Imaging of neural oscillations with embedded inferential and group prevalence statistics.

ABSTRACT: Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedd

SUBMITTER: Donhauser PW 

PROVIDER: S-EPMC5815621 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature