Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: EEG connectivity measures could provide a new type of feature space for inferring a subject's intention in Brain-Computer Interfaces (BCIs). Hover, very little is known on EEG connectivity patterns for BCIs. In this study, EEG connectivity during motor imagery (MI) of the left and right is investigated in a broad frequency range across the whole scalp by combining Beamforming with Transfer Entropy and taking into account possible volume conduction effects. Observed connectivity patterns indicate that modulation intentionally induced by MI is strongest in the γ-band, i.e., above 35 Hz. Furthermore, modulation beten MI and rest is found to be more pronounced than beten MI of different hands. This is in contrast to results on MI obtained with bandpor features, and might provide an explanation for the so far only moderate success of connectivity features in BCIs. It is concluded that future studies on connectivity based BCIs should focus on high frequency bands and consider experimental paradigms that maximally vary cognitive demands beten conditions.
['Moritz Grosse-Wentrup']
I am writing a research paper on a idea Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer Interfacing
[{"from": "human", "value": "I am writing a research paper on a idea Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer Interfacing"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: EEG connectivity measures could provide a new type of feature space for inferring a subject's intention in Brain-Computer Interfaces (BCIs). Hover, very little is known on EEG connectivity patterns for BCIs. In this study, EEG connectivity during motor imagery (MI) of the left and right is investigated in a broad frequency range across the whole scalp by combining Beamforming with Transfer Entropy and taking into account possible volume conduction effects. Observed connectivity patterns indicate that modulation intentionally induced by MI is strongest in the \u03b3-band, i.e., above 35 Hz. Furthermore, modulation beten MI and rest is found to be more pronounced than beten MI of different hands. This is in contrast to results on MI obtained with bandpor features, and might provide an explanation for the so far only moderate success of connectivity features in BCIs. It is concluded that future studies on connectivity based BCIs should focus on high frequency bands and consider experimental paradigms that maximally vary cognitive demands beten conditions."}]