Tommi Raij

This study uses MEG to show that trigger sounds in misophonia elicit smaller evoked responses and different oscillatory patterns in the right auditory cortex compared to non-trigger sounds.

This study investigates how EEG lead configurations affect TMS-induced EEG artifacts and finds that certain configurations can minimize both pulse and decay artifacts.

This paper introduces a fast MEG source estimation method using reciprocal relationships and BEM-FMM, achieving high-resolution gain matrices for up to 1 million dipoles.

The paper develops a BEM-based method to solve EEG/MEG forward problems for high-resolution head models in about 60 seconds.

The paper compares dipole source reconstruction accuracy between 3-layer and 5-layer BEM-FMM models, finding that 3-layer models provide good localization but less accurate orientation, with AMR improving 5-layer accuracy.

The paper decodes auditory working memory content from EEG aftereffects of auditory-cortical TMS using multivariate pattern analysis.

The paper uses MEG and computational modeling to show that cross-sensory visual input to human auditory cortex is feedback-type, consistent with findings in non-human primates.

The paper develops and validates a new EEG source localization algorithm using BEM-FMM, reciprocity principle, and TES forward model matrix, achieving high-resolution source reconstruction with low computational cost.

The paper introduces a software toolkit for high-resolution TMS modeling that balances computational speed and spatial precision using BEM-FMM, compatible with human head models.