source localization
Computational process to determine the brain regions generating observed electrical or magnetic signals recorded from scalp-based measurements.
Full Definition
Source localization, also known as the inverse problem in electrophysiology, involves determining the spatial origins of neural activity from surface measurements such as EEG or MEG. This computational challenge arises because multiple combinations of brain sources can produce identical scalp recordings, making the solution mathematically underdetermined. Various algorithms including dipole fitting, distributed source models (minimum norm estimation, sLORETA), and beamforming approaches are used to estimate source locations. The accuracy of source localization depends on factors including head modeling, electrode density, signal-to-noise ratio, and the assumptions underlying the chosen algorithm. Source localization enables researchers to bridge between scalp recordings and underlying brain activity patterns.
Usage
Usage note: Specify the algorithm used (e.g., sLORETA, beamforming) as different methods have varying assumptions.
In Context
- "Source localization identified bilateral temporal generators for the auditory evoked response." — EEG source analysis study
- "sLORETA was used for source localization with 64-channel EEG recordings." — Electrophysiology methods section