Optimization and development of concurrent EEG-fMRI data acquisition setup for understanding neural mechanisms of brain
Electroencephalography (EEG) and functional magnetic resonance (fMRI) both are considered as non-invasive neuroimaging modalities. Both are used for understanding brain functionalities in cognitive neuroscience as well as in clinical applications. EEG gives high temporal resolution and it has poor s...
| Main Authors: | Ahmad, R.F., Malik, A.S., Kamel, N., Reza, F., Abdul Karim, A.H. |
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| Format: | Conference or Workshop Item |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.26288 / |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2015
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938847068&doi=10.1109%2fI2MTC.2015.7151314&partnerID=40&md5=32fb61fefbecd6e5f7518e784f106e14 http://eprints.utp.edu.my/26288/ |
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| Summary: |
Electroencephalography (EEG) and functional magnetic resonance (fMRI) both are considered as non-invasive neuroimaging modalities. Both are used for understanding brain functionalities in cognitive neuroscience as well as in clinical applications. EEG gives high temporal resolution and it has poor spatial resolution. On the other hand, fMRI has very high spatial resolution and poor temporal resolution. For deep understanding of neural mechanisms inside human brain, it is desirable to get the higher spatiotemporal resolution of human brain at the same time. Concurrent EEG-fMRI data recording solve the problem of higher spatiotemporal resolution. It can be also helpful to understand the neural mechanism inside human brain effectively. The concurrent EEG-fMRI recording requires MRI compatible EEG equipment which can be placed inside the higher magnetic field of MRI scanner and also synchronization is required to make setup concurrent. To get higher signal to noise ratio (SNR), optimization of data acquisition parameters plays a significant role. In this paper, we discussed the some real issues during data acquisition and their optimization. We have developed the concurrent EEG-fMRI setup and also successfully recorded the EEG-fMRI data concurrently by optimizing the data acquisition parameters involved. Artifacts have been removed from the data and further, data fusion framework is proposed for combine analysis of EEG and fMRI data. © 2015 IEEE. |
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