LUO Sen-lin, LI Li, ZHANG Xin-li, ZHANG Tie-mei. Time Slice Analysis Method Based on OTCA Used in fMRI Weak Signal Function Extraction[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2007, 16(4): 443-447.
Citation:
LUO Sen-lin, LI Li, ZHANG Xin-li, ZHANG Tie-mei. Time Slice Analysis Method Based on OTCA Used in fMRI Weak Signal Function Extraction[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2007, 16(4): 443-447.
LUO Sen-lin, LI Li, ZHANG Xin-li, ZHANG Tie-mei. Time Slice Analysis Method Based on OTCA Used in fMRI Weak Signal Function Extraction[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2007, 16(4): 443-447.
Citation:
LUO Sen-lin, LI Li, ZHANG Xin-li, ZHANG Tie-mei. Time Slice Analysis Method Based on OTCA Used in fMRI Weak Signal Function Extraction[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2007, 16(4): 443-447.
The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity is exposed in processing brain activation signal which is relatively weak. The time slice analysis method based on OTCA is proposed considering the weakness of the functional magnetic resonance imaging (fMRI) signal of the rat model. By dividing the stimulation period into several time slices and analyzing each slice to detect the activated pixels respectively after the background removal, the sensitivity is significantly improved. The inhibitory response in the hypothalamus after glucose loading is detected successfully with this method in the experiment on rat. Combined with the OTCA method, the time slice analysis method based on OTCA is effective on detecting when, where and which type of response will happen after stimulation, even if the fMRI signal is weak.
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