Knowledge synthesis with maps of neural connectivity
This paper describes software for neuroanatomical knowledge synthesis based on high-quality neural connectivity data. This software supports a mature neuroanatomical methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural conn...
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doaj-1d994b5c5e9f47da98a1be3cfa861b252020-11-24T21:09:06ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962011-11-01510.3389/fninf.2011.000248857Knowledge synthesis with maps of neural connectivityMarcelo eTallis0Richard eThompson1Thomas eRuss2Gully A P C Burns3USC Information Sciences InstituteUniversity of Southern CaliforniaUSC Information Sciences InstituteUSC Information Sciences InstituteThis paper describes software for neuroanatomical knowledge synthesis based on high-quality neural connectivity data. This software supports a mature neuroanatomical methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macroconnections using the Swanson 3rd edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the neuroanatomical data mapping components within a unified web-application. As a step towards developing an accurate sub-regional account of neural connectivity, we provide navigational access between the neuroanatomical data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called ’Knowledge Engineering from Experimental Design’ (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web application that allows anatomical data sets to be described within a standard experimental context and thus incorporated with non-spatial data sets.http://journal.frontiersin.org/Journal/10.3389/fninf.2011.00024/fullSoftwaretract-tracingKnowledge EngineeringNeuroanatomical Mapping |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Marcelo eTallis Richard eThompson Thomas eRuss Gully A P C Burns |
spellingShingle |
Marcelo eTallis Richard eThompson Thomas eRuss Gully A P C Burns Knowledge synthesis with maps of neural connectivity Frontiers in Neuroinformatics Software tract-tracing Knowledge Engineering Neuroanatomical Mapping |
author_facet |
Marcelo eTallis Richard eThompson Thomas eRuss Gully A P C Burns |
author_sort |
Marcelo eTallis |
title |
Knowledge synthesis with maps of neural connectivity |
title_short |
Knowledge synthesis with maps of neural connectivity |
title_full |
Knowledge synthesis with maps of neural connectivity |
title_fullStr |
Knowledge synthesis with maps of neural connectivity |
title_full_unstemmed |
Knowledge synthesis with maps of neural connectivity |
title_sort |
knowledge synthesis with maps of neural connectivity |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neuroinformatics |
issn |
1662-5196 |
publishDate |
2011-11-01 |
description |
This paper describes software for neuroanatomical knowledge synthesis based on high-quality neural connectivity data. This software supports a mature neuroanatomical methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macroconnections using the Swanson 3rd edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the neuroanatomical data mapping components within a unified web-application. As a step towards developing an accurate sub-regional account of neural connectivity, we provide navigational access between the neuroanatomical data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called ’Knowledge Engineering from Experimental Design’ (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web application that allows anatomical data sets to be described within a standard experimental context and thus incorporated with non-spatial data sets. |
topic |
Software tract-tracing Knowledge Engineering Neuroanatomical Mapping |
url |
http://journal.frontiersin.org/Journal/10.3389/fninf.2011.00024/full |
work_keys_str_mv |
AT marceloetallis knowledgesynthesiswithmapsofneuralconnectivity AT richardethompson knowledgesynthesiswithmapsofneuralconnectivity AT thomaseruss knowledgesynthesiswithmapsofneuralconnectivity AT gullyapcburns knowledgesynthesiswithmapsofneuralconnectivity |
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