2011
DOI: 10.1038/nmeth.1635
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Large-scale automated synthesis of human functional neuroimaging data

Abstract: The explosive growth of the human neuroimaging literature has led to major advances in understanding of human brain function, but has also made aggregation and synthesis of neuroimaging findings increasingly difficult. Here we describe and validate an automated brain mapping framework that uses text mining, meta-analysis and machine learning techniques to generate a large database of mappings between neural and cognitive states. We demonstrate the capacity of our approach to automatically conduct large-scale, … Show more

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Cited by 3,046 publications
(3,405 citation statements)
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References 45 publications
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“…NeuroSynth is an automated meta‐analytic tool that generates activation maps (based on peak coordinates reported within neuroimaging articles) for certain psychological terms or constructs from a database of 5,809 studies (data retrieved 20/05/14). We used a reverse inference analysis in which the voxel‐wise Z statistic reflects the likelihood that a particular term was used given an activation at that voxel location (a full description of this method can be found in Yarkoni et al, 2011). …”
Section: Resultsmentioning
confidence: 99%
“…NeuroSynth is an automated meta‐analytic tool that generates activation maps (based on peak coordinates reported within neuroimaging articles) for certain psychological terms or constructs from a database of 5,809 studies (data retrieved 20/05/14). We used a reverse inference analysis in which the voxel‐wise Z statistic reflects the likelihood that a particular term was used given an activation at that voxel location (a full description of this method can be found in Yarkoni et al, 2011). …”
Section: Resultsmentioning
confidence: 99%
“…The TPJ has been implicated in domain-general processes beyond mentalizing, including attention (Decety and Lamm, 2007;Mitchell, 2008); however, previous studies have indicated that the region's roles in attention and mentalizing are spatially separable (Scholz et al, 2009;Carter and Huettel, 2013). Thus, we used the meta-analytic database Neurosynth (Yarkoni et al, 2011;www.neurosynth.org) to examine the peak TPJ coordinates from both the Story and Cue Window. Both clusters had a strong association with meta-analytic maps of 'mentalizing' (Story Window: z ¼ 4.54, posterior probability ¼ 0.82; Cue Window: z ¼ 4.76, posterior probability ¼ 0.83), but not with maps for 'attention', 'selective attention' or 'attentional control' (z ¼ 0 for all terms for both clusters).…”
Section: Neuroimaging Resultsmentioning
confidence: 99%
“…In order to aid the interpretation of the whole-brain voxel-wise analysis, we applied a novel method to 'decode' significant clusters using Neurosynth (Yarkoni et al, 2011). This method essentially correlates an input image with reverse inference maps related to a topic (ie, a map of the probability per voxel of being active given a certain topic, cf.…”
Section: Resultsmentioning
confidence: 99%