IEEE Transactions on Neural Systems and Rehabilitation EngineeringNeurosciencePeer-reviewed journal article
Brain Dynamics of Spatial Reference Frame Proclivity in Active Navigation
Che-Sheng Yang, Jia LiuiD, Avinash Kumar SinghiD, Kuan‐Chih HuangiD, Chin‐Teng LiniD
Abstract
Recent research into navigation strategy of different spatial reference frame proclivities (RFPs) has revealed that the parietal cortex plays an important role in processing allocentric information to provide a translation function between egocentric and allocentric spatial reference frames. However, most studies merely focused on a passive experimental environment, which is not truly representative of our daily spatial learning/navigation tasks. This study investigated the factor associated with brain dynamics that causes people to switch their preferred spatial strategy in different environments in virtual reality (VR) based active navigation task to bridge the gap. High-resolution electroencephalography (EEG) signals were recorded to monitor spectral perturbations on transitions between egocentric and allocentric frames during a path integration task. Our brain dynamics results showed navigation involved areas including the parietal cortex with modulation in the alpha band, the occipital cortex with beta and low gamma band perturbations, and the frontal cortex with theta perturbation. Differences were found between two different turning-angle paths in the alpha band in parietal cluster event-related spectral perturbations (ERSPs). In small turning-angle paths, allocentric participants showed stronger alpha desynchronization than egocentric participants; in large turning-angle paths, participants for two reference frames had a smaller difference in the alpha frequency band. Behavior results of homing errors also corresponded to brain dynamic results, indicating that a larger angle path caused the allocentric to have a higher tendency to become egocentric navigators in the active navigation environment.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 9
- FWCI
- 0.24
- Field percentile
- top 49%
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