Calcium Imaging
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Prof Geoff Goodhill
A new NIH-funded collaboration between David Prober (Caltech), Thai Truong (USC) and Geoff Goodhill (Washington University in St Louis) aims to gain new insight into the neural circuits underlying sleep, through a combination of whole-brain neural recordings in zebrafish and theoretical/computational modeling. The Goodhill lab is now looking for 2 postdocs for the modeling and computational analysis components. Using novel 2-photon imaging technologies Prober and Truong will record from the entire larval zebrafish brain at single-neuron resolution continuously for long periods of time, examining neural circuit activity during normal day-night cycles and in response to genetic and pharmacological perturbations. The Goodhill lab will analyze the resulting huge datasets using a variety of sophisticated computational approaches, and use these results to build new theoretical models that reveal how neural circuits interact to govern sleep. Theoretical and experimental work will be intimately linked.
Prof Georges Debrégeas
Zebrafish larva possesses a combination of assets – small dimensions, brain transparency, genetic tractability – which makes it a unique vertebrate model system to probe brain-scale neuronal dynamics. Using light-sheet microscopy, it is currently possible to monitor the activity of the entire brain at cellular resolution using functional calcium imaging, at about 1 full brain/second. The student will harness this unique opportunity to dissect the neural computation at play during sensory-driven navigation. 5-7 days old larvae will be partially restrained in agarose, i.e. with their tail free. Real-time video-monitoring of the tail beats will be used to infer virtual navigational parameters (displacement, reorientation); visual or thermal stimuli will be delivered to the larvae in a manner that will simulate a realistic navigation along light or thermal gradients. During this virtual sensory-driven navigation, the brain activity will be monitored using two-photon light-sheet functional imaging. These experiments will provide rich datasets of whole-brain activity during a complex sensorimotor task. The network dynamics will be analysed in order to extract a finite number of brain states associated with various motor programs. Starting from spontaneous navigation phases (i.e. absence of varying sensory cues), the student will analyse how different sensory cues interfere with the network endogenous dynamics to bias the probability of these different brain states and eventually favor movements along sensory gradients. For more information see: https://www.smartnets-etn.eu/whole-brain-network-dynamics-in-zebrafish-larvae-during-spontaneous-and-sensory-driven-virtual-navigation/
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