The University of Southampton
University of Southampton Institutional Repository

Confocal quality imaging of afferent neurons from semi-thin sections of Drosophila ganglia

Confocal quality imaging of afferent neurons from semi-thin sections of Drosophila ganglia
Confocal quality imaging of afferent neurons from semi-thin sections of Drosophila ganglia
The aim of this study was to develop protocols for computer imaging of the thoraco-abdominal ganglion of Drosophila from serial semi-thin sections, in which specific neurons were stained and related to neuropilar structures. The central projections of a subset of transgenically labelled sensory neurons were revealed by immunohistochemistry, while Nomarski optics were used to show motor neuron targets in the neuropil. Digital photomicrographs of each section were aligned and the resultant image stacks rendered into three-dimensional (3D) images that can be rotated in real time. The result is a detailed, in-depth visualization of labelled neurons at a resolution comparable with that in confocal reconstructions, which also allows investigation of their relationships with other components of the neuropil.
drosophila, enhancer trap, computer imaging, three-dimensional reconstruction, monosynaptic connections
0304-3940
93-96
Tyrer, N. Mark
f90ab83e-020a-426a-a532-6d64461224c2
Maddison, John
a8a56af6-37f7-49cf-bb88-4f0eed00e76d
Shepherd, David
11aa6858-d19c-4450-82ff-11dff9dcd9c4
Williams, Darren W.
604e70da-4237-4069-87b0-6dff0917ca49
Tyrer, N. Mark
f90ab83e-020a-426a-a532-6d64461224c2
Maddison, John
a8a56af6-37f7-49cf-bb88-4f0eed00e76d
Shepherd, David
11aa6858-d19c-4450-82ff-11dff9dcd9c4
Williams, Darren W.
604e70da-4237-4069-87b0-6dff0917ca49

Tyrer, N. Mark, Maddison, John, Shepherd, David and Williams, Darren W. (2000) Confocal quality imaging of afferent neurons from semi-thin sections of Drosophila ganglia. Neuroscience Letters, 296 (2-3), 93-96. (doi:10.1016/S0304-3940(00)01611-6).

Record type: Article

Abstract

The aim of this study was to develop protocols for computer imaging of the thoraco-abdominal ganglion of Drosophila from serial semi-thin sections, in which specific neurons were stained and related to neuropilar structures. The central projections of a subset of transgenically labelled sensory neurons were revealed by immunohistochemistry, while Nomarski optics were used to show motor neuron targets in the neuropil. Digital photomicrographs of each section were aligned and the resultant image stacks rendered into three-dimensional (3D) images that can be rotated in real time. The result is a detailed, in-depth visualization of labelled neurons at a resolution comparable with that in confocal reconstructions, which also allows investigation of their relationships with other components of the neuropil.

This record has no associated files available for download.

More information

Published date: 22 December 2000
Keywords: drosophila, enhancer trap, computer imaging, three-dimensional reconstruction, monosynaptic connections

Identifiers

Local EPrints ID: 55849
URI: http://eprints.soton.ac.uk/id/eprint/55849
ISSN: 0304-3940
PURE UUID: a4d33495-a983-4c47-bef8-bf2193a03c5f
ORCID for David Shepherd: ORCID iD orcid.org/0000-0002-6961-7880

Catalogue record

Date deposited: 21 Aug 2008
Last modified: 06 Aug 2024 01:52

Export record

Altmetrics

Contributors

Author: N. Mark Tyrer
Author: John Maddison
Author: David Shepherd ORCID iD
Author: Darren W. Williams

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×