Spatio-temporal patterns of ERP-based on combined ICA-LORETA analysis

Jiacai Zhang; Taomei Guo; Yaqin Xu; Xiaojie Zhao; Li Yao

doi:10.1117/12.706229

29 March 2007 Spatiotemporal patterns of ERP based on combined ICA-LORETA analysis

Jiacai Zhang, Taomei Guo, Yaqin Xu, Xiaojie Zhao, Li Yao

Proceedings Volume 6511, Medical Imaging 2007: Physiology, Function, and Structure from Medical Images; 651120 (2007) https://doi.org/10.1117/12.706229
Event: Medical Imaging, 2007, San Diego, CA, United States

Abstract

In contrast to the FMRI methods widely used up to now, this method try to understand more profoundly how the brain systems work under sentence processing task map accurately the spatiotemporal patterns of activity of the large neuronal populations in the human brain from the analysis of ERP data recorded on the brain scalp. In this study, an event-related brain potential (ERP) paradigm to record the on-line responses to the processing of sentences is chosen as an example. In order to give attention to both utilizing the ERPs' temporal resolution of milliseconds and overcoming the insensibility of cerebral location ERP sources, we separate these sources in space and time based on a combined method of independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. ICA blindly separate the input ERP data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. And then the spatial maps associated with each ICA component are analyzed, with use of LORETA to uniquely locate its cerebral sources throughout the full brain according to the assumption that neighboring neurons are simultaneously and synchronously activated. Our results show that the cerebral computation mechanism underlies content words reading is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, and activate at distinct time intervals and are grouped into different statistically independent components. Thus ICA-LORETA analysis provides an encouraging and effective method to study brain dynamics from ERP.

Citation Download Citation

Jiacai Zhang, Taomei Guo, Yaqin Xu, Xiaojie Zhao, and Li Yao "Spatiotemporal patterns of ERP based on combined ICA-LORETA analysis", Proc. SPIE 6511, Medical Imaging 2007: Physiology, Function, and Structure from Medical Images, 651120 (29 March 2007); https://doi.org/10.1117/12.706229

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available