

Physical Description

9 p.

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OSTI as DE99002182

Source

  • SPIE medical imaging conference, San Diego, CA (United States), 20-26 Feb 1999

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  • Other: DE99002182
  • Report No.: LA-UR--99-630
  • Report No.: CONF-990207--
  • Grant Number: W-7405-ENG-36
  • DOI: 10.2172/334231 | External Link
  • Office of Scientific & Technical Information Report Number: 334231
  • Archival Resource Key: ark:/67531/metadc676332

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  • April 1, 1999

Added to The UNT Digital Library

  • July 25, 2015, 2:20 a.m.

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  • Oct. 3, 2017, 7:24 p.m.

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Schmidt, D.M.; George, J.S. & Wood, C.C. Bayesian analysis of MEG visual evoked responses, report, April 1, 1999; New Mexico. (digital.library.unt.edu/ark:/67531/metadc676332/: accessed January 23, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.