Difference between revisions of "Topic Mapping"
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'''Abstract''' | '''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. | 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''' | '''Methods''' | ||
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MALLET | MALLET | ||
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Cognitive Atlas | Cognitive Atlas | ||
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| + | [NIFSTD http://bioportal.bioontology.org/ontologies/NIFSTD/?p=summary] - Neuroimaging Information Framework Standard Ontology | ||
'''Results''' | '''Results''' | ||
''Figure1'' | ''Figure1'' | ||
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| + | Description of Processing Pipeline: | ||
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| + | 'Figure2'' | ||
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| + | Description of Processing Pipeline: | ||
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| + | 'Figure3'' | ||
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| + | Description of Processing Pipeline: | ||
Revision as of 15:31, 4 December 2013
Poldrack, et al, 2012. Discovering relations between mind, brain, and mental disorders using topic mapping, PLOS Comp Bio 8(10)
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
Cognitive Atlas
[NIFSTD http://bioportal.bioontology.org/ontologies/NIFSTD/?p=summary] - Neuroimaging Information Framework Standard Ontology
Results
Figure1
Description of Processing Pipeline:
'Figure2
Description of Processing Pipeline:
'Figure3
Description of Processing Pipeline:
