Electroencephalography (EEG) has been known as the non-invasive tool and used as an index to represent brain state such as being awake, sleeping and to estimate brain regions which are activated as well as widely used in clinical diagnosis. The use of EEG activity to study the cortical process associated with execution of movements has been explored widely. Recent advancements in neuro-prosthetics show us promising ideas to improve the quality of life for people with motor impairments. Futuristic devices that are controlled by thought using BCI will be a great help for Activities of Daily Living (ADL). Decoding such motor tasks and their significance in non-invasive brain-computer interfaces were well studied from the recent past for rehabilitation and to understand the dysfunctions. To date, uncovering neural network dynamics associated with the execution or imagination of different movements has a substantial influence in boosting functional connectivity measures in the brain involved in the processing of motor movement.
Here at the Mind Brain Center our focus is to understand the reconstruction mechanisms in a simple movement by exploring event-related potentials (ERPs) derived from electroencephalography (EEG) signals recorded during the (attempted) execution of motor movements in healthy subjects. We explore patterns of inter-regional couplings during, before, and after the tasks and these pattern features can be significantly employed to distinguish different tasks and are extracted to make classifiers of BCI systems with a good performance
