Predicting Intended Movement Direction Using EEG from Human Posterior Parietal Cortex

The posterior parietal cortex (PPC) plays an important role in motor planning and execution. Here, we investigated whether noninvasive electroencephalographic (EEG) signals recorded from the human PPC can be used to decode intended movement direction. To this end, we recorded wholehead EEG with a delayed saccade-or-reach task and found direction-related modulation of event-related potentials (ERPs) in the PPC. Using parietal EEG components extracted by independent component analysis (ICA), we obtained an average accuracy of 80.25% on four subjects in binary single-trial EEG classification (left versus right). These results show that in the PPC, neuronal activity associated with different movement directions can be distinguished using EEG recording and might, thus, be used to drive a noninvasive brainmachine interface (BMI). Key words: posterior parietal cortex (PPC); electroencephalography (EEG); independent component analysis (ICA); brain-machine interface (BMI).

• Type: Journal
• Year: 2009
• Where: HCI
• Authors: Yijun Wang, Scott Makeig
• Keywords: HCI 2009, Human Computer Interaction, Independent Component Analysis, Parietal Eeg Components, Posterior Parietal Cortex