Extraction of microsaccade-related signal from single-trial local field potential by ICA with reference

During visual fixation, we unconsciously make tiny, involuntary eye movements or 'microsaccades', which have been shown to have a crucial influence on analysis and perception of our visual environment. Given the small size and high irregularity of microsaccades, it is a significant challenge to detect and extract the microsaccade-related neural activities. In this work, we present a novel application of the independent component analysis with reference algorithm to extract microsaccade-related neural activity from single-trial local field potential (LFP). We showed via extensive computer simulations that our approach can be used to reliably extract microsaccade-related activity. We then applied our method to real cortical LFP data collected from multiple visual areas of monkeys performing a generalized flash suppression task and demonstrated that our approach has excellent performance in extracting microsaccade-related signal from single-trial LFP data.