Wanner, Adrian A.. Reconstruction of neuronal activity and connectivity patterns in the zebrafish olfactory bulb. 2016, PhD Thesis, University of Basel, Faculty of Science.
Available under License CC BY (Attribution).
Official URL: http://edoc.unibas.ch/diss/DissB_11738
I combined in vivo twophoton calcium imaging with dense circuit reconstruction from complete serial block-face electron microscopy (SBEM) stacks of the larval zebrafish OB (4.5 dpf) with a voxel size of 9x9x25nm. To address bottlenecks in the workflow of SBEM, I developed a novel embedding and staining procedure that effectively reduces surface charging in SBEM and enables to acquire SBEM stacks with at least a ten-fold increase in both, signal-to-noise as well as acquisition speed.
I set up a high throughput neuron reconstruction pipeline with >30 professional tracers that is available for the scientific community (ariadne-service.com). To assure efficient and accurate circuit reconstruction, I developed PyKNOSSOS, a Python software for skeleton tracing and synapse annotation, and CORE, a skeleton consolidation procedure that combines redundant reconstruction with targeted expert input.
Using these procedures I reconstructed all neurons (>1000) in the larval OB. Unlike in the adult OB, INs were rare and appeared to represent specific subtypes, indicating that different sub-circuits develop sequentially. MCs were uniglomerular whereas inter-glomerular projections of INs were complex and biased towards groups of glomeruli that receive input from common types of sensory neurons. Hence, the IN network in the OB exhibits a topological organization that is governed by glomerular identity.
Calcium imaging revealed that the larval OB circuitry already decorrelates activity patterns evoked by similar odors. The comparison of inter-glomerular connectivity to the functional interactions between glomeruli indicates that pattern decorrelation depends on specific, non-random inter-glomerular IN projections. Hence, the topology of IN networks in the OB appears to be an important determinant of circuit function.
|Advisors:||Friedrich, Rainer W. and Hahnloser, Richard|
|Faculties and Departments:||09 Associated Institutions > Friedrich Miescher Institut FMI > Neuronal circuits and computations (Friedrich)|
|Bibsysno:||Link to catalogue|
|Number of Pages:||1 Online-Ressource (178 Seiten)|
|Last Modified:||16 Sep 2016 08:20|
|Deposited On:||16 Sep 2016 08:17|
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