Voxelwise Bayesian lesion-deficit analysis Export

@article{citeulike:2837790, abstract = {Relating cognitive deficits to the presence of lesions has been an important means of delineating structure-function associations in the human brain. We propose a voxel-based Bayesian method for lesion-deficit analysis, which identifies complex linear or nonlinear associations among brain-lesion locations, and neurological status. We validated this method using a simulated data set, and we applied this algorithm to data obtained from an acute-stroke study to identify associations among voxels with infarct or hypoperfusion, and impaired word reading. We found that a distributed region involving Brodmann areas (BA) 22, 37, 39, and 40 was implicated in word reading.}, author = {Chen, Rong and Hillis, Argye E. and Pawlak, Mikolaj and Herskovits, Edward H.}, citeulike-article-id = {2837790}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.neuroimage.2008.01.014}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6WNP-4RP0MKX-6/1/0247983261c51c59a5574f75f1bcdee1}, day = {1}, doi = {10.1016/j.neuroimage.2008.01.014}, journal = {NeuroImage}, keywords = {jc-neuroimage}, month = {May}, number = {4}, pages = {1633--1642}, posted-at = {2008-05-27 16:19:51}, priority = {2}, title = {Voxelwise Bayesian lesion-deficit analysis}, url = {http://dx.doi.org/10.1016/j.neuroimage.2008.01.014}, volume = {40}, year = {2008} }

TY - JOUR ID - citeulike:2837790 L3 - citeulike-article-id:2837790 N2 - Relating cognitive deficits to the presence of lesions has been an important means of delineating structure-function associations in the human brain. We propose a voxel-based Bayesian method for lesion-deficit analysis, which identifies complex linear or nonlinear associations among brain-lesion locations, and neurological status. We validated this method using a simulated data set, and we applied this algorithm to data obtained from an acute-stroke study to identify associations among voxels with infarct or hypoperfusion, and impaired word reading. We found that a distributed region involving Brodmann areas (BA) 22, 37, 39, and 40 was implicated in word reading. IS - 4 JF - NeuroImage EP - 1642 TI - Voxelwise Bayesian lesion-deficit analysis VL - 40 SP - 1633 KW - jc-neuroimage AU - Chen, Rong AU - Hillis, Argye AU - Pawlak, Mikolaj AU - Herskovits, Edward PY - 2008/05/01/ UR - http://dx.doi.org/10.1016/j.neuroimage.2008.01.014 ER -