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Assessing and improving the spatial accuracy in MEG source localization by depth-weighted minimum-norm estimates
Parieto-occipital approximately 10 Hz activity reflects anticipatory state of visual attention mechanisms.
High-density eeg recordings revealed sensory specific modulation of anticipatory parieto-occipital approximately 10 Hz oscillatory activity when visually presented word cues instructed subjects in an intermodal selective attention paradigm, and these results support models implicating parietoscipital areas in the directing and maintenance of visual attention.
Mapping the signal‐to‐noise‐ratios of cortical sources in magnetoencephalography and electroencephalography
Clinically, SNR maps in a patient explained differential sensitivity of MEG and EEG in detecting epileptic activity, and the results emphasize the benefits of recording M EG and EEG simultaneously.
Sensitivity of MEG and EEG to Source Orientation
For most cortical locations there was a source orientation to which MEG was insensitive, and the difference in the sensitivity is expected to contribute to systematic differences in the signal-to-noise ratio between MEG and EEG.
Lexical influences on speech perception: A Granger causality analysis of MEG and EEG source estimates
Spatiotemporal activity of a cortical network for processing visual motion revealed by MEG and fMRI.
Characteristic patterns of activity are revealed in this cortical network for processing sudden changes in the direction of visual motion in motion sensitive areas of the brain.
Magnetoencephalographic 10-Hz rhythm from the human auditory cortex
Developmental neural networks in children performing a Categorical N-Back Task
Parieto‐occipital ∼1 0Hz activity reflects anticipatory state of visual attention mechanisms
HIGH-DENSITY EEG recordings revealed sensory specific modulation of anticipatory parieto-occipital ∼10 Hz oscillatory activity when visually presented word cues instructed subjects in an intermodal…
Attention-driven auditory cortex short-term plasticity helps segregate relevant sounds from noise
- J. Ahveninen, M. Hämäläinen, J. Belliveau
- Biology, PhysicsProceedings of the National Academy of Sciences
- 22 February 2011
A simple gain model alone cannot explain auditory selective attention, and attention-driven short-term plasticity retunes neurons to segregate relevant sounds from noise in noisy environments.