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Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
Published on: October 24, 2012
Assessment of subcortical source localization using deep brain activity imaging model with minimum norm operators: a
1CRICM UMR-S975 - Centre de Recherche de l'Institut du Cerveau et de la Moelle Epinière, Université Pierre et Marie Curie-Paris 6, Paris, France. yohan.attal@upmc.fr
Plos One
|March 26, 2013
Summary
Magnetoencephalography (MEG) can accurately detect deep brain activity, even from the hippocampus and thalamus. Advanced models improve the localization of these subcortical sources, overcoming distance and anatomical challenges for better brain activity assessment.
Area of Science:
- Neuroscience
- Biophysics
- Medical Imaging
Background:
- Subcortical structures are vital for brain function, yet detecting their activity with magnetoencephalography (MEG) is challenging due to their depth and complex anatomy.
- Accurate localization of subcortical generators is crucial for understanding both healthy brain processes and neurological pathologies.
Purpose of the Study:
- To assess the source localization accuracy of MEG for subcortical generators.
- To compare the performance of three inverse operators (wMNE, sLORETA, dSPM) in localizing deep brain activity.
- To investigate the impact of noise-normalization methods on accuracy and potential biases.
Main Methods:
- Utilized a realistic anatomical and electrophysiological model of deep brain activity (DBA).
- Analyzed point-spread and cross-talk functions of wMNE, sLORETA, and dSPM inverse operators.
- Conducted Monte Carlo simulations with both neocortical and subcortical activations, including simultaneous activity.
Main Results:
- MEG demonstrated good accuracy in localizing single hippocampus activations.
- wMNE could detect hippocampal activity embedded within cortical sources, though with some bias towards superficial locations.
- dSPM and sLORETA detected deeper hippocampal activity but risked creating spurious "ghost" sources.
- The DBA model confirmed the feasibility of detecting weak thalamic modulations.
Conclusions:
- MEG, when combined with realistic modeling and appropriate inverse methods, can effectively detect and localize subcortical brain activity.
- The choice of inverse operator influences the accuracy and potential biases in localizing deep brain sources.
- This approach holds promise for advancing the study of neurological disorders involving subcortical structures.
