NDLI: EEG-Based Spatial Navigation Estimation in a Virtual Reality Driving Environment

Content Provider	IEEE Xplore Digital Library
Author	Chin-Teng Lin Fu-Shu Yang Te-Chung Chiou Li-Wei Ko Jeng-Ren Duann Gramann, K.
Copyright Year	2009
Abstract	Abstract—The aim of this study is to investigate the difference of EEG dynamics on navigation performance. A tunnel task was designed to classify subjects into allocentric or egocentric spatial representation users. Despite of the differences of mental spatial representation, behavioral performance in general were compatible between the two strategies subjects in the tunnel task. Task-related EEG dynamics in power changes were analyzed using independent component analysis (ICA), time-frequency and non-parametric statistic test. ERSP image results revealed navigation performance-predictive EEG activities which is is expressed in the parietal component by source reconstruction. For egocentric subjects, comparing to trails with well-estimation of homing angle, the power attenuation at the frequencies from 8 to 30 Hz (around alpha and beta band) was stronger when subjects overestimated homing directions, but the attenuated power was decreased when subjects were underestimated the homing angles. However, we did not found performance related brain activities for allocentric subjects, which may due to the functional dis-sociation between the use of allo- and egocentric reference frames.
Starting Page	435
Ending Page	438
File Size	231875
Page Count	4
File Format	PDF
ISBN	9780769536569
DOI	10.1109/BIBE.2009.65
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-22
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Navigation Virtual reality Electroencephalography Independent component analysis Time frequency analysis Statistical analysis Testing Image reconstruction Attenuation Brain electroencephalograph (EEG) spatial navigation allocentric egocentric reference frame
Content Type	Text
Resource Type	Article

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