Difference between revisions of "Topic Mapping"
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| − | + | <h3>Poldrack, et al, 2012. Discovering relations between mind, brain, and mental disorders using topic mapping, PLOS Comp Bio 8(10)</h3> | |
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| + | PMID 23071428<br> | ||
| + | Freds presentations slides are here: [[JC_Dec11]] | ||
| + | |||
| + | '''Abstract''' | ||
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| + | Neuroimaging research has largely focused on the identification of associations between brain activation and specific mental functions. Here we show that data mining techniques applied to a large database of neuroimaging results can be used to identify the conceptual structure of mental functions and their mapping to brain systems. This analysis confirms many current ideas regarding the neural organization of cognition, but also provides some new insights into the roles of particular brain systems in mental function. We further show that the same methods can be used to identify the relations between mental disorders. Finally, we show that these two approaches can be combined to empirically identify novel relations between mental disorders and mental functions via their common involvement of particular brain networks. This approach has the potential to discover novel endophenotypes for neuropsychiatric disorders and to better characterize the structure of these disorders and the relations between them. | ||
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| + | '''Methods''' | ||
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| + | [http://mallet.cs.umass.edu/ MALLET] - UMass Machine Learning for Language Toolkit | ||
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| + | [http://cognitiveatlas.org Cognitive Atlas] - Poldrack Cognitive Atlas | ||
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| + | [http://bioportal.bioontology.org/ontologies/NIFSTD/?p=summary NIFSTD] - Neuroimaging Information Framework Standard Ontology | ||
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| + | '''Results''' | ||
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| + | ''Figure1'' | ||
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| + | Description of Processing Pipeline: | ||
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| + | 'Figure2'' | ||
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| + | Plots of the average empirical likelihood of the left-out document sets across cross validation folds, for cognitive terms (left) and disorder terms (right). | ||
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| + | 'Figure3'' | ||
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| + | Histograms of the number of topics per document (top row) and documents per topic (bottom row) for cognitive terms (left column) and disorder terms (right column). | ||
Latest revision as of 16:33, 4 December 2013
Poldrack, et al, 2012. Discovering relations between mind, brain, and mental disorders using topic mapping, PLOS Comp Bio 8(10)
PMID 23071428
Freds presentations slides are here: JC_Dec11
Abstract
Neuroimaging research has largely focused on the identification of associations between brain activation and specific mental functions. Here we show that data mining techniques applied to a large database of neuroimaging results can be used to identify the conceptual structure of mental functions and their mapping to brain systems. This analysis confirms many current ideas regarding the neural organization of cognition, but also provides some new insights into the roles of particular brain systems in mental function. We further show that the same methods can be used to identify the relations between mental disorders. Finally, we show that these two approaches can be combined to empirically identify novel relations between mental disorders and mental functions via their common involvement of particular brain networks. This approach has the potential to discover novel endophenotypes for neuropsychiatric disorders and to better characterize the structure of these disorders and the relations between them.
Methods
MALLET - UMass Machine Learning for Language Toolkit
Cognitive Atlas - Poldrack Cognitive Atlas
NIFSTD - Neuroimaging Information Framework Standard Ontology
Results
Figure1
Description of Processing Pipeline:
'Figure2
Plots of the average empirical likelihood of the left-out document sets across cross validation folds, for cognitive terms (left) and disorder terms (right).
'Figure3
Histograms of the number of topics per document (top row) and documents per topic (bottom row) for cognitive terms (left column) and disorder terms (right column).
