An algorithm was proposed to enhance the spatial resolution of solutions of the under determined electroencephalography (EEG) inverse problem. The self-coherence enhancement algorithm (SCEA) provides a self-coherence solution, which is a function of self-coherence estimate of the under determined EEG inverse solution. The high order self-coherence function was determined by the blurring level of the actual source distribution.
Bibliographical noteFunding Information:
The authors wish to thank Jie Lian and Dr. Dong-sheng Wu for valuable discussions. This work was supported in part by NSF CAREER Award BES-9875344 and a grant from The Whitaker Foundation.
- Brain imaging
- EEG source reconstruction
- Functional imaging
- Image enhancement
- Minimum norm solution
- Self-coherence solution