DocumentCode :
1789546
Title :
Alpha and beta band power changes predict reaction time and endpoint error during planning reaching movements
Author :
Lingling Yang ; Leung, Henry ; Plank, Markus ; Snider, Joseph ; Poizner, Howard
Author_Institution :
Dept. of Comput. Sci., City Univ. of Hong Kong, Hong Kong, China
fYear :
2014
fDate :
14-16 Oct. 2014
Firstpage :
264
Lastpage :
268
Abstract :
Reaching is one of the fundamental tasks in daily life thus the neural processing of such a task will benefit brain computer interface (BCI) development. Even the simplest reaching task results from a movement planning phase as well as a movement execution phase. To facilitate the neural decoding of human reaching, brain activity in both movement planning and execution phases should be investigated. Many related studies focused on the correlation between movement kinematics and brain activity during movement execution or imagery. In this paper, we studied whether particular reaching parameters were encoded in the brain activity recorded by high-density EEG during the movement planning phase. Alpha and beta power over ten brain regions during the movement planning phase were correlated with reaction time/endpoint error during execution. The planning phase was divided into 2 movement planning intervals: 1) [0 250]ms and 2) [250 500]ms, with respect to the target onset to study the temporal characteristics of the power changes. Our results show that the greater the increase of the alpha band power in the left frontal region and the smaller the decrease of the beta band power in the right frontal region in the movement planning interval 2, the longer is the reaction time. A decrease of the beta band power in the motor and frontal regions from the two planning intervals correspond to a higher endpoint error. Moreover, higher alpha band power in the movement planning interval 2 over left parietal regions was related to smaller endpoint errors.
Keywords :
biomechanics; brain-computer interfaces; electroencephalography; kinematics; medical signal processing; neurophysiology; BCI development; beta band power; brain activity; brain computer interface development; brain regions; endpoint error; high alpha band power; high endpoint error; high-density EEG; left frontal region; motor-frontal regions; movement execution phase; movement kinematics; movement planning intervals; movement planning phase; neural decoding; neural processing; planning intervals; planning reaching movements; reaction time; temporal characteristics; Brain; Correlation; Decoding; Electrodes; Electroencephalography; Planning; Scalp; EEG; alpha and beta band powers; endpoint error; movement planning; reaction time;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2014 7th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4799-5837-5
Type :
conf
DOI :
10.1109/BMEI.2014.7002782
Filename :
7002782
Link To Document :
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