Summary

“Comparative topological analysis of neuronal arbors via sequence representation and alignment” By Todd Gillette, PhD | June 2015

This dissertation is focused on applying bioinformatic approaches to neuronal morphology to enable new discoveries and increase understanding about how morphology and neuron function interrelate.

Dissertation PDF

Posters

Mining Tree Patterns

Neuronal morphology plays a major role in the electrophysiological and connectivity characteristics of neurons, and thus in neuron and network function.

Various morphometrics have been applied in studying neurons; however, the structural patterns of the tree-like dendrites and axons have yet to be fully explored. These patterns may reflect strategies that achieve functional properties such as dendritic compartmentalization, space filling, and targeting of various spatial distributions of synapses.

To address these issues we analyzed thousands of neurons, made available via NeuroMorpho.Org, in terms of structural patterns by representing their arbors (axons, dendrites, apical dendrites) as gene-like sequences. We compared neurons by arborization type within and between cell classes using sequence analysis techniques. Sequence domains can be used in conjunction with functional studies to further elucidate the structure-function relationship.

Poster PDF

Big Neuron

BigNeuron: Building consensus among automated morphological reconstructions By Todd A. Gillette , Hanchuan Peng, Xiaoxiao Liu, Yinan Wan, Giorgio A. Ascoli

A community effort to find out what is exactly the state-of-the-art of single neuron reconstruction, standardize the protocols, and esablish a Big Data resource for neuroscience.

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Summary

The core article for David Hamilton’s dissertation is focused on the article in this post.

In order to alleviate this nomenclature confusion regarding hippocampal neuron types and properties, we introduce a new functionality of Hippocampome.org: a fully searchable, curated catalog of human and machine-readable definitions, each linked to the corresponding neuron and property terms.

Furthermore, we extend our robust approach to providing each neuron type with an informative name and unique identifier by mapping all encountered synonyms and homonyms.

Information

Name-calling in the hippocampus (and beyond): coming to terms with neuron types and properties

By D. J. Hamilton, D. W. Wheeler, C. M. White, C. L. Rees, A. O. Komendantov, M. Bergamino, G. A. Ascol Brain Informatics | June 9, 2016

Abstract

Widely spread naming inconsistencies in neuroscience pose a vexing obstacle to effective communication within and across areas of expertise. This problem is particularly acute when identifying neuron types and their properties. Hippocampome.org is a web-accessible neuroinformatics resource that organizes existing data about essential properties of all known neuron types in the rodent hippocampal formation. Hippocampome.org links evidence supporting the assignment of a property to a type with direct pointers to quotes and figures. Mining this knowledge from peer-reviewed reports reveals the troubling extent of ...