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First published June 25, 2008 as JAMIA PrePrint; doi:10.1197/jamia.M2358
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J Am Med Inform Assoc. 2008;15:671-678. DOI 10.1197/jamia.M2358.
© 2008 American Medical Informatics Association


Model Formulation

Modeling Functional Neuroanatomy for an Anatomy Information System

Jörg M. Niggemann, MD, Dipl Informa,1,*, Andreas Gebert, MDb and Stefan Schulz, MDc

a Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
b Institute of Anatomy, University of Lübeck, Lübeck, Germany
c Institute of Medical Biometry und Medical Informatics, Freiburg University Medical Center, Freiburg, Germany

* Correspondence: Dr. Jörg Niggemann, CompuGROUP Holding AG, Maria Trost 21, D-56070 Koblenz, Germany (Email: joerg.niggemann{at}thoughtblade.com).

Received for publication: 12/29/06; accepted for publication: 05/04/08.

Objective: Existing neuroanatomical ontologies, databases and information systems, such as the Foundational Model of Anatomy (FMA), represent outgoing connections from brain structures, but cannot represent the "internal wiring" of structures and as such, cannot distinguish between different independent connections from the same structure. Thus, a fundamental aspect of Neuroanatomy, the functional pathways and functional systems of the brain such as the pupillary light reflex system, is not adequately represented. This article identifies underlying anatomical objects which are the source of independent connections (collections of neurons) and uses these as basic building blocks to construct a model of functional neuroanatomy and its functional pathways.

Design: The basic representational elements of the model are unnamed groups of neurons or groups of neuron segments. These groups, their relations to each other, and the relations to the objects of macroscopic anatomy are defined. The resulting model can be incorporated into the FMA.

Measurements: The capabilities of the presented model are compared to the FMA and the Brain Architecture Management System (BAMS).

Results: Internal wiring as well as functional pathways can correctly be represented and tracked.

Conclusion: This model bridges the gap between representations of single neurons and their parts on the one hand and representations of spatial brain structures and areas on the other hand. It is capable of drawing correct inferences on pathways in a nervous system. The object and relation definitions are related to the Open Biomedical Ontology effort and its relation ontology, so that this model can be further developed into an ontology of neuronal functional systems.







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Copyright © 2008 by the American Medical Informatics Association.