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Learning from connectomics on the fly

Authors :
Marta Costa
Gregory S.X.E. Jefferis
Philipp Schlegel
Schlegel, Philipp [0000-0002-5633-1314]
Jefferis, Gregory [0000-0002-0587-9355]
Apollo - University of Cambridge Repository
Source :
Current Opinion in Insect Science
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

Parallels between invertebrates and vertebrates in nervous system development, organisation and circuits are powerful reasons to use insects to study the mechanistic basis of behaviour. The last few years have seen the generation in Drosophila melanogaster of very large light microscopy data sets, genetic driver lines and tools to report or manipulate neural activity. These resources in conjunction with computational tools are enabling large scale characterisation of neuronal types and their functional properties. These are complemented by 3D electron microscopy, providing synaptic resolution data. A whole brain connectome of the fly larva is approaching completion based on manual reconstruction of electron-microscopy data. An adult whole brain dataset is already publicly available and focussed reconstruction is under way, but its 40× greater volume would require ∼500-5000 person-years of manual labour. Nevertheless rapid technical improvements in imaging and especially automated segmentation will likely deliver a complete adult connectome in the next 5 years. To enhance our understanding of the circuit basis of behaviour, light and electron microscopy outputs must be integrated with functional and physiological information into comprehensive databases. We review presently available data, tools and opportunities in Drosophila. We then consider the limits and potential of future progress and how this may impact neuroscience in rich model systems provided by larger insects and vertebrates.

Details

ISSN :
22145745
Volume :
24
Database :
OpenAIRE
Journal :
Current Opinion in Insect Science
Accession number :
edsair.doi.dedup.....687951ca2d10bf3d01a28530410f0676
Full Text :
https://doi.org/10.1016/j.cois.2017.09.011