DocumentCode :
45663
Title :
An Innovative Strategy for Correctly Interpreting Simultaneous Acquisition of EEG Signals and FMRI Images
Author :
Fabbiano, L. ; Vacca, G. ; Morello, R. ; De Capua, C.
Author_Institution :
Dept. of Mech., Math. & Manage., Politec. di Bari, Bari, Italy
Volume :
13
Issue :
9
fYear :
2013
fDate :
Sept. 2013
Firstpage :
3175
Lastpage :
3181
Abstract :
Cognitive event-related measurements of the human brain are performed by measuring electrical signals and electromagnetic fields (electroencephalography, EEG, and magnetoencephalography, MEG) and hemodynamic responses (measured by fMRI and PET). The EEG and MEG reflect synchronized electrical activity of neurons, and then show the same timescale as neurocognitive processes. The fMRI is related to the power consumption of groups of neurons and registers a signal on a timescale of several seconds. Unlike fMRI, MEG and EEG are not imaging methods. It is our opinion that the combination of MEG or EEG with the fMRI therefore would be very useful to reach a high resolution, both in time and space, of brain functions. It is not assured however that all measured events during an EEG acquisition and cognitive process-related produce measurable changes of the BOLD signal-and vice versa. In this paper, a new strategy of combining signals (electric and hemodynamic responses) simultaneously acquired from different clinical methodologies is performed and tested in order to produce more reliable information about brain activity. Two different algorithms are explored and compared via repeatability standard deviation estimations of fMRI images.
Keywords :
biomedical MRI; brain; cognition; electroencephalography; haemodynamics; magnetoencephalography; medical image processing; neurophysiology; positron emission tomography; power consumption; BOLD signal; EEG signal; FMRI image; MEG; PET; cognitive event-related measurement; electrical signals; electroencephalography; electromagnetic fields; hemodynamics; human brain; magnetoencephalography; neurocognitive process; power consumption; repeatability standard deviation estimation; Biomedical measurements; ICA algorithms; image processing; neuroelectric signals;
fLanguage :
English
Journal_Title :
Sensors Journal, IEEE
Publisher :
ieee
ISSN :
1530-437X
Type :
jour
DOI :
10.1109/JSEN.2013.2261294
Filename :
6512589
Link To Document :
بازگشت