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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Main Authors: Marcelo eTallis, Richard eThompson, Thomas eRuss, Gully A P C Burns
Format: Article
Language:English
Published: Frontiers Media S.A. 2011-11-01
Series:Frontiers in Neuroinformatics
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fninf.2011.00024/full
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spelling 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
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AT thomaseruss knowledgesynthesiswithmapsofneuralconnectivity
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