Power dynamics of theta oscillations during goal-directed navigation in freely moving humans: A mobile EEG-virtual reality T-maze study
Lin, M.-h.; Liran, O.; Bauer, N. K.; Baker, T. E.
Show abstract
Theta oscillations ([~]4-12 Hz) are dynamically modulated by speed and direction in freely moving animals. However, due to the paucity of electrophysiological recordings of freely moving humans, this mechanism remains poorly understood. Here, we combined mobile-EEG with fully immersive virtual-reality to investigate theta dynamics in twenty-two healthy adults (aged 18-29 years old) freely navigating a T-maze to find rewards. Our results revealed three dynamic periods of theta modulation: 1) theta power increases coincided with the participants decision-making period; 2) theta power increased for fast and leftward trials as subjects approached the goal location; and 3) feedback onset evoked two phase-locked theta bursts over the right temporal and frontal-midline channels. These results suggest that recording scalp EEG in freely moving humans navigating a simple virtual T-maze can be utilized as a powerful translational model by which to map theta dynamics during "real-life" goal-directed behavior in both health and disease.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Mobile EEG reveals functionally dissociable dynamic processes supporting real-world ambulatory obstacle avoidance: Evidence for early proactive control 95%
- Mobile brain/body imaging of landmark-based navigation with high-density EEG 95%
- Stability of Neural Oscillations Supports Auditory-Motor Synchronization 93%
Similar papers in this journal
- Disentangling the Functional Roles of Pre-Stimulus Oscillations in Crossmodal Associative Memory Formation via Sensory Entrainment 94%
- Periodic attention operates faster during more complex visual search 94%
- Predicting the subjective intensity of imagined sensory experiences from electrophysiological measures of oscillatory brain activity. 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.