In contrast, both dynamic and stable coding are found in the continuous estimation task. In occipitoparietal electrodes, however, we find that remembered features are dynamically coded over time, whereas neural coding of the ensemble mean is absent in the old/new judgment task.
Here, we consistently observe stable coding of simple features as well as the ensemble mean in frontocentral electrodes, which even correlated with behavioral indices of the ensemble across individuals.
Ensemble representations provide a unique opportunity to investigate structured representations of working memory because the visual system encodes high-order summary statistics as well as noisy sensory inputs in a hierarchical manner. 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.We characterized the population-level neural coding of ensemble representations in visual working memory from human electroencephalography. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The results are produced in the form of MRI images. 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.
FDM is used for head modelling to solve forward problem. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods.
These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. 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. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources.
0 kommentar(er)
