Conditionally Exponential Prior in Focal Near- and Far-Field EEG Source Localization via Randomized Multiresolution Scanning (RAMUS)
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This paper develops mathematical methods for localizing focal sources at different depths based on the non-invasive electro-/magnetoencephalography measurements. In the context of hierarchical Bayesian modelling, we introduce a conditionally exponential prior (CEP) which extends the concept of the conditionally Gaussian prior (CGP) and has been proposed to be advantageous in reconstructing far-field activity, in particular, when coupled with randomized multiresolution scanning (RAMUS). An approach to obtain the shape and scale parameter of the gamma hyperprior steering the CEP is derived from the physiological a priori knowledge of the brain activity. The core concept of this study is to show that the first-degree CEP will yield and improve the focality compared to the second-order case. The results of the present numerical experiments suggest that sources reconstructed via a combination of the first-degree CEP and RAMUS achieve an accuracy comparable to the second-degree case while being more focal for numerically simulated originators of human somatosensory evoked potentials (SEPs) related to human median nerve stimulation, including simultaneous thalamic and cortical activity, as well as for a sub-thalamic dipolar and quadrupolar source configuration.
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