Single trial estimation of event‐related potential (ERP) components is an open research topic in neuroscience. In this article, we have proposed a method to improve the performance of spatiotemporal filtering by decreasing its dependency to prior estimates of ERP components. For this purpose, we have used a mixture of Gaussian kernels instead of a raw prior signal, and the parameters of the Gaussian kernel are estimated using artificial bee colony algorithm. The algorithm starts with one Gaussian kernel, and after optimizing its parameters, another Gaussian kernel is added. This procedure goes on until the stopping criterion is reached. The efficiency of the algorithm is tested for one single uncorrelated component and two correlated components for synthesized electroencephalogram (EEG) signal. Also, the efficiency of the proposed method is presented on real data for extraction of N170 component in real EEG data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.