Nature image identification and voxels activity modeling using fMRI encoding model

In may 2016. I tried to repeat a pioneering research published on NATURE (Kay et al., 2008) using a data-driven Voxel-Wise Model (Naselaris et al., 2011). I successfully constructed a liner receptive field model for every voxels using the Gabor wavelet filter according to the encoding theory of the primary visual cortex (Hubel and Wiesel, 1968). Without noise ceiling procedures, I also got remarkable accuracy in the identification task (about 48.8%, meanwhile the chance level is about 0.8%). My code is now open sccess on Github - Voxels-activity-modeling-using-fMRI-data.     Read more
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Jingjie Li Jun 14, 2016

Visual Image Reconstruction using fMRI

Mind-reading is an exciting topic. Modern fMRI(functional magnetic resonance imaging) technique are making mind-reading coming true. Using fMRI combine with modern machine learning algrithoms(MVPA), we can now decode some infomation from people’s brain activities. I repeated some previous prominence research about that topic in Badong Chen’s lab, such like fMRI signal decoding from primary visual cortex (V1) and reconstructing pattern image from fMRI signal (Miyawaki et al., 2008). Moreover, I improved the accuracy of the reconstruction by ~ 4% (from about 80% to about 84%), using the improved MVPA method with SVM classifier (Norman et al., 2006).     Read more
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Jingjie Li Mar 10, 2016