Visual Image Reconstruction from Human Brain Activity using a Combination of Multiscale Local Image Decoders Export

@article{citeulike:4180806, abstract = {Perceptual experience consists of an enormous number of possible states. Previous fMRI studies have predicted a perceptual state by classifying brain activity into prespecified categories. Constraint-free visual image reconstruction is more challenging, as it is impractical to specify brain activity for all possible images. In this study, we reconstructed visual images by combining local image bases of multiple scales, whose contrasts were independently decoded from fMRI activity by automatically selecting relevant voxels and exploiting their correlated patterns. Binary-contrast, 10 × 10-patch images (2100 possible states) were accurately reconstructed without any image prior on a single trial or volume basis by measuring brain activity only for several hundred random images. Reconstruction was also used to identify the presented image among millions of candidates. The results suggest that our approach provides an effective means to read out complex perceptual states from brain activity while discovering information representation in multivoxel patterns.}, author = {Miyawaki, Yoichi and Uchida, Hajime and Yamashita, Okito and Sato, Masa-aki and Morito, Yusuke and Tanabe, Hiroki C. and Sadato, Norihiro and Kamitani, Yukiyasu}, citeulike-article-id = {4180806}, citeulike-linkout-0 = {http://www.cell.com/neuron/abstract/S0896-6273(08)00958-6}, day = {10}, keywords = {decoding, fmri}, month = {December}, number = {5}, pages = {915--929}, posted-at = {2009-04-06 10:41:09}, priority = {2}, title = {Visual Image Reconstruction from Human Brain Activity using a Combination of Multiscale Local Image Decoders}, url = {http://www.cell.com/neuron/abstract/S0896-6273(08)00958-6}, volume = {60}, year = {2008} }

TY - JOUR ID - citeulike:4180806 L3 - citeulike-article-id:4180806 N2 - Perceptual experience consists of an enormous number of possible states. Previous fMRI studies have predicted a perceptual state by classifying brain activity into prespecified categories. Constraint-free visual image reconstruction is more challenging, as it is impractical to specify brain activity for all possible images. In this study, we reconstructed visual images by combining local image bases of multiple scales, whose contrasts were independently decoded from fMRI activity by automatically selecting relevant voxels and exploiting their correlated patterns. Binary-contrast, 10 × 10-patch images (2100 possible states) were accurately reconstructed without any image prior on a single trial or volume basis by measuring brain activity only for several hundred random images. Reconstruction was also used to identify the presented image among millions of candidates. The results suggest that our approach provides an effective means to read out complex perceptual states from brain activity while discovering information representation in multivoxel patterns. IS - 5 EP - 929 TI - Visual Image Reconstruction from Human Brain Activity using a Combination of Multiscale Local Image Decoders VL - 60 SP - 915 KW - decoding KW - fmri AU - Miyawaki, Yoichi AU - Uchida, Hajime AU - Yamashita, Okito AU - Sato, Masa-aki AU - Morito, Yusuke AU - Tanabe, Hiroki AU - Sadato, Norihiro AU - Kamitani, Yukiyasu PY - 2008/12/10/ UR - http://www.cell.com/neuron/abstract/S0896-6273(08)00958-6 ER -