An ontological approach to describing neurons and their relationships

Abstract

The advancement of neuroscience, perhaps one of the most information rich disciplines of all the life sciences, requires basic frameworks for organizing the vast amounts of data generated by the research community to promote novel insights and integrated understanding. Since Cajal, the neuron remains a fundamental unit of the nervous system, yet even with the explosion of information technology, we still have few comprehensive or systematic strategies for aggregating cell-level knowledge. Progress toward this goal is hampered by the multiplicity of names for cells and by lack of a consensus on the criteria for defining neuron types. However, through umbrella projects like the Neuroscience Information Framework (NIF) and the International Neuroinformatics Coordinating Facility (INCF), we have the opportunity to propose and implement an informatics infrastructure for establishing common tools and approaches to describe neurons through a standard terminology for nerve cells and a database (a Neuron Registry) where these descriptions can be deposited and compared. This article provides an overview of the problem and outlines a solution approach utilizing ontological characterizations. Based on illustrative implementation examples, we also discuss the need for consensus criteria to be adopted by the research community, and considerations on future developments. A scalable repository of neuron types will provide researchers with a resource that materially contributes to the advancement of neuroscience.

Keywords: characterization; neuron; ontology; part; property; relationship; type; value.

Figure 1

Ontological Graphical Depiction (courtesy of the INCF Neuron Registry task force) and Neuron Registry Establishment → and illustration of the many-to-many relationship between neurons and their properties. The Neuron Registry will constitute a resource to browse and search neuron types based on their properties, and properties based on the neuron types in which they are found.

Figure 2

NeuroLex—Neuroscience Lexicon.

Figure 3

Neuron Registry NIF Interface—This is a concept diagram depicting a planned capability not yet realized at the time of this writing.

Figure 4

Schema Mapping using Harmony—Interoperability among neuroinformatic resources is aided through synchronization and sharing of data. Schema matching across disparate informatic repositories is critical to this sharing. Harmony assists the implementer in mapping data types properly so as to preserve integrity of meaning. Both automated (e.g., pattern recognition) and manual (e.g., thresholding) techniques are leveraged in this tool.

Figure 5

Neuron Registry Extended Entity-Relationship Diagram.

Figure 6

Neuron Registry Curator Interface—List and Edit views (http://incfnrci.appspot.com/).

Figure 7

Mapping of a freeform neuronal description of the defining properties of an Olfactory bulb (main) mitral cell into a part-relation-value ontological description.