Spatial and Temporal Distribution Enhancement of Movement-Related Brain Macropotentials

Abstract

Conventional brain maps suffer from severe limitations due to both the spatial blur of potential distributions and the dependence on electrical reference. The surface Laplacian (SL) has been used to deblur movement-related brain macropotentials (MRBM) since it acts as a high-pass spatial filter that reduces the head volume conductor effects. Moreover, the method usually employed to improve the signal-to-noise ratio (SNR) is the well-known synchronized average. However, this method is no longer valid when the object of the study is the sweep-by-sweep variability. In this case, the SNR of original and Laplacian-transformed single-sweep MRBM can be improved by autoregressive with exogenous input (ARX) filtering. In our study, isolated or combined ARX and SL are applied to enhance the spatial distributions of single-sweep MRBM associated with unilateral voluntary self-paced finger movements in humans. It shows that single-sweep brain mappings are more coherent to physiological findings when ARX is first used followed by SL.