Application of neuroanatomical ontologies for neuroimaging data annotation
The annotation of functional neuroimaging results for data sharing and reuse is particularly challenging, due to the diversity of terminologies of neuroanatomical structures and cortical parcellation schemes. To address this challenge, we extended the Foundational Model of Anatomy Ontology (FMA) to...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2010-06-01
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| Series: | Frontiers in Neuroinformatics |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fninf.2010.00010/full |
| _version_ | 1819241121191034880 |
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| author | Jessica A Turner Jose L. V Mejino James F Brinkley Landon T Detwiler Hyo Jong Lee Maryann E Martone Daniel L Rubin |
| author_facet | Jessica A Turner Jose L. V Mejino James F Brinkley Landon T Detwiler Hyo Jong Lee Maryann E Martone Daniel L Rubin |
| author_sort | Jessica A Turner |
| collection | DOAJ |
| description | The annotation of functional neuroimaging results for data sharing and reuse is particularly challenging, due to the diversity of terminologies of neuroanatomical structures and cortical parcellation schemes. To address this challenge, we extended the Foundational Model of Anatomy Ontology (FMA) to include cytoarchitectural, Brodmann area labels, and a morphological cortical labeling scheme (e.g., the part of Brodmann area 6 in the left precentral gyrus). This representation was also used to augment the neuroanatomical axis of RadLex, the ontology for clinical imaging. The resulting neuroanatomical ontology contains explicit relationships indicating which brain regions are “part of” which other regions, across cytoarchitectural and morphological labeling schemas. We annotated a large functional neuroimaging dataset with terms from the ontology and applied a reasoning engine to analyze this dataset in conjunction with the ontology, and achieved successful inferences from the most specific level (e.g., how many subjects showed activation in a sub-part of the middle frontal gyrus) to more general (how many activations were found in areas connected via a known white matter tract?). In summary, we have produced a neuroanatomical ontology that harmonizes several different terminologies of neuroanatomical structures and cortical parcellation schemes. This neuranatomical ontology is publicly available as a view of FMA at the Bioportal website at http://rest.bioontology.org/bioportal/ontologies/download/10005. The ontological encoding of anatomic knowledge can be exploited by computer reasoning engines to make inferences about neuroanatomical relationships described in imaging datasets using different terminologies. This approach could ultimately enable knowledge discovery from large, distributed fMRI studies or medical record mining. |
| first_indexed | 2024-12-23T14:18:52Z |
| format | Article |
| id | doaj.art-1bfc5d76bc8b4c729a994137f05288d5 |
| institution | Directory Open Access Journal |
| issn | 1662-5196 |
| language | English |
| last_indexed | 2024-12-23T14:18:52Z |
| publishDate | 2010-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroinformatics |
| spelling | doaj.art-1bfc5d76bc8b4c729a994137f05288d52022-12-21T17:43:50ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962010-06-01410.3389/fninf.2010.000101317Application of neuroanatomical ontologies for neuroimaging data annotationJessica A Turner0Jose L. V Mejino1James F Brinkley2Landon T Detwiler3Hyo Jong Lee4Maryann E Martone5Daniel L Rubin6MIND Research NetworkUniversity of WashingtonUniversity of WashingtonUniversity of WashingtonMIND Research NetworkUniversity of California Stanford UniversityThe annotation of functional neuroimaging results for data sharing and reuse is particularly challenging, due to the diversity of terminologies of neuroanatomical structures and cortical parcellation schemes. To address this challenge, we extended the Foundational Model of Anatomy Ontology (FMA) to include cytoarchitectural, Brodmann area labels, and a morphological cortical labeling scheme (e.g., the part of Brodmann area 6 in the left precentral gyrus). This representation was also used to augment the neuroanatomical axis of RadLex, the ontology for clinical imaging. The resulting neuroanatomical ontology contains explicit relationships indicating which brain regions are “part of” which other regions, across cytoarchitectural and morphological labeling schemas. We annotated a large functional neuroimaging dataset with terms from the ontology and applied a reasoning engine to analyze this dataset in conjunction with the ontology, and achieved successful inferences from the most specific level (e.g., how many subjects showed activation in a sub-part of the middle frontal gyrus) to more general (how many activations were found in areas connected via a known white matter tract?). In summary, we have produced a neuroanatomical ontology that harmonizes several different terminologies of neuroanatomical structures and cortical parcellation schemes. This neuranatomical ontology is publicly available as a view of FMA at the Bioportal website at http://rest.bioontology.org/bioportal/ontologies/download/10005. The ontological encoding of anatomic knowledge can be exploited by computer reasoning engines to make inferences about neuroanatomical relationships described in imaging datasets using different terminologies. This approach could ultimately enable knowledge discovery from large, distributed fMRI studies or medical record mining.http://journal.frontiersin.org/Journal/10.3389/fninf.2010.00010/fullData MiningNeuroanatomyontology |
| spellingShingle | Jessica A Turner Jose L. V Mejino James F Brinkley Landon T Detwiler Hyo Jong Lee Maryann E Martone Daniel L Rubin Application of neuroanatomical ontologies for neuroimaging data annotation Frontiers in Neuroinformatics Data Mining Neuroanatomy ontology |
| title | Application of neuroanatomical ontologies for neuroimaging data annotation |
| title_full | Application of neuroanatomical ontologies for neuroimaging data annotation |
| title_fullStr | Application of neuroanatomical ontologies for neuroimaging data annotation |
| title_full_unstemmed | Application of neuroanatomical ontologies for neuroimaging data annotation |
| title_short | Application of neuroanatomical ontologies for neuroimaging data annotation |
| title_sort | application of neuroanatomical ontologies for neuroimaging data annotation |
| topic | Data Mining Neuroanatomy ontology |
| url | http://journal.frontiersin.org/Journal/10.3389/fninf.2010.00010/full |
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