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Magnetoencephalographic (MEG) measurements record magnetic fields generatedfrom neurons while information is being processed in the brain. The inverseproblem of identifying sources of biomagnetic fields and deducing theirintensities from MEG measurements is ill-posed when the number of fielddetectors is far less than the number of sources. This problem is less severeif there is already a reasonable prior knowledge in the form of a distributionin the intensity of source activation. In this case the problem of identifyingand deducing source intensities may be transformed to one of using the MEG datato update a prior distribution to a posterior distribution. Here we report onsome work done using the maximum entropy method (ME) as an updating tool.Specifically, we propose an implementation of the ME method in cases when theprior contain almost no knowledge of source activation. Two examples arestudied, in which part of motor cortex is activated with uniform and varyingintensities, respectively.Comment: 8 pages, 8 figures. Presented at 25th International Workshop on  Bayesian Inference and Maximum Entropy Methods in Science and Engineering,  San Jose, CA, USA Aug 7-12, 200

Identifying Biomagnetic Sources in the Brain by the Maximum Entropy Approach