Name
Abstract | ||
|---|---|---|
Electroencephalography EEG is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low-resolution brain electromagnetic tomography LORETA and standardized LORETA sLORETA have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian sLORETA in conjunction with finite difference method FDM as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density J for an area as compared to others. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1002/ima.22157 | Int. J. Imaging Systems and Technology |
Keywords | Field | DocType |
brain activation, source localization, EEG, finite difference method, LORETA, sLORETA, MRI | Computer vision,Signal processing,Digital filter,Computer science,Tomography,Artificial intelligence,Finite difference method,Image resolution,Electroencephalography,Visual perception,Bayesian probability | Journal |
Volume | Issue | ISSN |
26 | 1 | 0899-9457 |
Citations | PageRank | References |
3 | 0.44 | 5 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Munsif Ali Jatoi | 1 | 22 | 3.10 |
| Nidal S. Kamel | 2 | 86 | 18.18 |
| aamir saeed malik | 3 | 373 | 53.61 |
| ibrahima faye | 4 | 179 | 19.82 |
| Jose Miguel Bornot | 5 | 9 | 1.67 |
| Tahamina Begum | 6 | 24 | 3.47 |