Selected Publications on neuromorphology

  

Neuronal Morphology Goes Digital: A Research Hub for Cellular and System Neuroscience

Neuron. Volume 77, Issue 6, p1017–1038, 20 March 2013

Abstract
The importance of neuronal morphology in brain function has been recognized for over a century. The broad applicability of “digital reconstructions” of neuron morphology across neuroscience subdisciplines has stimulated the rapid development of numerous synergistic tools for data acquisition, anatomical analysis, three-dimensional rendering, electrophysiological simulation, growth models, and data sharing. Here we discuss the processes of histological labeling, microscopic imaging, and semiautomated tracing. Moreover, we provide an annotated compilation of currently available resources in this rich research “ecosystem” as a central reference for experimental and computational neuroscience

http://www.cell.com/neuron/abstract/S0896-6273%2813%2900232-8
 


Advanced microscopy techniques for quantitative analysis in neuromorphology and neuropathology research: current status and requirements for the future.

Lemmens MA, Steinbusch HW, Rutten BP, Schmitz C. 

J Chem Neuroanat. 2010 Nov;40(3):199-209. doi: 10.1016/j.jchemneu.2010.06.005. 

Abstract

Visualizing neuromorphology and in particular neuropathology has been the focus of many researchers in the quest to solve the numerous questions that are still remaining related to several neurological and neuropsychiatric diseases. Over the last years, intense research into microscopy techniques has resulted in the development of various new types of microscopes, software imaging systems, and analysis programs. This review briefly discusses some key techniques, such as confocal stereology and automated neuron tracing and reconstruction, and their applications in neuroscience research. Special emphasis is placed on needs for further developments, such as the demand for higher-throughput analyses in quantitative neuromorphology. These developments will advance basic neuroscience research as well as pharmaceutical and biotechnology research and development. 

http://www.ncbi.nlm.nih.gov/pubmed/20600825



Digital pathology: a tool for 21st century neuropathology.

Guzman M, Judkins AR. 
Brain Pathol. 2009 Apr;19(2):305-16. doi: 10.1111/j.1750-3639.2009.00264.x.

Abstract

Digital pathology represents an electronic environment for performing pathologic analysis and managing the information associated with this activity. The technology to create and support digital pathology has largely developed over the last decade. The use of digital pathology tools is essential to adapt and lead in the rapidly changing environment of 21st century neuropathology. The utility of digital pathology has already been demonstrated by pathologists in several areas including consensus reviews, quality assurance (Q/A), tissue microarrays (TMAs), education and proficiency testing. These utilities notwithstanding, interface issues, storage and image formatting all present challenges to the integration of digital pathology into the neuropathology work environment. With continued technologic improvements, as well as the introduction of fluorescent side scanning and multispectral detection, future developments in digital pathology offer the promise of adding powerful analytic tools to the pathology work environment. The integration of digital pathology with biorepositories offers particular promise for neuropathologists engaged in tissue banking. The utilization of these tools will be essential for neuropathologists to continue as leaders in diagnostics, translational research and basic science in the 21st century.

http://www.ncbi.nlm.nih.gov/pubmed/19290997 



L-Measure: a web-accessible tool for the analysis, comparison and search of digital reconstructions of neuronal morphologies
Ruggero Scorcioni, Sridevi Polavaram & Giorgio A Ascoli
Nature Protocols 3, 866 - 876 (2008)
Published online: 24 April 2008 | doi:10.1038/nprot.2008.51
L-Measure (LM) is a freely available software tool for the quantitative characterization of neuronal morphology. LM computes a large number of neuroanatomical parameters from 3D digital reconstruction files starting from and combining a set of core metrics. After more than six years of development and use in the neuroscience community, LM enables the execution of commonly adopted analyses as well as of more advanced functions. This report illustrates several LM protocols: (i) extraction of basic morphological parameters, (ii) computation of frequency distributions, (iii) measurements from user-specified subregions of the neuronal arbors, (iv) statistical comparison between two groups of cells and (v) filtered selections and searches from collections of neurons based on any Boolean combination of the available morphometric measures. These functionalities are easily accessed and deployed through a user-friendly graphical interface and typically execute within few minutes on a set of ~20 neurons. The tool is available at http://krasnow.gmu.edu/cn3 for either online use on any Java-enabled browser and platform or download for local execution under Windows and Linux.

Δεν υπάρχουν σχόλια:

Δημοσίευση σχολίου

Σημείωση: Μόνο ένα μέλος αυτού του ιστολογίου μπορεί να αναρτήσει σχόλιο.