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Analysis of fMRI time series is often performed by extracting one or more parameters for the individual voxels. Methods based, e.g., on various statistical tests are then used to yield parameters corresponding to probability of activation or activation strength. However, these methods do not indicate whether sets of voxels are activated in a similar way or(More)
Sentiment analysis of microblogs such as Twitter has recently gained a fair amount of attention. One of the simplest sentiment analysis approaches compares the words of a posting against a labeled word list, where each word has been scored for valence, — a " sentiment lexicon " or " affective word lists ". There exist several affective word lists, e.g.,(More)
We apply nine analytic methods employed currently in imaging neuroscience to simulated and actual BOLD fMRI signals and compare their performances under each signal type. Starting with baseline time series generated by a resting subject during a null hypothesis study, we compare method performance with embedded focal activity in these series of three(More)
Generalization can be defined quantitatively and can be used to assess the performance of principal component analysis (PCA). The generalizability of PCA depends on the number of principal components retained in the analysis. We provide analytic and test set estimates of generalization. We show how the generalization error can be used to select the number(More)
Introduction Automatic translation of Talairach coordinates to anatomical labels is, e.g., implemented in the Talairach Daemon [1] that is based on a digitization of the Talairach Atlas [2] and probabilistic atlases [3]. Here we describe a bootstraped method based on labels in the literature as recorded in the BrainMap database [4], This method allows us to(More)
Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel-time series. The optimal number of clusters was chosen using a(More)
We present a general method for automatic meta-analyses in neuroscience and apply it on text data from published functional imaging studies to extract main functions associated with a brain area-the posterior cingulate cortex (PCC). Abstracts from PubMed are downloaded, words extracted and converted to a bag-of-words matrix representation. The combined data(More)
The web has greatly improved the accessibility of scientific information, however the role of the web in formal scientific publishing has been debated. Some argue that the lack of persistence of web resources means that they should not be cited in scientific research. We analyze references to web resources in computer science publications, finding that the(More)
We describe a system for meta-analytical modeling of activation foci from functional neuroimaging studies. Our main vehicle is a set of density models in Talairach space capturing the distribution of activation foci in sets of experiments labeled by lobar anatomy. One important use of such density models is identification of novelty, i.e., low probability(More)