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Updated: Apr 21, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Eric Larson1, Ross K Maddox1, Adrian K C Lee2
1Institute for Learning and Brain Sciences, University of Washington Seattle, WA, USA.
Combining magnetoencephalography (MEG) data across individuals with diverse brain geometry improves source localization accuracy. This approach mitigates spatial uncertainty in neural activity mapping, enhancing data interpretation and overcoming technical challenges.
11:28Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
Published on: June 30, 2018
11:03High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging
Published on: November 10, 2015
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