Effectiveness of Employing Multimodal Signals in Removing Artifacts from Neuronal Signals: An Empirical Analysis

Neurophysiological recordings, particularly neuronal signals recorded using multi-site neuronal probes or multielectrode arrays, are often contaminated with unwanted signals or artifacts from external or internal sources. Almost all types of neuronal signals including electroencephalogram (EEG), electrocorticogram (ECoG), local field potentials (LFP), and spikes very often suffer greatly from these artifacts and require extensive amount of processing to get rid of them. Despite considerable efforts in developing sophisticated methods to detect and remove these artifacts, it often appears a challenging task due to the inherent similar spatio-temporal properties of the artifacts and the recorded signals. In such cases, the incorporation of another modality can facilitate and improve the detection of these artifacts, and remove them. This paper focuses on the EEG signal and empirically analyses the role played by the addition of a new modality (e.g., cardiac signals, muscular signals, ocular signals, and motion signals) in detecting artifacts from EEG signals.