High-gamma EEG

Affiliated researchers: PD Dr. Tonio Ball, Dr Lukas Fiederer, Martin Glasstetter

High-gamma band (HGB) activity in the human brain is often linked to higher cognitive functions and memory. It has also been shown that HGB power is phase-locked to theta band (4-8 Hz) oscillations, indicating that this cross-frequency coupling coordinates functional cortical activity and could be a communication mechanism for cognitive processing. Furthermore, HGB activity seems to be linked to spatial attention and the generation of the in fMRI measured BOLD signal. Thus, it is highly interesting for neuroscientists to uncover task-dependent HBG activity, as this information could help in the understanding of higher brain functions.

However, it is not easy to detect gamma band power modulations in EEG, as the power measured in EEG is inversely proportional to frequency. As a consequence, high-frequency, low-amplitude signals are often masked by broadband artifacts.

To tackle these issues, our EEG lab and measurement procedure is optimized to detect even subtle gamma oscillations with a low signal-to-noise ratio: The recording is done within an electromagnetically shielded EEG cabin with a high sampling rate of 5000 Hz. Furthermore, all subjects are monitored with a high-resolution eye tracker to detect and examine blinks, saccades and microsaccades.

Movement-related HGB activity in EEG and ECoG (Ball et al., 2008). The colorbars show the relative power. A) Movement-related spectral power changes in EEG, channel C3 (group median across 8 subjects). B) Movement-related spectral power changes in ECoG motor cortex channels (mean across 20 channels of 2 patients).

Related Publications 

• Multiple manuscripts under preparation
• Völker, M., Fiederer L.D.J., Berberich S., Hammer J., Behncke J., Kršek, P., Tomášek M., Marusič P., Reinacher P.C., Coenen V.A., Helias M., Schulze-Bonhage A., Burgard W., and Ball T. "The dynamics of error processing in the human brain as reflected by high-gamma activity in noninvasive and intracranial EEG". NeuroImage, 2018. doi.org/10.1016/j.neuroimage.2018.01.059
• Hartmann K.G., Schirrmeister R. T., and Ball T., "Hierarchical internal representation of spectral features in deep convolutional networks trained for EEG decoding". IEEE The 6th International Winter Conference on Brain-Computer Interface 2018. doi.org/10.1109/IWW-BCI.2018.8311493
• Schirrmeister R.T., Springenberg J.T., Fiederer L.D.J., Glasstetter M., Eggensperger K., Tangermann M., Hutter F., Burgard W., Ball T. Deep learning with convolutional neural networks for EEG decoding and visualization. Hum Brain Mapp. 2017 Aug 7. https://doi.org/10.1002/hbm.23730
• Ball, Tonio, Evariste Demandt, Isabella Mutschler, Eva Neitzel, Carsten Mehring, Klaus Vogt, Ad Aertsen, and Andreas Schulze-Bonhage. ‘Movement Related Activity in the High Gamma Range of the Human EEG’. NeuroImage 41, no. 2 (June 2008): 302–10. doi:10.1016/j.neuroimage.2008.02.032.