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Computational Modeling Methods for Neuroscientists$
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Erik De Schutter

Print publication date: 2009

Print ISBN-13: 9780262013277

Published to MIT Press Scholarship Online: August 2013

DOI: 10.7551/mitpress/9780262013277.001.0001

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PRINTED FROM MIT PRESS SCHOLARSHIP ONLINE (www.mitpress.universitypressscholarship.com). (c) Copyright The MIT Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in MITSO for personal use.date: 27 February 2021

An Approach to Capturing Neuron Morphological Diversity

An Approach to Capturing Neuron Morphological Diversity

Chapter:
(p.211) 9 An Approach to Capturing Neuron Morphological Diversity
Source:
Computational Modeling Methods for Neuroscientists
Author(s):

Haroon Anwar

Imad Riachi

Sean Hill

Felix Schürmann

Henry Markram

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262013277.003.0010

This chapter analyzes an algorithm for repairing computer-based neuronal reconstructions. It deals with a new probability density cloud approach for characterizing and repairing neuron dendritic and axonal morphologies. The chapter uses a layer 2 pyramidal cell to validate the dendritic repair process. In the repair algorithm, it assumes that the dendrites of neurons have a statistical symmetry in their morphologies, although they do not necessarily seem geometrically symmetric. The chapter also shows that the algorithm depends on the quality as well as the quantity of the population of cells.

Keywords:   repair algorithm, neuronal reconstructions, probability density cloud, neuron dendritic morphology, neuron axonal morphology, dendrites

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