Abstract
Current electroencephalography (EEG) Brain-Computer Interface (BCI) methods typically use control signals (P300, modulated slow cortical potentials, mu or beta rhythm) that suffer from a slow time scale, low signal to noise ratio, and/or low spatial resolution. High gamma oscillations (70–150 Hz; HG) are rapidly evolving, spatially localized signals and recent studies have shown that EEG can reliably detect task-related HG power changes. In this chapter, we discuss how we capitalize on EEG resolved HG as a control signal for BCI. We use functional magnetic resonance imaging (fMRI) to impose spatial constraints in an effort to improve the signal to noise ratio across the HG band. The overall combination lends itself to a fast-responding, dynamic BCI.
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Smith, M., Weaver, K., Grabowski, T., Darvas, F. (2013). Utilizing High Gamma (HG) Band Power Changes as a Control Signal for Non-Invasive BCI. In: Guger, C., Allison, B., Edlinger, G. (eds) Brain-Computer Interface Research. SpringerBriefs in Electrical and Computer Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36083-1_9
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DOI: https://doi.org/10.1007/978-3-642-36083-1_9
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