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Updated: Jan 23, 2026

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG
Published on: March 10, 2017
On the relevance of EEG resting theta activity for the neurophysiological dynamics underlying motor inhibitory
Charlotte Pscherer1, Moritz Mückschel1, Lena Summerer1
1Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Dresden, Germany.
Abstract:
The modulation of theta frequency activity plays a major role in inhibitory control processes. However, the relevance of resting theta band activity and of the ability to spontaneously modulate this resting theta activity for neural mechanisms underlying inhibitory control is elusive. Various theoretical conceptions suggest to take these aspects into consideration. In the current study, we examine whether the strength of resting theta band activity or the ability to modulate the resting state theta activity affects response inhibition. We combined EEG-time frequency decomposition and beamforming in a conflict-modulated Go/Nogo task. A sample of N = 66 healthy subjects was investigated. We show that the strength of resting state theta activity modulates the effects of conflicts during motor inhibitory control. Especially when resting theta activity was low, conflicts strongly affected response inhibition performance and total theta band activity during Nogo trials. These effects were associated with theta-related activity differences in the superior (BA7) and inferior parietal cortex (BA40). The results were very specific for total theta band activity since evoked theta activity and measures of intertrial phase coherency (phase-locking factor) were not affected. The data suggest that the strength of resting state theta activity modulates processing of a theta-related alarm or surprise signal during inhibitory control. The ability to voluntarily modulate theta band activity did not affect conflict-modulated inhibitory control. These findings have important implications for approaches aiming to optimize human cognitive control.
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