9 March 2011 Real-time fMRI data analysis using region of interest selection based on fast ICA
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Proceedings Volume 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging; 79651S (2011); doi: 10.1117/12.877141
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States
Abstract
Real-time functional magnetic resonance imaging (rtfMRI) is a new technique which can present (feedback) brain activity during scanning. Through fast acquisition and online analysis of BOLD signal, fMRI data are processed within one TR. Current rtfMRI provides an activation map under specific task mainly through the GLM analysis to select region of interest (ROI). This study was based on independent component analysis (ICA) and used the result of fast ICA analysis to select the node of the functional network as the ROI. Real-time brain activity within the ROI was presented to the subject who needed to find strategies to control his brain activity. The whole real-time processes involved three parts: pre-processing (including head motion correction and smoothing), fast ICA analysis and feedback. In addition, the result of fast head motion correction was also presented to the experimenter in a curve diagram. Based on the above analysis processes, a real time feedback experiment with a motor imagery task was performed. An overt finger movement task as localizer session was adopted for ICA analysis to get the motor network. Supplementary motor area (SMA) in such network was selected as the ROI. During the feedback session, the average of BOLD signals within ROI was presented to the subjects for self-regulation under a motor imagery task. In this experiment, TR was 1.5 seconds, and the whole time of processing and presentation was within 1 second. Experimental results not only showed that the SMA was controllable, but also proved that the analysis method was effective.
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Baoquan Xie, Xinyue Ma, Li Yao, Zhiying Long, Xiaojie Zhao, "Real-time fMRI data analysis using region of interest selection based on fast ICA", Proc. SPIE 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging, 79651S (9 March 2011); doi: 10.1117/12.877141; https://doi.org/10.1117/12.877141
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KEYWORDS
Independent component analysis

Brain

Functional magnetic resonance imaging

Head

Data acquisition

Data analysis

Shape memory alloys

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