Computational NeuroscienceThe extraction of LRP via functional data analysis techniques

A new strategy based on functional data analysis (FDA) techniques is proposed to extract the lateralized readiness potential (LRP), which treats electroencephalographic data as functional data. This FDA-based method combines longitudinal information from each trial (time series data) with cross-sectional information from all trials at a fixed time point (cross-sectional data). The comparison results show that the FDA-based LRP is closer to the assumed true LRP and is more robust against a reduction in the number of trials than the traditional average-based LRP. Furthermore, the results indicate that the onset of an FDA-based LRP is more accurate than that of an average-based LRP under several measuring criteria.

► A new strategy based on functional data analysis (FDA) techniques is proposed to extract the lateralized readiness potential (LRP). ► The FDA-based method combines longitudinal information of each trial (time series data) with cross-sectional information from all trials at a fixed time point (cross-sectional data). ► The comparison results show that the FDA-based LRP is closer to the assumed true LRP than the traditional average-based LRP. Meanwhile, the onset of an FDA-based LRP is more accurate than that of an average-based LRP under several measuring criteria.